GA Parameters
\r\n\tThis book is intended to show the advances in cytoskeleton structure, functional dynamics, and role in cell signaling. In addition, it will include protein structure-composition of the major filament systems and major cytoplasmic components, which play important roles in cell function, and investigations into the functional role of the cytoskeleton that currently represent a major area of cell biological research.
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Jimenez-Lopez",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8414.jpg",keywords:"membrane coordinating cytoskeletal systems, endocytosis, F-actin, actin-binding proteins, cell migration, tubulins, From filaments to function, cortical cytoskeletal array",numberOfDownloads:129,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"August 7th 2018",dateEndSecondStepPublish:"August 28th 2018",dateEndThirdStepPublish:"October 27th 2018",dateEndFourthStepPublish:"January 15th 2019",dateEndFifthStepPublish:"March 16th 2019",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,editors:[{id:"33993",title:"Dr.",name:"Jose C.",middleName:null,surname:"Jimenez-Lopez",slug:"jose-c.-jimenez-lopez",fullName:"Jose C. Jimenez-Lopez",profilePictureURL:"https://mts.intechopen.com/storage/users/33993/images/system/33993.jpg",biography:"Dr. Jose C. Jimenez-Lopez finished his PhD degree in Plant Science in 2008 at the Spanish National Research Council (CSIC), which focused in the study of the actin-binding protein profilin in olive from functional and allergenic point of views. During this predoctoral period, he visited as an invited researcher different EU and US laboratories such as the Institute of Cellular and Molecular Botany (IZMB), University of Bonn, Germany (2005); the University of Vienna, Faculty of Life Sciences (2006); and the College of Sciences, Purdue University in the USA.\nSoon after, he moved to the USA to start his postdoctoral research at Purdue University, the College of Sciences, until 2011 to work in the biochemical and cellular characterization of actin-binding proteins involved in plant actin cytoskeleton dynamics and signaling throughout membrane association. \nIn 2012, he was awarded with an EU research grant from the Marie Curie program to work until 2015 in the University of Western Australia and CSIC in a project related to the human health benefits of legume seed–derived foods and molecular aspects of allergy and cross allergenicity to legume seed proteins.\nCurrently, Jose is working at the Estación Experimental del Zaidín (EEZ), Spanish National Research Council (CSIC), as a senior research fellow thanks to a grant awarded from the “Ramon y Cajal” research program (MINECO), focusing in the functionality, health benefits, and allergy implications of proteins from reproductive tissues (pollen and seeds) in crop species (mainly legumes) of agro-industrial interest.",institutionString:"Spanish National Research Council (CSIC)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"5",institution:{name:"Spanish National Research Council",institutionURL:null,country:{name:"Spain"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"47",title:"Cell Biology",slug:"biochemistry-genetics-and-molecular-biology-cell-biology"}],chapters:[{id:"65643",title:"Microscale Mechanics of Plug-and-Play In Vitro Cytoskeleton Networks",slug:"microscale-mechanics-of-plug-and-play-in-vitro-cytoskeleton-networks",totalDownloads:129,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"194666",firstName:"Nina",lastName:"Kalinic Babic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/194666/images/4750_n.jpg",email:"nina@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Buchholz and Erik J. Behringer",coverURL:"https://cdn.intechopen.com/books/images_new/7264.jpg",editedByType:"Edited by",editors:[{id:"89438",title:"Dr.",name:"John N.",surname:"Buchholz",slug:"john-n.-buchholz",fullName:"John N. Buchholz"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"834",title:"Optimal Design of Parallel Kinematics Machines with 2 Degrees of Freedom",doi:"10.5772/5436",slug:"optimal_design_of_parallel_kinematics_machines_with_2_degrees_of_freedom",body:'\n\t\tThe mechanical structure of today’s machine tools is based on serial kinematics in the overwhelming majority of cases. Parallel kinematics with closed kinematics chains offer many potential benefits for machine tools but they also cause many drawbacks in the design process and higher efforts for numerical control and calibration.
