These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\n
This collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\n
To celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\n
Initially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\n
This collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\n
To celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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\n\t\t\t
1. Introduction
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Multibody dynamics methods are being used extensively to model biomolecular systems to study important physical phenomena occurring at different spatial and temporal scales [1], [2]. These systems may contain thousands or even millions of degrees of freedom, whereas, the size of the time step involved during the simulation is on the order of femto seconds. Examples of such problems may include proteins, DNAs, and RNAs. These highly complex physical systems are often studied at resolutions ranging from a fully atomistic model to coarse-grained molecules, up to a continuum level system [3], [4], [5]. In studying these problems, it is often desirable to change the system definition during the course of the simulation in order to achieve an optimal combination of accuracy and speed. For example, in order to study the overall conformational motion of a bimolecular system, a model based on super-atoms (beads) [6], [7] or articulated multi-rigid and/or flexible body [8], [9] can be used. Whereas, localized behavior has to be studied using fully atomistic models. In such cases, the need for the transition from a fine-scale to a coarse model and vice versa arises. Illustrations of a fully atomistic model of a molecule, and its coarse-grained model are shown in Fig. (1-a) and Fig. (1-b).
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(a) Fully atomistic model
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(b) Mixed type multibody model
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Figure 1.
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Illustration of a biomolecular system. a) Fully atomistic model. b) Coarse grain model with different rigid and flexible sub-domains connected to each other via kinematic joints.
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Given the complexity and nonlinearity of challenging bimolecular systems, it is expected that different physical parameters such as dynamic boundary conditions and applied forces will have a significant affect on the behavior of the system. It is shown in [10] that time-invariant coarse models may provide inadequate or poor results and as such, an adaptive framework to model these systems should be considered [11]. Transitions between different system models can be achieved by intelligently removing or adding certain degrees of freedom . This change occurs instantaneously and as such, may be viewed as model changes as a result of impulsively applied constraints. For multi-rigid and flexible body systems, the transition from a higher fidelity (fine-scale) model to a lower fidelity model (coarse-scale) using divide-and-conquer algorithm (DCA) has been studied previously in [12], [13]. DCA efficiently provides the unique states of the system after this transition. In this chapter, we focus on the transition from a coarse model to a fine-scale model. When the system is modeled in an articulated multi-flexible-body framework, such transitions may be achieved by two different means. In the first, a fine-scale model is generated by adding flexible . This type of fine scaling may be necessary in order to capture higher frequency modes. For instance, when two molecules bind together, due to the impact, the higher frequency modes of the system are excited. The second type of fine scaling transition may be achieved through releasing the connecting joints in the multi-flexible-body system. In other words, certain constraints on joints are removed to introduce new in the model.\n
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In contrast to those types of dynamic systems in which the model definition is persistent, and the total energy of the system is conserved, the class of problems discussed here experiences discontinuous changes in the model definition and hence, the energy of the system must also change (nominally increase) in a discontinuous fashion. During the coarse graining process, based on a predefined metric, one may conclude that naturally existing higher modes are less relevant and can be ignored. As such, the kinetic energy associated with those modes must be estimated and properly accounted for, when transitioning back to the fine-scale model. Moreover, any change in the system model definition is assumed to occur as a result of impulsively applied constraints, without the influence of external loads. As such, the generalized momentum of the system must also be conserved [14]. In other words, the momentum of each differential element projected onto the space of admissible motions permitted by the more restrictive model (whether pre- or post-transition) when integrated over the entire system must be conserved across the model transition. If the generalized momentum is not conserved during the transition, the results are non-physical, and the new initial conditions for the rest of the simulation of the system are invalid.
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In the next section, a brief overview of the DCA and analytical preliminaries necessary to the algorithm development are presented. The optimization problem associated with the coarse to fine scale transitioning is discussed next. Then the impulse-momentum formulation for transitioning from coarse models to fine-scale models in the articulated flexible-body scheme is presented. Finally conclusions are made.
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2. Theoretical background
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In this section, a brief introduction of the basic divide-and-conquer algorithm is presented. The DCA scheme has been developed for the simulation of general multi-rigid and multi-flexible-body systems [15], [16], [13], and systems with discontinuous changes [17], [12]. The basic algorithm described here is independent of the type of problem and is presented so that the chapter might be more self contained. In other words, it can be used to study the behavior of any rigid- and flexible-body system, even if the system undergoes a discontinuous change. Some mathematical preliminaries are also presented in this section which are important to the development of the algorithm.
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2.1. Basic divide-and-conquer algorithm
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The basic DCA scheme presented in this chapter works in a similar manner described in detail in [15], [16]. Consider two representative flexible bodies and connected to each other by a joint as shown in Fig. (2-a). The two points of interest, and , on body are termed handles. A handle is any selected point through which a body interacts with the environment. In this chapter, we will limit our attention to each body having two handles, and each handle coincides with the joint location on the body, i.e. joint locations and in case of body . Similarly, for body , the points and are located at the joint locations and , respectively. Furthermore, large rotations and translations in the flexible bodies are modeled as rigid body . Elastic deformations in the flexible bodies are modeled through the use of modal coordinates and admissible shape functions.
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DCA is implemented using two main processes, hierarchic assembly and disassembly. The goal of the assembly process is to find the equations describing the dynamics of each body in the hierarchy at its two handles. This process begins at the level of individual bodies and adjacent bodies are assembled in a binary tree configuration. Using recursive formulations, this process couples the two-handle equations of successive bodies to find the two-handle equations of the resulting assembly. For example, body and body are coupled together to form the assembly shown in Fig. (2-b). At the end of the assembly process, the two-handle equations of the entire system are obtained.
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(a) Consecutive bodies
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(b) Assembly
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Figure 2.
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Assembling of the two bodies to form a subassembly. a) Consecutive bodies k and k+1. b) A fictitious subassembly formed by coupling bodies k and k+1.
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The hierarchic disassembly process begins with the solution of the two-handle equations associated with the primary node of the binary tree. The process works from this node to the individual sub-domain nodes of the binary tree to solve for the two-handle equations of the constituent subassemblies. This process is repeated until all unknowns (e.g., spatial constraint forces, spatial constraint impulses, spatial accelerations, jumps in the spatial velocities) of the bodies at the individual sub-domain level of the binary tree are known. The assembly and disassembly processes are illustrated in Fig. (?).
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Figure 3.
The hierarchic assembly-disassembly process in DCA.
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2.2. Analytical preliminaries
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For convenience, the superscript shows that a quantity of interest is associated with the coarse model, while denotes that it is associated with the fine model. For example, the column matrix represents the velocity of handle-1 in the coarse model, and represents the velocity of the same handle in the fine-scale model. In these matrices, and are the spatial velocity vector of handle-1 and the associated generalized modal speeds, respectively.
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As discussed previously, the change in the system model definition may occur by changing the number of flexible modes used to describe the behavior of flexible bodies, and/or the number of of the connecting joints. To implement these changes in the system model mathematically, the joint free-motion map is defined as follows.
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The joint free-motion map can be interpreted as the matrix of the free-modes of motion permitted by the degree-of-freedom joint, . In other words, maps generalized speeds associated with relative free motion permitted by the joint into a spatial relative velocity vector which may occur across the joint, [15]. For instance, consider a transition in which a spherical joint in the system is altered, where only one is locked about the first axis. The joint free-motion maps of the fine and coarse models in this case are shown in the following:
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We define the orthogonal complement of the joint free-motion map, . As such, by definition one arises at the following
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3. Optimization problem
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Any violation in the conservation of the generalized momentum of the system in the transition between different models leads to non-physical results since the instantaneous switch in the system model definition is incurred without the influence of any external load. In other words, the momentum of each differential element projected onto the space\nof the admissible motions permitted by the more restrictive model (whether pre- or post-transition) when integrated over the entire system must be conserved across the model transition [14]. Jumps in the system partial velocities due to the sudden change in the model resolution result in the jumps in the generalized speeds corresponding to the new set of degrees of freedom. Since the model is instantaneously swapped, the position of the system does not change. Hence, the position dependent forces acting on the system do not change, and do not affect the generalized speeds. Any change in the applied loads (e.g., damping terms) which might occur due to the change in the model definition and the associated velocity jumps do not contribute to the impulse-momentum equations which describe the model transition. This is because these changes in the applied loads are bounded, and integrated over the infinitesimally short transition time.\n
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Consider a fine-scale model with . Let the of the model reduce to after the imposition of certain instantaneous constraints. In this case, the conservation of the generalized momentum of the system is expressed as
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In the above equation, and represent the momenta of the coarse and fine models, respectively, projected on to the space of partial velocity vectors of the coarse model. Equation (?) provides a set of equations which are linear in the generalized speeds of the coarse model and solvable for the unique and physically meaningful states of the system after the transition to the coarser model.
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Now consider the case in which, the coarse model is transitioned back to the fine-scale model. Equation (?) is still valid, and provides equations with unknown generalized speeds of the finer model. Furthermore, during the coarsening process, the level of the kinetic energy also drops because we chose to ignore certain modes of the system. However, in actual biomolecular systems such a decrease in energy does not happen. Consequently, it is important to realize the proper kinetic energy when transitioning back to the fine-scale model. Therefore, the following equation must be satisfied
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In the above equation is the column matrix containing the generalized speeds of the fine model, and represents the generalized inertia matrix of the fine model.\nIt is clear that Eqs.�(?) and (?) provide equations with unknowns. This indicates that the problem is under-determined when multiple of the system are released. We may arrive at a unique or finite number of solutions, solving the following optimization problem\n
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In the above equation, is the physics- or knowledge- or mathematics-based objective function to be optimized (nominally minimized) subjected to the constraint equations . In [18], [19], different objective functions are proposed for coarse to fine-scale transition problems. For instance, in order to prevent the generalized speeds of the new fine-scale model from deviating greatly from those of the coarse scale model, we may minimize the norm of the difference between the generalized speeds of the coarse and fine scale models as follows
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As indicated previously, constraint equations governing the optimization problem are obtained from the conservation of the generalized momentum of the system within the transition. The rest of the constraint equations are obtained from other information about the system, such as the specific value of kinetic energy or the temperature of the system.