\n\t\t\tThe Parallel Kinematics Machine (PKM) is a new type of machine tool which was firstly showed at the 1994 International Manufacturing Technology in Chicago by two American machine tool companies, Giddings & Lewis and Ingersoll.
\n\t\t\tParallel Kinematics Machines seem capable of answering the increase needs of industry in terms of automation. The nature of their architecture tends to reduce absolute positioning and orienting errors (Stan et al., 2006). Their closed kinematics structure allows them obtaining high structural stiffness and performing high-speed motions. The inertia of its mobile parts is reduced, since the actuators of a parallel robot are often fixed to its base and the end-effector can perform movements with higher accelerations. One drawback with respect to open-chain manipulators, though, is a typically reduced workspace and a poor ratio of working envelope to robot size.
\n\t\t\tIn theory, parallel kinematics offer for example higher stiffness and at the same time higher acceleration performance than serial structures. In reality, these and other properties are highly dependent on the chosen structure, the chosen configuration for a structure and the position of the tool centre point (TCP) within the workspace. There is a strong and complex link between the type of robot’s geometrical parameters and its performance. It’s very difficult to choose the geometrical parameters intuitively in such a way as to optimize the performance. The configuration of parallel kinematics is more complex due to the high sensitivity to variations of design parameters. For this reason the design process is of key importance to the overall performance of a Parallel Kinematics Machines. For the optimization of Parallel Kinematics Machines an application-oriented approach is necessary.
\n\t\t\tIn this chapter an approach is presented that includes the definition of specific objective functions as well as an optimization algorithm. The presented algorithm provides the basis for an overall multiobjective optimization of several kinematics structures.
\n\t\t\tAn important objective of this chapter is also to propose an optimization method for planar Parallel Kinematics Machines that combines performance evaluation criteria related to the following robot characteristics: workspace, design space and transmission quality index. Furthermore, a genetic algorithm is proposed as the principle optimization tool. The success of this type of algorithm for parallel robots optimization has been demonstrated in various papers (Stan et al., 2006).
\n\t\t\tParallel kinematics for milling machines
For parallel kinematics machines with reduced number of degrees of freedom kinematics and singularity analyses can be solved to obtain algebraic expressions, which are well suited for an implementation in optimum design problems.
\n\t\t\tBenefits of Parallel Kinematics Machines
High dynamical performance is achieved due to the low moved masses. Due to the closed kinematics the movements of parallel kinematics machines are vibration free for which the accuracy is improved. Finally, the modular concept allows a cost-effective production of the mechanical parts.
\n\t\t\tIn this chapter, the optimization workspace index is defined as the measure to evaluate the performance of two degree of freedom Parallel Kinematics Machines. Another important contribution is the optimal dimensioning of the two degree-of-freedom Parallel Kinematics Machines of type Bipod and Biglide for the largest workspace using optimization based on Genetic Algorithms.
\n\t\tOne of the main influential factors on the performance of a machine tool with parallel kinematics is its structural configuration. The performance of a machine tool with parallel kinematics can be evaluated by its kinematic, static and dynamic properties. Optimal design is one of the most important issues in the development of a parallel machine tool. Two issues are involved in the optimal design: performance evaluation and dimensional synthesis. The latter one is one of the most difficult issues in this field. In the optimum design process, several criteria could be involved for a design purpose, such as workspace, singularity, dexterity, accuracy, stiffness, and conditioning index.
\n\t\t\tAfter its choice, the next step on the machine tool with parallel kinematics design should be to establish its dimensions. Usually this dimensioning task involves the choice of a set of parameters that define the mechanical structure of the machine tool. The parameter values should be chosen in a way to optimize some performance criteria, dependent upon the foreseen application.
\n\t\t\tThe optimization of machine tools with parallel kinematics can be based on the following objectives functions:
\n\t\t\tworkspace,
the overall size of the machine tool,
kinematic transmission of forces and velocities,
stiffness,
acceleration capabilities,
dexterity,
accuracy,
the singular configurations,
isotropy.
In the design process we want to determine the design parameters so that the parallel kinematics machine fulfills a set of constraints. These constraints may be extremely different but we can mention:
\n\t\t\tworkspace requirement,
maximum accuracy over the workspace for a given accuracy of the sensors,
maximal stiffness of the Parallel Kinematics Machines in some direction,
minimum articular forces for a given load,
maximum velocities or accelerations for given actuator velocities and accelerations.
Determination of the architecture and size of a mechanism is an important issue in the mechanism design. Several objectives are contradictory to each other. An optimization with only one objective runs into unusable solutions for all other objectives. Unfortunately, any change that improves one performance will usually deteriorate the other. This trade-off occurs with almost every design and this inevitable generates the problem of design optimization. Only a multiobjective approach will result in practical solutions for machine tool applications.
\n\t\t\tThe classical methods of design optimization, such as iterative methods, suffer from difficulties in dealing with this problem. Firstly, optimization problems can take many iterations to converge and can be sensitive to numerical problems such as truncation and round-off error in the calculation. Secondly, most optimization problems depend on initial guesses, and identification of the global minimum is not guaranteed. Therefore, the relation between the design parameters and objective function is difficult to know, thus making it hard to obtain the most optimal design parameters of the mechanism. Also, it’s rather difficult to investigate the relations between performance criteria and link lengths of all mechanisms. So, it’s important to develop a useful optimization approach that can express the relations between performance criteria and link lengths.
\n\t\t\tThe workspace of a robot is defined as the set of all end-effector configurations which can be reached by some choice of joint coordinates. As the reachable locations of an end-effector are dependent on its orientation, a complete representation of the workspace should be embedded in a 6-dimensional workspace for which there is no possible graphical illustration; only subsets of the workspace may therefore be represented.
\n\t\t\t\tThere are different types of workspaces namely constant orientation workspace, maximal workspace or reachable workspace, inclusive orientation workspace, total orientation workspace, and dextrous workspace. The constant orientation workspace is the set of locations of the moving platform that may be reached when the orientation is fixed. The maximal workspace or reachable workspace is defined as the set of locations of the end-effector that may be reached with at least one orientation of the platform. The inclusive orientation workspace is the set of locations that may be reached with at least one orientation among a set defined by ranges on the orientation parameters. The set of locations of the end-effector that may be reached with all the orientations among a set defined by ranges on the orientations on the orientation parameters constitute the total orientation workspace. The dextrous workspace is defined as the set of locations for which all orientations are possible. The dextrous workspace is a special case of the total orientation workspace, the ranges for the rotation angles (the three angles that define the orientation of the end-effector) being [0,2π].
\n\t\t\t\tIn the literature, various methods to determine workspace of a parallel robot have been proposed using geometric or numerical approaches. Early investigations of robot workspace were reported by (Gosselin, 1990), (Merlet, 1995), (Kumar & Waldron, 1981), (Tsai and Soni, 1981), (Gupta & Roth, 1982), (Sugimoto & Duffy, 1982), (Gupta, 1986), and (Davidson & Hunt, 1987). The consideration of joint limits in the study of the robot workspaces was presented by (Delmas & Bidard, 1995). Other works that have dealt with robot workspace are reported by (Agrawal, 1990), (Gosselin & Angeles, 1990), (Cecarelli, 1995). (Agrawal, 1991) determined the workspace of in-parallel manipulator system using a different concept namely, when a point is at its workspace boundary, it does not have a velocity component along the outward normal to the boundary. Configurations are determined in which the velocity of the end-effector satisfies this property. (Pernkopf & Husty, 2005) presented an algorithm to compute the reachable workspace of a spatial Stewart Gough-Platform with planar base and platform (SGPP) taking into account active and passive joint limits. Stan (Stan, 2003) presented a genetic algorithm approach for multi-criteria optimization of PKM (Parallel Kinematics Machines). Most of the numerical methods to determine workspace of parallel manipulators rest on the discretization of the pose parameters in order to determine the workspace boundary (Cleary & Arai, 1991), (Ferraresi et al., 1995). In the discretization approach, the workspace is covered by a regularly arranged grid in either Cartesian or polar form of nodes. Each node is then examined to see whether it belongs to the workspace. The accuracy of the boundary depends upon the sampling step that is used to create the grid. The computation time grows exponentially with the sampling step. Hence it puts a limit on the accuracy. Moreover, problems may occur when the workspace possesses singular configurations. Other authors proposed to determine the workspace by using optimization methods (Stan, 2003). Numerical methods for determining the workspace of the parallel robots have been developed in the recent years. Exact computation of the workspace and its boundary is of significant importance because of its impact on robot design, robot placement in an environment, and robot dexterity.