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The generalized momenta balance equations from Eq.�(?) are expressed as
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where and are and known matrices, respectively, and is an column matrix of the generalized speeds of the fine-scale system model. As a part of the optimization problem, one must solve this linear system for dependent generalized speeds in terms of independent generalized speeds. Therefore, the optimization is performed on a much smaller number () variables, with a cost of . For a complex molecular system, could be very large, and , hence a significant reduction is achieved in the overall cost of optimization as compared to other traditional techniques, such as Lagrange multipliers [20]. However, the computations required to find the relations between dependent and independent generalized speeds can impose a significant burden on these simulations.\nIt is shown in [21] that if traditional methods such as Gaussian elimination or LU factorization are used to find these relations, this cost tends to be . The DCA scheme provided here finds these relations at the end of the hierarchic disassembly process with computational complexity of almost in serial implementation. In other words, in this strategy, DCA formulates the impulse-momentum equations of the system which is followed by providing the relations between dependent and independent generalized speeds of the system in a timely manner. As such, this significantly reduces the costs associated with forming and solving the optimization problem in the transitions to the finer models.
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4. DCA-based momenta balance for multi-flexible bodies
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In this section, two-handle impulse-momentum equations of flexible bodies are derived. Mathematical modeling of the transition from a coarse model to a fine-scale model is discussed. For the fine-scale to coarse-scale model transition in multi-flexible-body system the reader is referred to [22], [23]. We will now derive the two-handle impulse-momentum equations when flexible degrees of freedom of a flexible body or the joints in the system are released. Then, the assembly of two consecutive bodies for which the connecting joint is unlocked is discussed. Finally, the hierarchic assembly-disassembly process for the multi-flexible-body system is presented.
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4.1. Two-handle impulse-momentum equations in coarse to fine transitions
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Now, we develop the two-handle impulse-momentum equations for consecutive flexible bodies in the transition from a coarse model to a fine-scale model. It is desired to develop the handle equations which express the spatial velocity vectors of the handles after the transition to the finer model as explicit functions of only newly introduced modal generalized speeds of the fine model. For this purpose, we start from the impulse-momentum equation of the flexible body as
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where and are the inertia matrices associated with the fine-scale and coarse models, respectively. Also, and represent the time right before and right after the transition. The quantities and are the spatial impulsive constraint forces on handle-1 and handle-2 of the flexible body. The matrices and are the coefficients resulting from the generalized constraint force contribution at handle-1 and handle-2, respectively. Moreover, in Eq.�(?), the impulses due to the applied loads are not considered since they represent a bounded loads integrated over an infinitesimal time interval. For detailed derivation of these quantities the reader is referred to [13]. It is desired to develop the handle equations which provide the spatial velocity vectors of the handles right after the transition to the fine-scale model in terms of newly added modal generalized speeds. Therefore, in Eq.�(?), the inertia matrix of the flexible body is represented by its components corresponding to rigid and flexible modes, as well as the coupling terms
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which is decomposed to the following relations\n
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Since the generalized momentum equations are calculated based on the projection onto the space of the coarser model, the matrix is not a square matrix and thus is not invertible. However, we can partition Eq.�(?) in terms of dependent (those associated with the coarser model) and independent (newly introduced) generalized speeds as
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Using the above relation, the expression for the dependent generalized modal speeds is written as
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Defining
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and using Eqs.�(?) and (?), the spatial velocity vector of handle-1 can be written in terms of the independent modal speeds
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid24
\n\t\t\t\t
As such, the spatial velocity vector of handle-2 becomes
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid25
\n\t\t\t\t
Employing the same partitioning technique, Eqs.�(?) can be written as\n
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid26
\n\t\t\t\t
Using
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid27
\n\t\t\t\t
and Eq.�(?), the spatial velocity vector of handle-2 can be written as
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid28
\n\t\t\t\t
Equations (?) and (?) are now in two-handle impulse-momentum form and along with Eq.�(?), give the new velocities associated with each handle after the transition. These equations express the spatial velocity vectors of the handles of the body as well as the modal generalized speeds which have not changed within the transition in terms of the newly added modal generalized speeds. This important property will be used in the optimization problem to provide the states of the system after the transition to the finer models.
\n\t\t\t\t
As such, the two-handle equations describing the impulse-momentum of two consecutive bodies, body and body are expressed as\n
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid29
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
4.2. Assembly process and releasing the joint between two consecutive bodies
\n\t\t\t\t
In this section, a method to combine the two-handle equations of individual flexible bodies to form the equations of the resulting assembly is presented. Herein, the assembly process of the consecutive bodies is discussed only within the transition from a coarse model to a finer model. This transition is achieved by releasing the joint between two consecutive bodies. Clearly, this would mean a change in the joint free-motion map and its orthogonal complement . It will become evident that the assembly process of the consecutive bodies for the fine to coarse transition is similar, and the associated equations can be easily derived by following the given procedure.
\n\t\t\t\t
From the definition of joint free-motion map, the relative spatial velocity vector at the joint between two consecutive bodies is expressed by the following kinematic constraint
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid31
\n\t\t\t\t
In the above equation, is the relative generalized speed defined at the joint of the fine model. From Newton\'s third law of motion, the impulses at the intermediate joint are related by
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid32
\n\t\t\t\t
Substituting Eqs.�(?), (?) and (?) into Eq.�(?) results in
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid33
\n\t\t\t\t
Using the definition of the joint free-motion map, the spatial constraint impulses lie exactly in the space spanned by the orthogonal complement of joint free-motion map of the coarser model. These constraint impulses can be expressed as
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid34
\n\t\t\t\t
In the above equation, is an ordered measure number of the impulsive constraint torques and forces. Pre-multiplying Eq.�(?) by , one arrives at the expression for as
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid35
\n\t\t\t\t
where
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid36
\n\t\t\t\t
Using Eqs.�(?), (?), and (?), we write the two-handle equations for the assembly\n\n
\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid37
\n\t\t\t\t
where:
\n\t\t\t\t\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\tuid38
\n\t\t\t\t
The two-handle equations of the resultant assembly express the spatial velocity vectors of the terminal handles of the assembly in terms of the spatial constraint impulses on the same handles, as well as the newly added modal generalized speeds of each constituent flexible body, and the newly introduced at the connecting joint. These are the equations which address the dynamics of the assembly when both types of transitions occur simultaneously. In other words, they are applicable when new flexible modes are added to the flexible constituent subassemblies and new degrees of freedom are released at the connecting joint. If there is no change in the joint free-motion map, the spatial partial velocity vector associated with does not appear in the handle equations of the resulting assembly.
\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
5. Hierarchic assembly-disassembly
\n\t\t\t
The DCA is implemented in two main passes: assembly and disassembly [13], [16].\nAs mentioned previously, two consecutive bodies can be combined together to recursively form the handle equations of the resulting assembly. As such, the assembly process starts at the individual sub-domain level of the binary tree to combine the adjacent bodies and form the equations of motion of the resulting assembly. This process is recursively implemented as that of the binary tree to find the impulse-momentum equations of the new assemblies. In this process, the spatial velocity vector (after transition) and impulsive load of the handles at the common joint of the consecutive bodies are eliminated. The handle equations of the resulting assembly are expressed in terms of the constraint impulses and spatial velocities of the terminal handles, as well as the newly introduce modal generalized speeds and generalized speeds associated with the newly added degrees of freedom at the connecting joints. This process stops at the top level of the binary tree in which the impulse-momentum equations of the entire system are expressed by the following two-handle equations
\n\t\t\t
\n\t\t\t\t\n\t\t\tuid39
\n\t\t\t
Note that through the partial velocity vectors , these equations are linear in terms of the newly added generalized modal speeds as well as the generalized speeds associated with the released at the joints of the system.
\n\t\t\t
The two-handle equations for the assembly at the primary node is solvable by imposing appropriate boundary conditions. Solving for the unknowns of the terminal handles initiates the disassembly process [17], [18]. In this process, the known quantities of the terminal handles of each assembly are used to solve for the spatial velocities and the impulsive loads at the common joint of the constituent subassemblies using the handle equations of each individual subassembly. This process is repeated in a hierarchic disassembly of the binary tree where the known boundary conditions are used to solve the impulse-momentum equations of the subassemblies, until the spatial velocities of the fine model and impulses on all bodies in the system are determined as a known linear function of the newly introduced generalized speeds of the fine model.
\n\t\t
\n\t\t
\n\t\t\t
6. Conclusion
\n\t\t\t
The method presented in this chapter is able to efficiently simulate discontinuous changes in the model definitions for articulated multi-flexible-body systems. The impulse-momentum equations govern the dynamics of the transitions when the number of deformable modes changes and the joints in the system are locked or released. The method is implemented in a divide-and-conquer scheme which provides linear and logarithmic complexity when implemented in serial and parallel, respectively. Moreover, the transition from a coarse-scale to a fine-scale model is treated as an optimization problem to arrive at a finite number of solutions or even a unique one. The divide-and-conquer algorithm is able to efficiently produce equations to express the generalized speeds of the system after the transition to the finer models in terms of the newly added generalized speeds. This allows the reduction in computational expenses associated with forming and solving the optimization problem.
\n\t\t
\n\t\t
\n\t\t\t
Acknowledgment
\n\t\t\t
Support for this work received under National Science Foundation through award No. 0757936 is gratefully acknowledged.