\n\t\t\t\tMasory, who used the discretisation method (Masory & Wang, 1995), presented interesting results for the Stewart-Gough type parallel manipulator:
\n\t\t\t\tThe mechanical limits on the passive joints play an important role on the volume of the workspace. For ball and socket joints with given rotation ability, the volume of the workspace is maximal if the main axes of the joints have the same directions as the links when the robot is in its nominal position.
The workspace volume is roughly proportional to the cube of the stroke of the actuators.
The workspace volume is not very sensitive to the layout of the joints on the platforms, even though it is maximal when the two platforms have the same dimension (in this case, the robot is in a singular configuration in its nominal position).
Even though powerful three-dimensional Computer Aided Design and Dynamic Analysis software packages such as Pro/ENGINEER, IDEAS, ADAMS and Working Model 3-D are now being used, they cannot provide important visual and realistic workspace information for the proposed design of a parallel robot. In addition, there is a great need for developing methodologies and techniques that will allow fast determination of workspace of a parallel robot. A general numerical evaluation of the workspace can be deduced by formulating a suitable binary representation of a cross-section in the taskspace. A cross-section can be obtained with a suitable scan of the computed reachable positions and orientations p, once the forward kinematic problem has been solved to give p as function of the kinematic input joint variables q. A binary matrix Pij can be defined in the cross-section plane for a crosssection of the workspace as follows: if the (i, j) grid pixel includes a reachable point, then Pij = 1; otherwise Pij = 0, as shown in Fig. 3. Equations (1)-(4) for determining the workspace of a robot by discretization method can be found in Ref. (Ottaviano et al., 2002).
\n\t\t\t\tThen is computed i and j:
\n\t\t\t\twhere i and j are computed as integer numbers. Therefore, the binary mapping for a workspace cross-section can be given as:
\n\t\t\t\twhere W(H) indicates workspace region; \n\t\t\t\t\t
\n\t\t\t\t\t
The general scheme for binary representation and evaluation of robot workspace
In addition, the proposed binary representation is useful for a numerical evaluation of the position workspace by computing the sections areas A as:
\n\t\t\t\tThis numerical approximation of the workspace area has been used for the optimum design purposes.
\n\t\t\tThe kinematics accuracy is a key factor for the design and application of the machine tools with parallel kinematics. But the research of the accuracy is still in initial stage because of the various structures and the nonlinear errors of the parallel kinematics machine tools.
\n\t\t\t\tTo analyze the sensitiveness of the structural error is one of the directions for the research of structural accuracy. An approach was introducing a dimensionless factor of sensitiveness for every leg of the structure. Other approach includes the use of the value of Jacobian matrix as sensitivity index for the whole legs or the use of condition number of Jacobian matrix as a quantity index to describe the error sensitivity of the whole system.
\n\t\t\tStiffness describes the ratio “deformation displacement to deformation force” (static stiffness). In case of dynamic loads this ratio (dynamic stiffness) depends on the exciting frequencies and comes to its most unfavorable (smallest) value at resonance (Hesselbach et al., 2003). In structural mechanics deformation displacement and deformation force are represented by vectors and the stiffness is expressed by the stiffness matrix\n\t\t\t\t\tK.
\n\t\t\tBecause singularity leads to a loss of the controllability and degradation of the natural stiffness of manipulators, the analysis of Parallel Kinematics Machines has drawn considerable attention. This property has attracted the attention of several researchers because it represents a crucial issue in the context of analysis and design. Most Parallel Kinematics Machines suffer from the presence of singular configurations in their workspace that limit the machine performances. The singular configurations (also called singularities) of a Parallel Kinematics Machine may appear inside the workspace or at its boundaries. There are two main types of singularities (Gosselin & Angeles, 1990). A configuration where a finite tool velocity requires infinite joint rates is called a serial singularity or a type 1 singularity. A configuration where the tool cannot resist any effort and in turn, becomes uncontrollable is called a parallel singularity or type 2 singularity. Parallel singularities are particularly undesirable because they cause the following problems:
\n\t\t\t\ta high increase of forces in joints and links, that may damage the structure,
a decrease of the mechanism stiffness that can lead to uncontrolled motions of the tool though actuated joints are locked.
Thus, kinematics singularities have been considered for the formulated optimum design of the Parallel Kinematics Machines.
\n\t\t\tDexterity has been considered important because it is a measure of a manipulator’s ability to arbitrarily change its position and orientation or to apply forces and torques in arbitrary direction. Many researchers have performed design optimization focusing on the dexterity of parallel kinematics by minimization of the condition number of the Jacobian matrix. In regards to the PKM’s dexterity, the condition number ρ, given by ρ=σmax/σmin where σmax and σmin are the largest and smallest singular values of the Jacobian matrix J.
\n\t\t\tThe determinant of the Jacobian matrix J, det(J), is proportional to the volume of the hyper ellipsoid. The condition number represents the sphericity of the hyper ellipsoid. The manipulability measure w, given by \n\t\t\t\t\t
A planar Parallel Kinematics Machines is formed when two or more planar kinematic chains act together on a common rigid platform. The most common planar parallel architecture is composed of two RPR chains (Fig. 4), where the notation RPR denotes the planar chain made up of a revolute joint, a prismatic joint, and a second revolute joint in series. Another common architecture is PRRRP (Fig. 5). Two general planar Parallel Kinematics Machines with two degrees of freedom activated by prismatic joints are shown in Fig. 4 and Fig. 5.
\n\t\t\t\tThere are a wide range of parallel robots that have been developed but they can be divided into two main groups:
\n\t\t\t\tType 1) Parallel Kinematics Machine with variable length struts,
Type 2) Parallel Kinematics Machine with constant length struts.
Since mobility of these Parallel Kinematics Machines is two, two actuators are required to control these Parallel Kinematics Machines. For simplicity, the origin of the fixed base frame {B} is located at base joint A with its x-axis towards base joint B, and the origin of the moving frame {M} is located in TCP, as shown in Fig. 7. The distance between two base joints is b. The position of the moving frame {M} in the base frame {B} is x=(xP, yP)T and the actuated joint variables are represented by q=(q1, q2)T.
\n\t\t\t\tVariable length struts Parallel Kinematics Machine
Constant length struts Parallel Kinematics Machine
PKM kinematics deal with the study of the PKM motion as constrained by the geometry of the links. Typically, the study of the PKMs kinematics is divided into two parts, inverse kinematics and forward (or direct) kinematics. The inverse kinematics problem involves a known pose (position and orientation) of the output platform of the PKM to a set of input joint variables that will achieve that pose. The forward kinematics problem involves the mapping from a known set of input joint variables to a pose of the moving platform that results from those given inputs. However, the inverse and forward kinematics problems of our PKMs can be described in closed form.
\n\t\t\t\tThe general kinematic scheme of a PRRRP Parallel Kinematics Machine
The general kinematic scheme of a RPRPR Parallel Kinematics Machine
The kinematics relation between x and q of these 2 DOF Parallel Kinematics Machines can be expressed solving the following equation:
\n\t\t\t\tThen the inverse kinematics problem of the PKM from Fig. 6 can be solved by writing the following equations:
\n\t\t\t\tThen the inverse kinematics problem of the PKM from Fig. 7 can be solved by writing the following equations:
\n\t\t\t\tThe TCP position can be calculated by using inverted transformation, from (6), thus the direct kinematics of the PKM can be described as:
\n\t\t\t\twhere the values of the x\n\t\t\t\t\tp, y\n\t\t\t\t\tP can be easily determined.