\n\t\t
\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/37790.pdf",chapterXML:"https://mts.intechopen.com/source/xml/37790.xml",downloadPdfUrl:"/chapter/pdf-download/37790",previewPdfUrl:"/chapter/pdf-preview/37790",totalDownloads:1463,totalViews:110,totalCrossrefCites:1,totalDimensionsCites:2,totalAltmetricsMentions:0,introChapter:null,impactScore:1,impactScorePercentile:69,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"November 11th 2011",dateReviewed:"May 15th 2012",datePrePublished:null,datePublished:"July 11th 2012",dateFinished:"July 11th 2012",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/37790",risUrl:"/chapter/ris/37790",book:{id:"2738",slug:"linear-algebra-theorems-and-applications"},signatures:"Mohammad Poursina, Imad M. Khan and Kurt S. Anderson",authors:[{id:"140281",title:"Dr.",name:"Mohammad",middleName:null,surname:"Poursina",fullName:"Mohammad Poursina",slug:"mohammad-poursina",email:"poursm2@rpi.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Rensselaer Polytechnic Institute",institutionURL:null,country:{name:"United States of America"}}},{id:"144415",title:"Ph.D. Student",name:"Imad",middleName:"M",surname:"Khan",fullName:"Imad Khan",slug:"imad-khan",email:"khani2@rpi.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Rensselaer Polytechnic Institute",institutionURL:null,country:{name:"United States of America"}}},{id:"144416",title:"Prof.",name:"Kurt",middleName:null,surname:"Anderson",fullName:"Kurt Anderson",slug:"kurt-anderson",email:"anderk5@rpi.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Rensselaer Polytechnic Institute",institutionURL:null,country:{name:"United States of America"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Theoretical background",level:"1"},{id:"sec_2_2",title:"2.1. Basic divide-and-conquer algorithm",level:"2"},{id:"sec_3_2",title:"2.2. Analytical preliminaries",level:"2"},{id:"sec_5",title:"3. Optimization problem",level:"1"},{id:"sec_6",title:"4. DCA-based momenta balance for multi-flexible bodies",level:"1"},{id:"sec_6_2",title:"4.1. Two-handle impulse-momentum equations in coarse to fine transitions",level:"2"},{id:"sec_7_2",title:"4.2. Assembly process and releasing the joint between two consecutive bodies",level:"2"},{id:"sec_9",title:"5. Hierarchic assembly-disassembly",level:"1"},{id:"sec_10",title:"6. Conclusion",level:"1"},{id:"sec_11",title:"Acknowledgment",level:"1"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\tAnderson, K.�S. & Poursina, M. (2009a).\nEnergy concern in biomolecular simulations with transition from a\ncoarse to a fine model, Proceedings of the Seventh International\nConference on Multibody Systems, Nonlinear Dynamics and Control, ASME Design\nEngineering Technical Conference, number IDETC2009 in MSND-87297, San\nDiego, CA.\n\t\t\t'},{id:"B2",body:'\n\t\t\t\tAnderson, K.�S. & Poursina, M. (2009b).\nOptimization problem in biomolecular simulations with DCA-based\nmodeling of transition from a coarse to a fine fidelity, Proceedings of\nthe Seventh International Conference on Multibody Systems, Nonlinear Dynamics\nand Control, ASME Design Engineering Technical Conference 2009, (IDETC09),\nnumber IDETC2009/MSND-87319, San Diego, CA.\n\t\t\t'},{id:"B3",body:'\n\t\t\t\tDemel, J.�W. (1997).\nApplied Numerical Linear Algebra, SIAM, Philadelphia, PA.\n\t\t\t'},{id:"B4",body:'\n\t\t\t\tDill, K.�A., Ozkan, S.�B., Shell, M.�S. & Weikl, T.�R.\n(2008).\nThe protein folding problem, Annual Review of Biophysics\n37(1):�289�316.\n\t\t\t'},{id:"B5",body:'\n\t\t\t\tFeatherstone, R. (1999).\nA divide-and-conquer articulated body algorithm for parallel\n calculation of rigid body dynamics. Part 1: Basic\nalgorithm, International Journal of Robotics Research 18(9):�867�875.\n\t\t\t'},{id:"B6",body:'\n\t\t\t\tKane, T.�R. & Levinson, D.�A. (1985).\nDynamics: Theory and Application, Mcgraw-Hill, NY.\n\t\t\t'},{id:"B7",body:'\n\t\t\t\tKhan, I., Poursina, M. & Anderson, K.�S. (2011).\nDCA-based optimization in transitioning to finer models in\narticulated multi-flexible-body modeling of biopolymers, Proceedings of\nthe ECCOMAS Thematic Conference - Multibody Systems Dynamics, Brussels,\nBelgium.\n\t\t\t'},{id:"B8",body:'\n\t\t\t\tMukherjee, R. & Anderson, K.�S. (2007a).\nA logarithmic complexity divide-and-conquer algorithm for\nmulti-flexible articulated body systems, Computational and Nonlinear\nDynamics 2(1):�10�21.\n\t\t\t'},{id:"B9",body:'\n\t\t\t\tMukherjee, R. & Anderson, K.�S. (2007b).\nAn orthogonal complement based divide-and-conquer algorithm for\nconstrained multibody systems, Nonlinear Dynamics 48(1-2):�199�215.\n\t\t\t'},{id:"B10",body:'\n\t\t\t\tMukherjee, R., Crozierb, P.�S., Plimptonb, S.�J. & Anderson, K.�S.\n(2008).\nSubstructured molecular dynamics using multibody dynamics algorithms,\nInternational Journal of Non-Linear Mechanics 43:�1040�1055.\n\t\t\t'},{id:"B11",body:'\n\t\t\t\tMukherjee, R.�M. & Anderson, K.�S. (2007c).\nEfficient methodology for multibody simulations with discontinuous\nchanges in system definition, Multibody System Dynamics 18:�145�168.\n\t\t\t'},{id:"B12",body:'\n\t\t\t\tMukherjee, R.�M. & Anderson, K.�S. (2008).\nA generalized momentum method for multi-flexible body systems for\nmodel resolution change, Proceedings of the 12th conference on nonlinear\nvibrations, dynamics, and multibody systems, Blacksburg, VA.\n\t\t\t'},{id:"B13",body:'\n\t\t\t\tNorberg, J. & Nilsson, L. (2003).\nAdvances in biomolecular simulations: methodology and recent\napplications, Quarterly Reviews of Biophysics 36(3):�257�306.\n\t\t\t'},{id:"B14",body:'\n\t\t\t\tPoursina, M. (2011).\nRobust Framework for the Adaptive Multiscale Modeling of\nBiopolymers, PhD thesis, Rensselaer Polytechnic Institute, Troy.\n\t\t\t'},{id:"B15",body:'\n\t\t\t\tPoursina, M., Bhalerao, K.�D. & Anderson, K.�S. (2009).\nEnergy concern in biomolecular simulations with discontinuous changes\nin system definition, Proceedings of the ECCOMAS Thematic Conference -\nMultibody Systems Dynamics, Warsaw, Poland.\n\t\t\t'},{id:"B16",body:'\n\t\t\t\tPoursina, M., Bhalerao, K.�D., Flores, S., Anderson, K.�S. & Laederach, A. (2011).\nStrategies for articulated multibody-based adaptive coarse grain\nsimulation of RNA, Methods in Enzymology 487:�73�98.\n\t\t\t'},{id:"B17",body:'\n\t\t\t\tPoursina, M., Khan, I. & Anderson, K.�S. (2011).\nModel transitions and optimization problem in multi-flexible-body\nmodeling of biopolymers, Proceedings of the Eighths International\nConference on Multibody Systems, Nonlinear Dynam. and Control, ASME Design\nEngineering Technical Conference 2011, (IDETC11), number DETC2011-48383,\nWashington, DC.\n\t\t\t'},{id:"B18",body:'\n\t\t\t\tPraprotnik, M., Site, L. & Kremer, K. (2005).\nAdaptive resolution molecular-dynamics simulation: Changing the\ndegrees of freedom on the fly, J. Chem. Phys. 123(22):�224106�224114.\n\t\t\t'},{id:"B19",body:'\n\t\t\t\tScheraga, H.�A., Khalili, M. & Liwo, A. (2007).\nProtein-folding dynamics: Overview of molecular simulation\ntechniques, Annu. Rev. Phys. Chem. 58(1):�57�83.\n\t\t\t'},{id:"B20",body:'\n\t\t\t\tShahbazi, Z., Ilies, H. & Kazerounian, K. (2010).\nHydrogen bonds and kinematic mobility of protein molecules, Journal of Mechanisms and Robotics 2(2):�021009�9.\n\t\t\t'},{id:"B21",body:'\n\t\t\t\tTurner, J.�D., Weiner, P., Robson, B., Venugopal, R., III, H.�S. & Singh, R. (1995).\nReduced variable molecular dynamics, Journal of Computational\nchemistry 16:�1271�1290.\n\t\t\t'},{id:"B22",body:'\n\t\t\t\tVoltz, K., Trylska, J., Tozzini, V., Kurkal-Siebert, V., Langowski, J.\n& Smith, J. (2008).\nCoarse-grained force field for the nucleosome from self-consistent\nmultiscaling, Journal of Computational chemistry 29(9):�1429�1439.\n\t\t\t'},{id:"B23",body:'\n\t\t\t\tWu, X.�W. & Sung, S.�S. (1998).\nConstraint dynamics algorithm for simulation of semiflexible\nmacromolecules, Journal of Computational chemistry 19(14):�1555�1566.\n\t\t\t'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Mohammad Poursina",address:null,affiliation:'
Department of Mechanical, Aeronautics, and Nuclear Engineering, Rensselaer Polytechnic Institute, USA
'},{corresp:null,contributorFullName:"Imad M. Khan",address:null,affiliation:'
Department of Mechanical, Aeronautics, and Nuclear Engineering, Rensselaer Polytechnic Institute, USA
'},{corresp:null,contributorFullName:"Kurt S. Anderson",address:null,affiliation:'
Department of Mechanical, Aeronautics, and Nuclear Engineering, Rensselaer Polytechnic Institute, USA
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1. Introduction
This chapter deals with maintenance management in organisations. He submits a literary search in connection with the current situation. Based on the implementation of the probe in several companies, it tries to design effective approaches to planning and managing the maintenance process in the context of a process approach and an integrated management system.
2. Historical review
From the very beginning, when a man made the first product, one began to think about how to prolong its life or restore or improve its function. Various technological procedures have been developed. With the transition from manual to mechanical production, this approach has gained more importance and regularity, as well as technical sophistication. Sophisticated mechanical components and then electronic components have made the equipment a more productive, but on the other hand more complex and vulnerable. From this reason, the probability of his failure increased. That status had to be stopped. It went from maintenance to failure to preventive maintenance. Gradual digitisation has resulted in greater diagnostic development and the birth of predictive maintenance. Now, the maintenance is in the stage of integration with the production into one unit. However, the conditions of the significant environment of organisations and the internal context of their maintenance are also changing. Maintenance management must respect the process approach and its aspects. However, most organisations suffer from inertia. Therefore, this development is yet to come, and organisations face a number of difficulties.
3. Publications and the maintenance management
Equipment outages, human errors and product quality deviations are always a signal for organisations to correct maintenance. They lead to efforts to mitigate the impact on production problems as the article [1] mentioned. Many publications therefore deal with partial and general studies in the scope of this topic maintenance management. For preliminary maintenance planning algorithms for steel companies, the text [2] describes generally the study [3]. A study of tools to support maintenance decisions in discrete production is in the study [4]. It brings the issue of processing a group of tasks in parallel on multiple equipment, as in the article [5]. The preventive maintenance planning model for serial parallel systems is described in the publication [6].
Principles of maintenance are examined with respect to time and cost in the article [7]. The creation of a decision-making system for the maintenance of the spatial arrangement of equipment for the city’s road infrastructure is described in the publication [8]. Papers [8, 9] examine the assessment of the level of maturity of a heavy equipment maintenance management system. The solution of barriers and their relations in industrial production are solved in the text [10]. An empirical study of the relationship between maintenance management and employee performance is described in the article [11]. The article [12] devotes to muscle and skeletal disorders in maintenance employees in connection with the risk assessment of these activities. Critical analysis of models that combine maintenance, lean manufacturing and the Industry 4.0, and design of its own for predictive maintenance is mentioned in the article [13]. Multi-target optimisation algorithm for wind turbine maintenance is used in the publication [14]. The explanation in computer-aided maintenance management when considering aspects of the Industry 4.0, such as neural network, models, clouds, the Internet of Things, the article [15] provides. The study [16] assesses and categorises maintenance services across their life cycle and in relation to the Industry 4.0.
Current trends in the production management and the maintenance management are described in texts such as [17, 18, 19, 20, 21, 22].
4. Methods
Various management tools are used in the performed studies to streamline maintenance work. The basis is the cooperation of maintenance department with production department in the organisation according to the text [19]. It should be noted that maintenance planning should overlap with production planning, as it is noted in the text [21].
Due to conditions of the substantial surroundings, work with resources and hybrid work [22] are balanced for the predictive maintenance. Emphasis is placed on the installation of sensors [20]. Preliminary maintenance planning can be based on the Genetic algorithm with two-phase optimisation, where the integration of the organisation’s strengths in the article [2] takes place. The planning of each cell system in the text [6] is based on the same algorithm and combination of the maintenance after failure and the preventive maintenance in the article [14].
Various characters of the maintenance process are monitored in organisations, such as: MTTR (Mean Time to Repair), MTBF (Mean Time Between Failures) and OEE (Overall Equipment Effectiveness) to solve outage problems [19, 23]. The small OEE is at 55–70% in the article [21]. The determination of the maintenance policy is based primarily on the characters of the number of failures, the number of operating cycles of the equipment and the time of performing the part replacement according to the text [7]. Based on a search of publications and analysis, models are created, including together maintenance, lean production and the Industry 4.0 in the article [13]. Reducing maintenance costs while increasing production performance and assessing several scenarios in the maintenance is described in the publication [14]. An important source of knowledge is also a critical analysis of computer-aided maintenance management systems as in the text [15]. The non-technical sphere brings the interconnection of sustainable, social and economic requirements for technical systems as in the text [16]. Multi-criteria analysis is also used for the maintenance decision-making system. All stakeholders are involved, which strengthens the solution of the problem, which is pointed in the article [8]. The production process depends on production speed, the number of nonconformities, system availability and other performance characters, such as complex KPI metrics. The context of the information can be determined via the semantic profile of a part of the system as in publications [1, 18]. The Pareto analysis of maintenance barriers in the organisation’s production system is mentioned in the text [10].
The evaluation of equipment criticality is performed through setting priorities and decisions on maintenance with the help of data from computer systems as MES (Manufacturing Execution System) and CMMS (Computerised Maintenance Management System). It is based on cooperation between maintenance and production to increase productivity without increasing investment as in the article [4]. Critical activities are also assessed according to the standard ISO/TR 12295 [12, 24].
To strengthen production performance and to monitor the status of maintenance, meetings and verification of the comprehensibility of tasks by staff in the text [11] are recommended. The health risks of maintenance employees are determined by using an ergonomics study in the publication [12].
The benchmarking in maintenance is promoted as a comparative method. It provides information on the number of unplanned outages and the condition of the equipment. In accordance with the article [23], an audit can be recommended as a tool for measuring the performance of the maintenance process in organisations. Furthermore, it is possible to compare maintenance process through an inventory, where the physical assets and information about them correspond to the data in the computer system as for example CMMS according to the text [18].
Furthermore, methods of evolutionary algorithms, clustering method [25] and/or linear programming [5] are used to plan and schedule maintenance and reduce its costs. Using a digital twin improves the visibility of problems in this process well in the article [17].
CBM methodology is widely used for dynamic maintenance planning, as stated in the publications [3], here in conjunction with the standard ISO 31000 [23, 26]. Methods such as RCM and TPM [23] are also used for a maintenance planning. Reliability-focused maintenance is recommended as suitable for minimising costs when there is insufficient capacity of qualified staff. The standard ISO 55001 [19, 27] is recommended to enhance sustainability. All maintenance process scenarios over time are also considered, as in the publication [3].
The assessment of the level of maturity of the maintenance process is performed based on the standard ISO 55001 [9, 27].
5. Problems of area
The current maintenance process faces a lot of problems in organisations.
Implications of production planning for maintenance planning have not yet been satisfactorily considered. These two areas are not integrated. There is no suitable approach to rescheduling maintenance according to the current situation in the workshop in the article [2]. There is a lack of analysis of the advantages and disadvantages of various maintenance planning and control algorithms [14] and rigorous data analysis according to the text [20]. There is more interest in a production than in maintenance the text [4] notes. It is necessary to address unplanned maintenance also due to the availability of staff as in the text [25]. A major problem for many organisations is a lack of strategic maintenance planning and overall integration of the maintenance into the strategy of organisations according to the article [23]. The implementation of the Industry 4.0 in the maintenance requires a more sophisticated method of maintenance planning, backed by data and industry knowledge and risk analysis as in the article [3]. Maintenance decision algorithms are often based on discrete state variables [28]. Deviations occur in the communication of sensors, actuators and other devices that can affect production decisions. There is a need to improve the work with contexts and workflows [1]. Problems occur also in the application of predictive maintenance in organisations [17].
Many organisations have difficulty to implement the conception TPM and a spatial arrangement of equipment in a shopfloor as the article [13] describes. The eternal problem is to reduce maintenance costs and increase equipment availability for many articles as in [15, 18]. Problems can be seen in the supply chain in the text [19]. Studies often involve individual facilities or shopfloors, not the entire asset management of organisations. It is necessary to update the methodology for determining the criticality of the equipment regarding new conditions of the substantial surroundings and the consistency between bottlenecks of production and the criticality of equipment. Data for maintenance analysis are often not of excellent quality. Stakeholder requirements are not understood. A static approach is applied, and the holistic concept is not considered. The maintenance is often decided by staff who have any access to it, and even the maintenance staff themselves are not familiar with data analysis [4].
According to the article [10], a common reason for maintenance problems in organisations is a poor communication in organisations and a small interest of management. Employees do not report maintenance problems and do not make improvement suggestions for maintenance. There is a need for more training on maintenance for all employees of the organisation, as texts [18, 23] add. There is a lack of qualified staff [21]. The safety of maintenance staff must be ensured [11] because working conditions of maintenance employees are hazardous to health, as shown by studies [12, 23]. Green technologies are not synchronised with the maintenance and the maintenance is not monitored environmentally [10]. Maintenance workspaces will need to be optimised for energy consumption and a carbon footprint as the article [22] notes.
Overall, problems of maintenance are financial, organisational, environmental, social and technological, as the articles [10, 20] write. The assessment of the level of maturity of the maintenance management system needs to be assessed in relation to the maintenance costs as in the text [9]. Occasionally, there is an inefficient maintenance process, as in the publication [23]. The Benchmarking towards the best maintenance group is problematic from position of internal data, as the authors write [23, 29, 30].
6. Trends
There are a number of trends in maintenance management and in workshop maintenance. The goal of all efforts is to improve the organisation’s production performance by more than 40% with the help of preliminary maintenance planning, as stated in the text [2]. The basis is the determination of suitable characters of the maintenance process and their use in sophisticated algorithms that help rapid planning, optimisation and management of maintenance and elimination of staff conflicts in publications [2, 5]. Other factors influencing the maintenance are involved in the prediction, such as vibration [13], energy prices and spare parts wear [14]. It is necessary to establish common characters or metrics for the production process and the maintenance process [4, 16]. Applications of smart technologies such as glasses increase the speed of solving maintenance problems. It also contributed to the transition from the original equipment condition monitoring to continuous multidimensional monitoring and immediate problem solving as it is described by texts [6, 17, 28]. Analysis of the causes of nonconformities will help to subsequently improve the maintenance process [20].
Small- and medium-sized organisations and households need to be supported in the application of computer-assisted maintenance management systems as publications [4, 15] recommended. Data from CMMS are used more often for maintenance planning than from MES, although this one better describes the status quo of the equipment in relation to maintenance and system dynamics. CMMS is used to determine causes of equipment failure, which is a knowledge that production also needs. The management of large volumes of data and their use for planning and managing production and maintenance together is addressed. The task of the future will be to ensure data quality in such a comprehensive management system what the article [4] notes. The programming of the Internet of Things will have to be validated in a real fault environment as in the text [3]. It is necessary to involve expert systems in the maintenance of objects, such as a road condition assessment in the article [8]. Artificial intelligence will affect not only maintenance jobs [19], but also finding compromise solutions between production and maintenance [21].
Frameworks need to be developed for several types of spatial arrangements for maintenance and production [4]. Ergonomic procedures need to be developed, and ergonomic advice should be available to staff. Furthermore, there is a need to expand research into physically demanding jobs that go beyond chronic diseases. There is a need to strengthen the effectiveness of ergonomic assistance in the shopfloor and to create a set of the best ergonomic maintenance procedures, according to the publication [12]. According to the authors [23], approximately 20% of incidents in 2020 year occurred in company maintenance. Therefore, the trend of safety in maintenance in the text [20] is growing.
Organisations should be more committed to a maintenance and risk analysis strategy, according to publications [3, 11]. This must already be included in the design of the equipment. A man and his or her activity cannot be completely excluded from the production process due to manual work, such as maintenance interventions. But his mistake can affect strategy and downtime. Therefore, durable technical equipment and social systems are needed. MES could be a plug-in for an organisation’s production planning and management system, for example, according to the article [4]. The maintenance should be part of Advanced Planning Systems according to the text [1].
Furthermore, organisations must follow cultural changes in the substantial surroundings in maintenance, as the text [23] adds. It means creating a culture of teamwork, effective emergency planning and using of the knowledge from a computer support of the maintenance. ‘Doing more with a fewer people’, according to the article [18]. Human-centred maintenance and the strengthening of communication tools according to the text [22] will help the shopfloor.
7. Discussion
As can be seen from the list of publications above, the maintenance management is an enough broad topic.
The regulating of OEE maintenance metrics as responsibilities does not always seem appropriate for organisations. This method is not yet prescribed by law. However, organisations would need to have some maintenance characters identified and evaluated. The basic characters of maintenance should be a more realistic in the maintenance work environment, which corresponds to the findings in the text [6]. The KPI metric, as stated in the text [18], can be taken in an analogous way. Lack of information on a maintenance performance leads to an inefficient process according to the article [23].