\n\t\t\t\tThe forward and the inverse kinematics problems were solved under the MATLAB environment and it contains a user friendly graphical interface. The user can visualize the different solutions and the different geometric parameters of the PKM can be modified to investigate their effect on the kinematics of the PKM. This graphical user interface can be a valuable and effective tool for the workspace analysis and the kinematics of the PKM. The designer can enhance the performance of his design using the results given by the presented graphical user interface.
\n\t\t\t\tThe Matlab-based program is written to compute the forward and inverse kinematics of the PKM with 2 degrees of freedom. It consists of several MATLAB scripts and functions used for workspace analysis and kinematics of the PKM. A friendly user interface was developed using the MATLAB-GUI (graphical user interface). Several dialog boxes guide the user through the complete process.
\n\t\t\t\tGraphical User Interface (GUI) for solving inverse kinematics of the 2 DOF planar Parallel Kinematics Machine of type Bipod in MATLAB environment.
The user can modify the geometry of the 2 DOF PKM. The program visualizes the corresponding kinematics results with the new inputs.
\n\t\t\t\tParallel Kinematics Machine configuration for XP=25 mm YP=60 mm
Parallel Kinematics Machine configuration for XP=35 mm YP=60 mm
The workspace is one of the most important kinematics properties of manipulators, even by practical viewpoint because of its impact on manipulator design and location in a workcell (Ceccarelli et al., 2005). Workspace is a significant design criterion for describing the kinematics performance of parallel robots. The planar parallel robots use area to evaluate the workspace ability. However, is hard to find a general approach for identification of the workspace boundaries of the parallel robots. This is due to the fact that there is not a closed form solution for the direct kinematics of these parallel robots. That’s why instead of developing a complex algorithm for identification of the boundaries of the workspace, it’s developed a general visualization method of the workspace for its analysis and its design.
\n\t\t\t\tA general numerical evaluation of the workspace can be deduced by formulating a suitable binary representation of a cross-section in the taskspace. Other authors proposed to determine the workspace by using optimization (Stan, 2003). A fundamental characteristic that must be taken into account in the dimensional design of robot manipulators is the area of their workspace. It is crucial to calculate the workspace and its boundaries with perfect precision, because they influence the dimensional design, the manipulator’s positioning in the work environment, and its dexterity to execute tasks. Because of this, applications involving these Parallel Kinematics Machines require a detailed analysis and visualization of the workspace of these PKMs. The algorithm for visualization of workspace needs to be adaptable in nature, to configure with different dimensions of the parallel robot’s links. The workspace is discretized into square and equal area sectors. A multi-task search is performed to determine the exact workspace boundary. Any singular configuration inside the workspace is found along with its position and dimensions. The area of the workspace is also computed.
\n\t\t\t\tThe workspace is the area in the plane case where the tool centre point (TCP) can be controlled and moved continuously and unobstructed. The workspace is limited by singularities. At singularity poses it is not possible to establish definite relations between input and output coordinates. Such poses must be avoided by the control.
\n\t\t\t\tThe robotics literature contains various indices of performance (Du Plessis & Snyman, 2001) (Schoenherr & Bemessen, 1998), such as the workspace index W and the general equation is given in (8). Workspace for this kind of robot may be easily generated by intersection of the enveloping surfaces and the area can be also computed.
\n\t\t\t\tThe workspace of the 2 DOF planar PKM of type Bipod is often represented as a region of the plane, which can be obtained by the reacheable points of the TCP.
\n\t\t\t\tThe workspace is the intersection of two enveloping surface of two legs.