Methods such as RCM, CBM and TPM are used in practice, but in the Czech Republic the RCM method is essential and then the organisations’ own approaches.
The maintenance policy determination procedure is described for technicians not only maintenance in the text [7]. This is a helpful solution. It is aimed at professionals, not primarily managers, as is often the case. For example, processes in the article [1] are thought to be technological, but it is necessary to link them with the system according to the process map of the organisation. In addition, planning is not a process, as stated in the text [19], but an activity. Again, this is about dealing with a hierarchical structure and a directive management as in the article [21], which is unsuitable for the maintenance.
Maintenance planning and management algorithms are refined, and the number of iterations is reduced. The period of preventive maintenance is extended, as stated in the article [14]. The algorithms used so far include procedures that perform maintenance at the expense of production time. The article [4] lists several findings that can be agreed with. This is not suitable in terms of shortening the production lead time as the author [31] wrote. Maintenance calendars are often scheduled separately. There may be no link between the maintenance plan and downtime. Production losses should also be a guide for maintenance decisions. The equipment downtime should be a part of inputs to plans and so on. The only time that is crucial for the production is the main technological time. Those interested in streamlining maintenance should focus primarily on problems and waste in the current process and eliminate them.
Teamwork requires the responsibility of all employees for maintenance in the organisation. There is a need to strengthen the image of the need for maintenance in the organisation as a tool for prevention. Qualified staff is required for the maintenance [19]. However, some organisations are not interested in potential new employees. This can subsequently have a demotivating effect on them. The need for a human-machine collaboration is mentioned, but it should have been solved in the past automation efforts. The responsibility or self-responsibility is a good thing for the maintenance process. However, employees must also have other conditions such as rights and resources, including information, which is doubly true in maintenance. All employees in the organisation must be trained in maintenance so that they not only understand its importance, but also ensure their share of maintenance in their own abilities as a part of their activities. Many organisations get into trouble due to the lack of interest of the organisation’s management and the lack of sufficient resources for their employees, as shown in the text [23]. Employees must be guided to carry out maintenance tasks effectively, but they should be given an appropriate working environment, as in the text [11]. The fact is that teamwork cannot be required if some form of a hierarchical organisational structure is applied at the same time. This form also leads to other ways of management that are associated with it. The reason the maintenance process is inefficient is the insufficient definition of the process according to its characteristics. Organisations should provide their maintenance staff with sufficient quality protective equipment, which agrees with the authors [23]. However, according to the article [12], the teamwork is also the basis for prevention in maintenance ergonomics.
Surprisingly, the availability of spare parts is not so much discussed in the publications, although the article [14] assesses the field of maintenance quite comprehensively. Maintenance inventory management needs to be based on more suppliers and more extensive forecasts given the current situation, which is in line with the text [20]. There are already mentions of waste management and building efficiency, as in the article [22]. This situation with a lack of spare parts and materials in maintenance (e.g. according to the text [19]) leads to an extension of the equipment’s operation in organisations.
From problems described above and according to nonconformities that the author of this chapter encountered, the need for overall integration within the management system is evident. The trend described in the article [19] that environmental and social responsibility issues will be involved in the performance evaluation and the organisation strategy has been deviating since February 2022, although it would be necessary. The holistic of production and maintenance is necessary to increase productivity. This will strengthen the appropriate specification of characters in the integrated management system, in accordance with the text [4]. The problem is that a profit is often required, and the equipment must run constantly. This is a traditional myth of managers. The article [3] describes the involvement of design in risk assessment and maintenance planning. But it is unique. It is associated with production. Therefore, rather than a quality-oriented culture in maintenance, as in the text [23], organisations should build a safety-oriented culture or a holistic culture in the maintenance.
For these reasons, the next text of the chapter focuses on the application of the process approach in the maintenance process and on finding suitable methods for maintenance planning and management.
8. The status quo
The dynamics of the competitive environment is growing [23]. Rapid technological development is underway [19]. Initially, maintenance organisations over the past 5 years have focused on implementing the Industry 4.0 and on the increasing efficiency. The COVID-19 crisis and the current situation, as well as other threats, change the situation of all organisations and affect maintenance as in the text [17]. Maintenance systems come under pressure in such conditions [19]. The supply chains for materials and spare parts are disrupted [20]. As a result of these crises, financial resources are being reduced not only for maintenance [21]. Due to the epidemiological situation, service actions were postponed due to a lack of shift employees and a limit on the number of people who could meet at one workplace. As a result of delayed maintenance, there was a chaining and an increase in the number of problems on the equipment. The root causes of nonconformities have not been addressed [17].
There is a growing need to learn how to work and maintain new complex equipment. Therefore, not only financial and material resources for maintenance are important, but also the staff and their commitment. They are afraid of losing their jobs. Conflicts between maintenance and production are common as in the text [23]. Hybrid work is used [22]. Maintenance employees work under time pressure, under stress. The activities are long-lasting and inconvenient, and performed with an inadequate equipment. The upper limbs and torso are endangered. Handling large loads, working at heights, occasional activities are problematic, maintaining employees age. There is an extended period of training and insufficient knowledge. The organisation of work in enterprises is difficult in the team [12].
Within the survey probe, 10 organisations were examined for the purposes of this chapter on maintenance management. There were seven small- and medium-sized organisations and three large organisations. They operate in the Czech Republic. Their fields of activities are mechanical engineering, electrical industry, automotive industry, glass industry, textile industry and services. The type of production was piece or serial. The organisational structure was full and hierarchical one. There was one group of maintenance employees in organisations. Organisations had implemented basic management systems—quality ISO 9001 [32], occupational safety ISO 45001 [33], environment ISO 14001 [34] and industry standards. They usually do not have implemented the information security management system according to the standard ISO/IEC 27001 [35].
The research interest was focused on the maintenance and its links. Following nonconformities were found out by observations, interviews with companies´staff and by data analysis: outdated equipment, poor storage of spare parts, insufficient identification of facilities, lack of staff, duplication of data, data transcription errors, lack of maintenance records, low material quality, spare parts not available on the market and different maintenance procedures are applied for the same type of work, insufficient staff qualification, work safety incidents, problematic communication, low motivation, hacker attacks and loss of know-how, insufficient training, poor quality previous maintenance work, only one supplier of spare parts and materials for the organisation, data are only collected and analysis is not performed; maintenance plans and production plans diverge. In addition, there is a poor relationship between operators and their equipment.
In terms of the frequency of these nonconformities, the most numerous are occupational safety incidents, incomplete and missing records, communication, different maintenance, and production plans, not performed analyses, reduced material quality and data transcription errors. Due to the COVID crisis, organisations are learning to cope with the lack of maintenance staff and with the size of workshops. The most risk factor in the maintenance is occupational safety incidents. The health and lives of employees are endangered. Hacking attacks are dangerous in terms of data loss, change of instructions or blocking of maintenance work and then stopping the equipment. Making records means consistency and diligence. The situation in supply chains is deteriorating. The prices of items for maintenance are rising. There are not enough of them on the market. Delivery times are too long. The quality of the items is sometimes not good. It is possible to come across fraudulent actions of suppliers.
From the point of view of waste, utilisation of maintenance staff, waiting, unnecessary work and poor-quality material inputs are evident in maintenance according to publications [36, 37].
9. Process approach
The process approach is currently the cornerstone of an organisation’s management systems. It is based on the common foundations of the TQM and ISO 9001 [32]. concepts. It is based on decentralisation, cooperation, stakeholder interest, basic documentation of a process, waste elimination, object identification, leadership, communication, value-added solution variability, measurement, comparison, and review as sources of objective evidence and for the continuous improvement of the management system. Effective forms of maintenance also use these interfaces. Some of the types of flexible organisational structure are suitable for the maintenance process. This solution ensures decentralisation, autonomy and initiative. Leadership as a form of leadership supports this. Communication is then free. This makes the whole more flexible. Suitable interpersonal conditions then create an ideal mushroom for creativity and initiative. At the same time, the independence of the individual is supported. At the same time, disinterest and frustration are declining. This also reduces the number of nonconformities in the process. Characters are more apt for such a process. Maintenance procedures can be documented more consistently. Data are collected and analysed as a source for further process development.
10. Planning and control of maintenance
In general, planning in an organisation can be divided into time, material and capacity as in the book [38]. Sometimes, financial planning is added to them. All this can also be applied to maintenance.
The planning tells staff how often to conduct inspections and at what times, for example daily, weekly, monthly. Given the machinery and other assets, the organisation has an idea of how long the maintenance work will take. Normative indicators are still insufficient. Maintenance depends on the design of the equipment and its disassembly options, on the location in the building and accessibility, on the work of previous maintenance. These factors can significantly change maintenance time. Furthermore, it is the detection of the cause of the fault that prolongs the on-going time of maintenance. Maintenance time also increases depending on the technological activities performed.
Material planning tells staff how much material is needed. For example, how many bearings of a certain type on the machine, and how many litters of oil for lubrication. Here, they play a role and are assessed: delivery conditions, availability of the purchased item on the market, its price, failure rate, consumption time, storability, required quantity for maintained objects, frequency of request for use in maintenance. The storage of spare parts and materials must comply with the required storage conditions and the stacking instructions for the item. Due to the current difficult situation of suppliers, it is possible to expect a request for an increase in maintenance stocks. The ABC method can be recommended for the analysis of input materials for maintenance. As with machines, their criticality for the organisation is evaluated here. A novelty in this area will be a greater emphasis on the recycling of materials, their environmental friendliness and the return of packaging.
Financial planning tells staff how much it will cost. These are items such as materials and spare parts, wages and levies, maintenance work, taxes, depreciation.
Capacity planning indicates how much resources are needed for maintenance work. The sources in this case are workers and equipment (machines and hand tools). Qualification and awareness play a role for employees. This category also includes assembly and disassembly procedures and own maintenance procedures, as well as legislative requirements.
There are four specific maintenance levels. They correspond with publications [29, 30].
Equipment inspections can be performed by electronic systems or the human senses of an operator. They are usually performed every day.
The production operator or maintenance employee also performs caring maintenance or service every day. It means replenishing the lubricant and other media that are needed to operate the machine and adjust the machine.
Prevention or repairs to the equipment according to the type of maintenance selected are performed by maintenance personnel over a longer period.