The following presents the main factors affecting workspace. For ease of comparison a cubic working envelope with a common contour length is used together with a machine size that is calculated from the maximum required strut length. Other design specific factors such as the end-effector size, drive volumes have been neglected for simplification.
\n\t\t\t\tThe working envelope to machine size using variable length struts is dependent on the following factors:
\n\t\t\t\tThe length of the extended and retracted actuator (Lmin, Lmax);
Limitations due to the joint angle range.
The limiting effect of the joint limits is clearly illustrated in Fig. 12-13.
\n\t\t\t\tWorkspace of the Parallel Kinematics Machine with variable length struts
Workspace of the Parallel Kinematics Machine with constant length struts
In this section, the workspace of the proposed Parallel Kinematics Machines will be discussed systematically. It’s very important to analyze the area and the shape of workspace for parameters given robot in the context of industrial application. The workspace is primarily limited by the boundary of solvability of inverse kinematics. Then the workspace is limited by the reachable extent of drives and joints, occurrence of singularities and by the link and platform collisions. The PKM mechanisms PRRRP and RPRPR realize a wide workspace as well as high-speed. Analysis, visualization of workspace is an important aspect of performance analysis. A numerical algorithm to generate reachable workspace of parallel manipulators is introduced.
\n\t\t\t\tThe GUI for calculus of workspace for the planar 2 DOF Parallel Kinematics Machine with variable length struts
The GUI for calculus of workspace for the planar 2 DOF Parallel Kinematics Machine with constant length struts
In the followings is presented the workspace analysis of 2 DOF Bipod PKM.
Case I:Conditions:
\n\t\t\t\t\n\t\t\t\t\ta) for y>0\n\t\t\t\t
\n\t\t\t\tThe workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
b) for\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:
\n\t\t\t\ta) for y>0
\n\t\t\t\tThe workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
b) for\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
The workspace of the planar 2 DOF Parallel Kinematics Machine is shown as the shading region.
Conditions:\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
Different regions of workspace for Biglide PKM for different lengths of stroke of actuators
Because singularity leads to a loss of the controllability and degradation of the natural stiffness of manipulators, the analysis of parallel manipulators has drawn considerable attention. Most parallel robots suffer from the presence of singular configurations in their workspace that limit the machine performances. Based on the forward and inverse Jacobian matrix, three cases of singularities of parallel manipulators can be obtained. Singular configurations should be avoided.
\n\t\t\t\tIn the followings are presented the singular configurations of 2 DOF Biglide Parallel Kinematic Machine.
\n\t\t\t\tSingular configuration for the planar 2 DOF Biglide Parallel Kinematic Machine
Singular configuration for the planar 2 DOF Biglide Parallel Kinematic Machine
Singular configuration for the planar 2 DOF Biglide Parallel Kinematic Machine
Beside workspace which is an important design criterion, transmission quality index is another important criterion. The transmission quality index couples velocity and force transmission properties of a parallel robot, i.e. power features (Hesselbach et al., 2004). Its definition runs:
\n\t\t\t\twhere I is the unity matrix. T is between 0<T<1; T=0 characterizes a singular pose, the optimal value is T=1 which at the same time stands for isotropy (Stan, 2003).
\n\t\t\t\tTransmission quality index for RPRPR Bipod Parallel Kinematic Machine
Transmission quality index for PRRRP Biglide Parallel Kinematic Machine
As it can be seen from the Fig. 30, the performances of the PRRRP Biglide Parallel Kinematic Machine are constant along y-axis. On every y section of such workspace, the performance of the robot can be the same.
\n\t\t\tThe design of the PKM can be made based on any particular criterion. The chapter presents a genetic algorithm approach for workspace optimization of Bipod Parallel Kinematic Machine. For simplicity of the optimization calculus a symmetric design of the structure was chosen.
\n\t\t\t\tIn order to choose the PKM’s dimensions b, q1min, q1max, q2min, q2max, we need to define a performance index to be maximized. The chosen performance index is W (workspace) and T (transmission quality index).