Overhauls of equipment or outages mean that the production process is stopped in a matter of weeks to months. The outage follows mostly preventive maintenance. It is usually necessary to perform maintenance on a larger technical unit or key equipment. This means stopping the production of the company. The shutdown must be planned at all points. All resources must be provided in advance and procedures for maintenance activities, organisational team and documentation, and SW equipment must be prepared. The safety measures of individual objects and the use of protective equipment by maintenance personnel must not be forgotten either. The following must be kept in mind. Residues of substances in equipment can cause safety incidents due to chemical and physical phenomena. During the entire outage, it is necessary to collect data that will be evaluated after the outage. The main risk of downtime is overtime. It could not be foreseen advance. The solution procedure is then determined on the spot, as well as the necessary resources are determined. An extension of the time until the device is put into operation is a consequence. This status creates production losses for the organisation and increases maintenance costs. The evaluation of the shutdown should be reflected in the maintenance documentation. It is an update of the maintenance procedure. An indispensable part of the outage at present is diagnostic devices—vibro, thermo, tribo, measurement of pressure, air leakage, microcrack diagnostics, etc.
The original maintenance planning and management algorithms were based on the business situation in the 1970s. It was a hierarchical organisational structure, directive management, extensive administration, and a complex planning system. However, due to waste, inadequate information and a long flow of data, day-to-day operational interventions had to be used to prosecute both production and maintenance. Maintenance after the failure prevailed. This approach can still be found in some organisations.
PPS (Production Planning and Control) methods are intended for operational planning and management of production. The most common methods such as MRP II, KANBAN, BOA and OPT are available. Maintenance is de facto piece to small series production. Therefore, the JIT method is not included. Although the MRP II method is comprehensive in terms of planning and management, its characteristics do not correspond to the process approach. The BOA method is based on the maximum capacity utilisation and the pressure method in terms of production flow, which is also not the best. The comparison with maintenance would therefore be close to the KANBAN and OPT methods, which are based on decentralisation and are based on the pull method. However, regarding the exclusion of time, material and resource planning, they are not sufficient. Therefore, the development of a more suitable PPS method is expected due to the process approach. Therefore, the connection with maintenance planning and management will take some time.
The planning and control management of maintenance must meet goals to improve the cost effectiveness of the maintenance process and increase equipment uptime and eliminate maintenance risks.
RCM (Reliability Centred Maintenance) is a standardised method according to the standard IEC 60300-3-11 [39], which helps implement an organisation’s preventive maintenance program. This method considers safety and reduces environmental impact. It determines the technical system, its parts and their functions. It determines the probable causes of failures of the so-called functionally principal elements. Consequences and probabilities of their failures are determined. The consequences are categorised in the decision tree. They are assigned efficient maintenance activities. The result is a maintenance program that can be constantly updated according to the operating situation.
TPM (Total Productive Maintenance) is a comprehensive philosophy of effective preventive maintenance. It is not only focused on the equipment, but also on the involvement of employees who are both production operators and carers for the equipment. Equipment innovations and improvement proposals are put into practice. Staff is trained and emphasis is placed on occupational safety. The performed maintenance must be performed well. De facto, this method comprehensively strengthens the culture of the organisation.
RBM (Risk Based Maintenance) is a method that identifies and evaluates the corresponding risks when planning the maintenance of the object. They are assigned a list of faults for which the severity is evaluated. The resulting risk is the product of three parts—human health losses, productivity losses and cost losses. Probabilistic analysis is performed using a fault tree (FTA). From here, the occurrence of faults can be determined in production [40].
FFM (Failure Finding Maintenance) is a method that aims to find hidden faults that are often associated with the security features of the equipment. Even the specification of these maintenance tasks will not prevent equipment failure. The method is based on risk analysis and safety regulations from the manufacturer for the given type of equipment. Maintenance according to this method is performed at regular intervals.
TBM (Time-Based Maintenance) is a method that includes preventive maintenance, performed at regular intervals on a specific device. The goal is to prevent the object or the entire device from failing. The intervals are either time-related or tied to another quantity (e.g. the number of km driven by the car). This method is applied to working equipment.
CBM (Condition-Based Maintenance) is a method based on the identification of physical manifestations of the equipment. No consequence is expected, but manifestations preceding this device failure are detected. It is based on the P-F curve. The point P indicates the detection of the manifestation leading to the fault. The point F indicates a loss of object functionality. The distance between points P and F is the time interval when the maintenance intervention must be performed immediately. In contrast to post-failure maintenance, this type of maintenance can help the organisation prepare for intervention in terms of material preparation, spare parts, tools and maintenance platoon. On the contrary, the method is not suitable if the failure has high variability [29, 30, 40].
The first two of the methods are the most complex and, according to the author’s surveys, the most used in organisations.
Maintenance planning and management also depends on the criticality of the object. In this sense, the objects—devices, are classified into three groups:
Key objects are essential for the main production and often complex. They are irreplaceable in technology or performance. They tend to be expensive or new. They are significant due to the depreciation period according to the country.
Common objects can be replaced technologically or numerically. They are moderately complex. Spare parts for these objects are more accessible.
Auxiliary objects are less complex. They are sometimes used for ancillary work. They are usually older.
Each device should have its own passport. This document contains all information about the equipment—production drawings, technological procedures, diagrams, material certificates, test reports, etc. Passport is also the basis on which to determine the criticality of the object and the subsequent planning and management of maintenance.
The calculation of the criticality of the object depends on the cost of failures (1).
The second option is to use analysis using point evaluation of a group of characters on the equipment. These features are then evaluated in terms of criticality of this device in a semi-quantitative manner.
For the purposes of this chapter, an analysis of strategic planning and management methods was performed according to publications [30, 31, 41, 42, 43]. It was based on the current state of the market and the situation of organisations, considering nonconformities and trends in the field of maintenance management. There are a lot of methods available in this area. However, they are de facto modifications of the following methods. The following basic methods were assessed: Porter’s Five Forces, Boston Matrix, Balanced Scorecard, Key Performance Indicators, GAP analysis, Management by Objects, MOST Analysis, PESTLE Analysis, Winterling Crisis Matrix, Technique of Scenarios, SPACE Analysis, 10 Megatrends, VRIO Analysis, Forecasting. They are often mentioned as suitable for the strategic management of organisations. However, the focus on maintenance requires a primarily technical concept rather than an economic (market) concept. Furthermore, today’s organisation needs to work with risks and security factors. The linking to production must be possible. The method must be able to capture a lot of data from various sources for subsequent analysis and decision making. It should consider all relevant stakeholders. Finally, it must be in accordance with the process approach that is the basis of such organisations from the point of view of management systems.
Some methods have been removed from the menu. They are quite theoretical for practice and their application in business practice would be quite difficult. Other methods are very economically oriented. Others are relevant to different environmental conditions than they currently exist or correspond to a functional approach.
After a thorough analysis of the above methods in terms of their application, algorithm and required data sources, the following are suitable for maintenance management in the current situation: Key Performance Indicators, GAP analysis, PESTLE Analysis, Winterling Crisis Matrix, Technique of Scenarios.
Key Performance Indicators is a performance metric of a process, department or organisation. It includes features of economic, quality, performance and IT services, which helps build the Industry 4.0, features of inventory with respect to spare parts and materials. It fulfils the SMART methodology for goal setting.
GAP analysis is a method of decision making and problem solving in a certain area. It describes the current state, the required goals, determines the difference between the state and the goals, considers nonconformities and measures, proposes, and evaluates solutions. Its safety part is especially important for maintenance. It also has market and legislative parts.
PESTLE Analysis is an analysis of the essential environment of the organisation in terms of strategy. It includes factors such as technical, social, environmental, economic, and political. It also considers nonconformities, events and risks. This method is therefore a risk analysis regarding the internal and external context of the assessed area.
Winterling Crisis Matrix is a risk analysis of the assessed area, which plots the dependence of the probability of risk on its consequences into a matrix.
Technique of Scenarios is an analytical method that devises the course and consequences of various crisis situations with a view to the development of the organisation and changes in the environment. It can also work with qualitative characters (indicators). It then also sets out the procedure for resolving the relevant contingency. This method is a more general.
The Balanced Scorecard method would be borderline for the needs of maintenance management. However, it works less with risks and security.
Smaller organisations can also use the Area Diagram method, where they select and apply the values of maintenance process characters to individual axes. They will then assess them against the target values at certain time intervals.
The widely used SWOT analysis method is more general and is primary intended for the analysis of the organisation’s risks. Evaluation frameworks are part of its modifications.
All these selected methods help guide the organisation’s maintenance and management efforts in dynamic conditions too. They work with a system of current characters and their target values. From this reason, the strategic planning is applied. These methods help to determine the ways to manage the area so that the organisation can achieve them effectively. This can be called strategic management. The organisation’s strategy in the current conditions can be determined with a view to a maximum of 2 years.
11. Characteristics of the maintenance process
Characteristics of the maintenance process is possible solved according to the book [43] and standard as EN 13460 [44], EN 13306 [45], EN 15341 [46], IEC 60300–3-11 [39] and so on.
For most organisations, the maintenance process is the basic process that supports the main production process. Its effectiveness lies in the ability with as few maintenance employees and maintenance equipment as possible to keep as many equipment as possible operational for as long as possible, so as not to reduce function or even to downtime. This is all to happen at minimal cost. The managerial myth of today is that they need to implement predictive maintenance at all costs. As can be seen from practice, for example, the RCM method directly shows that some objects have maintenance after a failure even cheaper. However, aspects such as occupational safety, environment and information security must be considered. If the consequence of the failure affects any of these areas, consistent prevention is in place. This is the case for installations such as the distribution network, water mains and nuclear power plants. Price is not the only aspect. This area shows the essence of a holistic understanding of the integration of management systems in organisations with a significant impact on the maintenance.
Inputs are staff, material and spare parts, equipment, passport of maintenance and its records, medium. Output is equipment under function. Also, there is a waste. Tool can be the Pareto analysis or the FMECA for example. Rules are standard at the end of the chapter. Characters can be for example: cost of maintenance, number of maintenance staff, average maintenance time, number of failures per month, number of safety incidents, average time between failures, delivery time. Owner can be leader of process.
12. Maintenance staff
Employees are an important item of the maintenance. These are not production employees. They must be quite qualified. Their work includes both manual and mental activities. The maintenance team must be able to perform not only mechanical and electrical work, but they must also observe order, cleanliness, degreasing and handle hazardous substances carefully. It must also be able to solve the problem of interconnection of HW (connectivity) and SW for current systems within the Industry 4.0 for proper operation without deadlocks and to ensure quality data transmission. Maintenance employees should have imagination, analytical skills, knowledge of equipment operation, foresight. Therefore, they need a special approach. They must have enough training. Due to the importance and complexity of their work, they must proceed with caution. They need not only responsibilities but also powers and sufficient resources. Their work is, in a sense, creative. Therefore, regarding management schools such as from T. Peters, the standardisation of their work is not appropriate here. It leads to stress and nonconformities. Motivation and communication are important. Timely and full information of employees help speed up maintenance activities, and prevent conflicts and security incidents. The flexible organisational structure is suitable for the maintenance. Equality between members and their mutual trust is essential. Leaders should be their leader, not superiors. A suitable structure is therefore, for example, a team. From a long-term perspective, there is also a need to balance work and personal life. In the past, maintenance employees were called to intervene even when they were out of the emergency status. This had a negative effect on their family life, involvement in associations in the region and their rest. The work pace of the maintenance employees depends on the current work practice, but also on his health condition (e.g. it may be affected by ‘the Post Covid’) and the type of temperament (e.g. choleric, or melancholic). Appropriate communication contributes to awareness, explanation of unclear issues and encouragement. Ethics, safety and reliability come the first in the maintenance.
13. The Industry 4.0 and maintenance
The Industry 4.0 brings new aspects of maintenance. Compared to the production process, this area is developing more slowly. According to the surveys in which the author participated, the possibility is to state the following. Maintenance work is facilitated by electrical permitting systems and small diagnostic probes for evaluating an object from a multi-character perspective. Maintenance staff use various code readers and data terminals. Furthermore, more self-diagnostics of the equipment is used, which will allow to carefully plan maintenance intervention. The devices are equipped with one or a set of different sensors, which are connected to a SW system for storing and analysing and evaluating data. The equipment can communicate with each other in this way due to production and maintenance. This is the Internet of Things. Auxiliary logistics for maintenance in the form of small autonomous material trucks and autonomous equipment for certain tasks, such as drone inspection of the building, is advantageous. However, this solution is an expensive for some organisations. Internet services are now primarily cloud storage. It is suitable for large volumes of data such the maintenance has. However, it is important where the storage is physically located for security reasons, such as incidents such as theft, damage or data blocking. The organisation’s knowledge would be compromised, or the production equipment could be reset or shut down.
Artificial intelligence includes self-learning systems to enhance equipment automation as well as evaluate the life of its spare parts. Businesses collect data from a variety of business areas, including maintenance. They can be marked as the big data due to their volume. However, the data are often incomplete. This in turn leads to the problem that there is nothing to make maintenance predictions. The link between equipment development and maintenance and parts recycling is just beginning to gain ground. Reverse engineering with 3D parts scans and their subsequent conversion into a model and then to 3D printing make it easy to supply some spare parts right now. It depends on the material used and other properties of the unit that the spare part made in this way is reliable for use in the equipment in terms of operation and useful properties. This in turn affects maintenance planning and speeds up its execution.
14. Conclusion
Maintenance planning and management is based on the organisation’s current equipment and its capacity, especially the staffing team. It should be noted, however, that maintenance is decided much earlier. This time is the design stage of the device. The design and manufacture of equipment must be designed to allow their subsequent maintenance. This also affects the planning and management of the maintenance process. Dismantled joints, such as welding and gluing, are disadvantageous in this respect. The production must also comply with all relevant standards. Cost savings often lead to material savings, even in areas where wear and tear occur faster due to under sizing. The choice of materials is also important, both in terms of technology and use, and in terms of recycling. Emphasis should be placed on the maintenance stage, called care—service. This applies to refilling lubricants and changing filters. For each equipment, it is necessary to determine whether maintenance is economically worthwhile. Parts should have approximately the same service life so that one component does not burden the equipment that is otherwise successful. Simply simpler construction, even in current conditions, simplifies maintenance and streamlines production. This includes the concept of maintenance as a process and helps to integrate management systems. Ergonomic and safety conditions must be considered. Staff must ensure that maintenance is documented in all activities in a uniform manner in accordance with the maintenance process guidelines. It is necessary to check the stock for the maintenance.
Greater emphasis must be placed on the soft characters of the maintenance process, which also needs to be evaluated. The whole management system is then more flexible. The maturity assessment of the maintenance management system should also be based on this. The recommended planning and management methods then contribute both to the maintenance and to the organisation.
This is a different view of maintenance. Risk management is integrated in it. Within this chapter, only methodological steps were outlined on how to link operational planning and maintenance management and how to proceed in the strategy. Research needs to continue. However, these partial findings are already working in practice. The goal is an efficient maintenance process in organisations.
Acknowledgments
This work was supported with institutional support for long term strategic development of the Ministry of Education, Youth and Sports of the Czech Republic.
\n',keywords:"maintenance, process, management system, organisation, equipment, nonconformity, planning, control, strategy, employee",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/82473.pdf",chapterXML:"https://mts.intechopen.com/source/xml/82473.xml",downloadPdfUrl:"/chapter/pdf-download/82473",previewPdfUrl:"/chapter/pdf-preview/82473",totalDownloads:11,totalViews:0,totalCrossrefCites:0,dateSubmitted:null,dateReviewed:"June 3rd 2022",datePrePublished:"July 4th 2022",datePublished:null,dateFinished:"July 1st 2022",readingETA:"0",abstract:"The chapter deals with the maintenance management. The review is based on maintenance and management trends in organisations in 2022 and on other findings. There are also historical parallels. Aspects such as maintenance planning and control and management including downtime, resources in terms as material (spare parts and added materials) and personnel are discussed. The issue is linked to other management systems such as quality control, occupational safety, and environment and information security. The methods of planning and control of equipment maintenance are presented. The application of the process approach and the concept of maintenance as a process that needs to be improved are described. The relationship to the Industry 4.0 is mentioned. Linking to risk management is included in this chapter. The chapter is based on a small survey probe in several organisations, and points out identified nonconformities of the maintenance and suggested actions. The goal is effective maintenance for needs of organisations in a current dynamic environment.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/82473",risUrl:"/chapter/ris/82473",signatures:"Věra Pelantová",book:{id:"11528",type:"book",title:"Maintenance Management - Current Challenges, New Developments, and Future Directions",subtitle:null,fullTitle:"Maintenance Management - Current Challenges, New Developments, and Future Directions",slug:null,publishedDate:null,bookSignature:"Prof. Germano Lambert-Torres, Dr. Erik Leandro Bonaldi and Dr. Levy Ely Oliveira",coverURL:"https://cdn.intechopen.com/books/images_new/11528.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80356-480-7",printIsbn:"978-1-80356-479-1",pdfIsbn:"978-1-80356-481-4",isAvailableForWebshopOrdering:!0,editors:[{id:"112971",title:"Prof.",name:"Germano",middleName:null,surname:"Lambert-Torres",slug:"germano-lambert-torres",fullName:"Germano Lambert-Torres"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Historical review",level:"1"},{id:"sec_3",title:"3. Publications and the maintenance management",level:"1"},{id:"sec_4",title:"4. Methods",level:"1"},{id:"sec_5",title:"5. Problems of area",level:"1"},{id:"sec_6",title:"6. Trends",level:"1"},{id:"sec_7",title:"7. Discussion",level:"1"},{id:"sec_8",title:"8. The status quo",level:"1"},{id:"sec_9",title:"9. Process approach",level:"1"},{id:"sec_10",title:"10. Planning and control of maintenance",level:"1"},{id:"sec_11",title:"11. Characteristics of the maintenance process",level:"1"},{id:"sec_12",title:"12. Maintenance staff",level:"1"},{id:"sec_13",title:"13. The Industry 4.0 and maintenance",level:"1"},{id:"sec_14",title:"14. Conclusion",level:"1"},{id:"sec_15",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Koch S et al. Tackling problems on maintenance and evolution in industry 4.0 scenarios using a distributed architecture. 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ČESKÁ SPOLEČNOST PRO JAKOST, Praha, The Czech Republic; 2004'},{id:"B30",body:'Legát V et al. Management a inženýrství údržby. Příbram: Professional Publishing; 2016'},{id:"B31",body:'Lubina J. The Industry Engineering. Liberec: Technical university of Liberec; 2000'},{id:"B32",body:'Standard ISO 9001 Quality management systems – Requirements'},{id:"B33",body:'Standard ISO 45001 Occupational health and safety management systems – requirements with instructions for use'},{id:"B34",body:'Standard ISO 14001 Environmental management systems – Requirements with instructions for use'},{id:"B35",body:'Standard ISO/IEC 27001 Information technology. Security techniques. Information security management systems. Requirements'},{id:"B36",body:'Pavelka, M. Naučte se vidět a odstraňovat plýtvání [online]. 2015. Available from: https://www.e-api.cz/25781n-naucte-se-videt-a-odstranovat-plytvani'},{id:"B37",body:'Svozilová A. Zlepšování podnikových procesů. Praha: Grada; 2011'},{id:"B38",body:'Synek M. Manažerská ekonomika. 5., aktualiz. a dopl. vyd. Praha: Grada; 2011'},{id:"B39",body:'Standard IEC 60300-3-11 Reliability management – Part 3-11: Instructions for use – Fault-tolerant maintenance'},{id:"B40",body:'Ben-Daya M. Introduction to Maintenance Engineering: Modelling, Optimization and Management [Online]. Hoboken, United Kingdom: John Wiley & Sons Ltd; 2016. Available from: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118926581'},{id:"B41",body:'Authors. Strategic management. In: Management Mania\'s Series of Management. Managementmania.com; Praha, The Czech Republic; 2022. Available from: https://managementmania.com/cs/strategicke-rizeni'},{id:"B42",body:'Hupjé E. 9 Types of Maintenance: How to Choose the Right Maintenance Strategy. R2 Relisability.com. The Netherlands: R2 Reliability Pty Ltd.; 2021. Available from: https://roadtoreliability.com/types-of-maintenance/#h-time-based-maintenance-tbm'},{id:"B43",body:'Pelantová V, Havlíček J. Integrace a systémy Managementu. Liberec: Technical University of Liberec; 2014'},{id:"B44",body:'EN 13460 Maintenance – Maintenance Documentation'},{id:"B45",body:'EN 13306 Maintenance – Maintenance Terminology'},{id:"B46",body:'EN 15341 Maintenance – Key Maintenance Performance Indicators'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Věra Pelantová",address:"vera.pelantova@tul.cz",affiliation:'
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We believe financial barriers should not prevent researchers from publishing their findings. With the need to make scientific research more publicly available and support the benefits of Open Access, more and more institutions and funders are dedicating resources to assist faculty members and researchers cover Open Access Publishing Fees (OAPFs). In addition, IntechOpen provides several further options presented below, all of which are available to researchers, and could secure the financing of your Open Access publication.
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Paying the OAPF
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Please consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
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IntechOpen Waivers in Action
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At IntechOpen, the majority of OAPFs are paid by an Author’s institution or funding agency - Institutions (73%) vs. Authors (23%).
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However, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
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Please consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
\n\n
IntechOpen Waivers in Action
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For Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
\n\n
Our mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
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While providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
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How to Apply for a Waiver
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The application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
Feel free to contact us at funders@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
\n\n
Note: All data represented above was collected by IntechOpen from 2013 to 2017.
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Dr. Summers is a systems ecologist and began his career at the EPA in 1989 and has worked in various programs and capacities. This includes leading the National Coastal Assessment in collaboration with the Office of Water which culminated in the award-winning National Coastal Condition Report series (four volumes between 2001 and 2012), and which integrates water quality, sediment quality, habitat, and biological data to assess the ecosystem condition of the United States estuaries. He was acting National Program Director for Ecology for the EPA between 2004 and 2006. He has authored approximately 150 peer-reviewed journal articles, book chapters, and reports and has received many awards for technical accomplishments from the EPA and from outside of the agency. 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He also has an honorary appointment to serve as a Collaborative Professor at Kanazawa University, Japan, from Mar 2015 to the present. \nFormerly, Dr. Rahman was a faculty member of the University of Chittagong, Bangladesh, affiliated with the Department of Chemistry (Oct 2002 to Mar 2012) and the Department of Applied Chemistry and Chemical Engineering (Mar 2012 to Sep 2015). Dr. Rahman was also adjunctly attached with Kanazawa University, Japan (Visiting Research Professor, Dec 2014 to Mar 2015; JSPS Postdoctoral Research Fellow, Apr 2012 to Mar 2014), and Tokyo Institute of Technology, Japan (TokyoTech-UNESCO Research Fellow, Oct 2004–Sep 2005). \nHe received his Ph.D. degree in Environmental Analytical Chemistry from Kanazawa University, Japan (2011). He also achieved a Diploma in Environment from the Tokyo Institute of Technology, Japan (2005). Besides, he has an M.Sc. degree in Applied Chemistry and a B.Sc. degree in Chemistry, all from the University of Chittagong, Bangladesh. \nDr. Rahman’s research interest includes the study of the fate and behavior of environmental pollutants in the biosphere; design of low energy and low burden environmental improvement (remediation) technology; implementation of sustainable waste management practices for treatment, handling, reuse, and ultimate residual disposition of solid wastes; nature and type of interactions in organic liquid mixtures for process engineering design applications.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",slug:"zinnat-ara-begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",biography:"Zinnat A. 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The research focus of Dr. Zinnat includes the effect of the relative stability of metal-chelator complexes in the environmental remediation process designs and the development of eco-friendly soil washing techniques using biodegradable chelators.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null},{id:"39",title:"Environmental Resilience and Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",isOpenForSubmission:!0,editor:{id:"137040",title:"Prof.",name:"Jose",middleName:null,surname:"Navarro-Pedreño",slug:"jose-navarro-pedreno",fullName:"Jose Navarro-Pedreño",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRAXrQAO/Profile_Picture_2022-03-09T15:50:19.jpg",biography:"Full professor at University Miguel Hernández of Elche, Spain, previously working at the University of Alicante, Autonomous University of Madrid and Polytechnic University of Valencia. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. 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Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11413,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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The scope of this topic will range from molecular, biochemical, cellular, and physiological processes in all animal species. Work pertaining to the whole organism, organ systems, individual organs and tissues, cells, and biomolecules will be included. Medical, animal, cell, and comparative physiology and allied fields such as anatomy, histology, and pathology with physiology links will be covered in this topic. Physiology research may be linked to development, aging, environment, regular and pathological processes, adaptation and evolution, exercise, or several other factors affecting, or involved with, animal physiology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/10.jpg",keywords:"Physiology, Comparative, Evolution, Biomolecules, Organ, Homeostasis, Anatomy, Pathology, Medical, Cell Division, Cell Signaling, Cell Growth, Cell Metabolism, Endocrine, Neuroscience, Cardiovascular, Development, Aging, Development"},{id:"11",title:"Cell Physiology",scope:"
\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
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Because of the close relationship between structure and function, studies in human physiology and anatomy seek to understand the mechanisms that help the human body function. The series on human physiology deals with the various mechanisms of interaction between the various organs, nerves, and cells in the human body.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/12.jpg",keywords:"Anatomy, Cells, Organs, Systems, Homeostasis, Functions"},{id:"13",title:"Plant Physiology",scope:"Plant Physiology explores fundamental processes in plants, and it includes subtopics such as plant nutrition, plant hormone, photosynthesis, respiration, and plant stress. In recent years, emerging technologies such as multi-omics, high-throughput technologies, and genome editing tools could assist plant physiologists in unraveling molecular mechanisms in specific critical pathways. The global picture of physiological processes in plants needs to be investigated continually to increase our knowledge, and the resulting technologies will benefit sustainable agriculture.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/13.jpg",keywords:"Plant Nutrition, Plant Hormone, Photosynthesis, Respiration, Plant Stress, Multi-omics, High-throughput Technology, Genome Editing"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
",annualVolume:11399,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",editor:{id:"205604",title:"Dr.",name:"Tomas",middleName:null,surname:"Jarzembowski",fullName:"Tomas Jarzembowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKriQAG/Profile_Picture_2022-06-16T11:01:31.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorTwo:{id:"484980",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Garbacz",fullName:"Katarzyna Garbacz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003St8TAQAZ/Profile_Picture_2022-07-07T09:45:16.jpg",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorThree:null,editorialBoard:[{id:"190041",title:"Dr.",name:"Jose",middleName:null,surname:"Gutierrez Fernandez",fullName:"Jose Gutierrez Fernandez",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"University of Granada",institutionURL:null,country:{name:"Spain"}}},{id:"156556",title:"Prof.",name:"Maria Teresa",middleName:null,surname:"Mascellino",fullName:"Maria Teresa Mascellino",profilePictureURL:"https://mts.intechopen.com/storage/users/156556/images/system/156556.jpg",institutionString:"Sapienza University",institution:{name:"Sapienza University of Rome",institutionURL:null,country:{name:"Italy"}}},{id:"164933",title:"Prof.",name:"Mónica Alexandra",middleName:null,surname:"Sousa Oleastro",fullName:"Mónica Alexandra Sousa Oleastro",profilePictureURL:"https://mts.intechopen.com/storage/users/164933/images/system/164933.jpeg",institutionString:"National Institute of Health Dr Ricardo Jorge",institution:{name:"National Institute of Health Dr. Ricardo Jorge",institutionURL:null,country:{name:"Portugal"}}}]},{id:"4",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",annualVolume:11400,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",institutionString:null,institution:{name:"Sichuan University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"302145",title:"Dr.",name:"Felix",middleName:null,surname:"Bongomin",fullName:"Felix Bongomin",profilePictureURL:"https://mts.intechopen.com/storage/users/302145/images/system/302145.jpg",institutionString:null,institution:{name:"Gulu University",institutionURL:null,country:{name:"Uganda"}}},{id:"45803",title:"Ph.D.",name:"Payam",middleName:null,surname:"Behzadi",fullName:"Payam Behzadi",profilePictureURL:"https://mts.intechopen.com/storage/users/45803/images/system/45803.jpg",institutionString:"Islamic Azad University, Tehran",institution:{name:"Islamic Azad University, Tehran",institutionURL:null,country:{name:"Iran"}}}]},{id:"5",title:"Parasitic Infectious Diseases",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",annualVolume:11401,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",editor:{id:"67907",title:"Dr.",name:"Amidou",middleName:null,surname:"Samie",fullName:"Amidou Samie",profilePictureURL:"https://mts.intechopen.com/storage/users/67907/images/system/67907.jpg",institutionString:null,institution:{name:"University of Venda",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188881",title:"Dr.",name:"Fernando José",middleName:null,surname:"Andrade-Narváez",fullName:"Fernando José Andrade-Narváez",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRIV7QAO/Profile_Picture_1628834308121",institutionString:null,institution:{name:"Autonomous University of Yucatán",institutionURL:null,country:{name:"Mexico"}}},{id:"269120",title:"Dr.",name:"Rajeev",middleName:"K.",surname:"Tyagi",fullName:"Rajeev Tyagi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRaBqQAK/Profile_Picture_1644331884726",institutionString:"CSIR - Institute of Microbial Technology, India",institution:null},{id:"336849",title:"Prof.",name:"Ricardo",middleName:null,surname:"Izurieta",fullName:"Ricardo Izurieta",profilePictureURL:"https://mts.intechopen.com/storage/users/293169/images/system/293169.png",institutionString:null,institution:{name:"University of South Florida",institutionURL:null,country:{name:"United States of America"}}}]},{id:"6",title:"Viral Infectious Diseases",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",annualVolume:11402,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",fullName:"Emmanuel Drouet",profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",institutionString:null,institution:{name:"Grenoble Alpes University",institutionURL:null,country:{name:"France"}}},{id:"188219",title:"Prof.",name:"Imran",middleName:null,surname:"Shahid",fullName:"Imran Shahid",profilePictureURL:"https://mts.intechopen.com/storage/users/188219/images/system/188219.jpeg",institutionString:null,institution:{name:"Umm al-Qura University",institutionURL:null,country:{name:"Saudi Arabia"}}},{id:"214235",title:"Dr.",name:"Lynn",middleName:"S.",surname:"Zijenah",fullName:"Lynn Zijenah",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSEJGQA4/Profile_Picture_1636699126852",institutionString:null,institution:{name:"University of Zimbabwe",institutionURL:null,country:{name:"Zimbabwe"}}},{id:"178641",title:"Dr.",name:"Samuel Ikwaras",middleName:null,surname:"Okware",fullName:"Samuel Ikwaras Okware",profilePictureURL:"https://mts.intechopen.com/storage/users/178641/images/system/178641.jpg",institutionString:null,institution:{name:"Uganda Christian University",institutionURL:null,country:{name:"Uganda"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/128183",hash:"",query:{},params:{id:"128183"},fullPath:"/profiles/128183",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var t;(t=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(t)}()