\n\t\t\t\tAn objective function is defined and used in optimization. It is noted as in Eq. (8), and corresponds to the optimal workspace and transmission quality index. We can formalize our design optimization problem as the following:
\n\t\t\t\tOptimization problem is formulated as follows: the objective is to evaluate optimal link lengths which maximize Eq. (10). The design variables or the optimization factor is the ratios of the minimum link lengths to the base link length b, and they are defined by:
\n\t\t\t\tConstraints to the design variables are:
\n\t\t\t\tFlowchart of the optimization Algorithm with GAOT (Genetic Algorithm Optimization Toolbox)
For this example the lower limit of the constraint was chosen to fulfill the condition q1min≥b/2 that means the minimum stroke of the actuators to have a value greater than the half of the distance between them in order to have a workspace only in the upper region. For simplicity of the optimization calculus the upper bound was chosen q1min≤1,35b.
\n\t\t\t\tDuring optimization process using genetic algorithm it was used the following GA parameters, presented in Table 1.
\n\t\t\t\tGenerations | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t
Crossover rate | \n\t\t\t\t\t\t\t0.08 | \n\t\t\t\t\t\t
Mutation rate | \n\t\t\t\t\t\t\t0.005 | \n\t\t\t\t\t\t
Population | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t
GA Parameters
Researchers have used genetic algorithms, based on the evolutionary principle of natural chromosomes, in attempting to optimize the design parallel kinematics. Kirchner and Neugebaur (Kirchner & Neugebaur, 2000), emphasize that a parallel manipulator machine tool cannot be optimized by considering a single performance criterion. Also, using a genetic algorithm, they consider a multiple design criteria, such as the “velocity relationship” between the moving platform and the actuator legs, the influence of actuator leg errors on the accuracy of the moving platform, actuator forces, stiffness, as well as a singularity-free workspace.
\n\t\t\t\tA genetic algorithm (GA) is used because its robustness and good convergence properties. The genetic algorithms optimization approach has the clear advantage over conventional optimization approaches in that it allows a number of solutions to be examined in a single design cycle.
\n\t\t\t\tThe traditional methods searches optimal points from point to point, and are easy to fall into local optimal point. Using a population size of 50, the GA was run for 100 generations. A list of the best 50 individuals was continually maintained during the execution of the GA, allowing the final selection of solution to be made from the best structures found by the GA over all generations.
\n\t\t\t\tWe performed a kinematic optimization in such a way to maximize the objective function. It is noticed that optimization result for Bipod when the maximum workspace of the 2 DOF planar PKM is obtained for \n\t\t\t\t\t
If an elitist GA is used, the best individual of the previous generation is kept and compared to the best individual of the new one. If the performance of the previous generation’s best individual is found to be superior, it is passed on to the next generation instead of the current best individual.
\n\t\t\t\tThere have been obtained different values of the parameter optimization (q1/b) for different objective functions. The following table presents the results of optimization for different goal functions. W1 and W2 are the weight factors.
\n\t\t\t\tMethod | \n\t\t\t\t\t\t\tGAOT Toolbox MATLAB | \n\t\t\t\t\t\t|
Goal functions | \n\t\t\t\t\t\t\tZ=W\n1∙T+W2∙W, W1 =0,7 and W2=0,3 | \n\t\t\t\t\t\t\tq 1 /b = 0.92 | \n\t\t\t\t\t\t
Z=W1∙T+W2∙W, W1=0,3 and W2 =0,7 | \n\t\t\t\t\t\t\tq 1 /b = 1.13 | \n\t\t\t\t\t\t|
Z= W1∙T, W1 =1 and W2 =0 | \n\t\t\t\t\t\t\tq 1 /b =0.71 | \n\t\t\t\t\t\t|
Z=W2∙W, W1 =0 and W2 =1 | \n\t\t\t\t\t\t\tq 1 /b= 1.3 | \n\t\t\t\t\t\t
Results of Optimization for Different Goal Functions
The results show that GA can determine the architectural parameters of the robot that provide an optimized workspace. Since the workspace of a parallel robot is far from being intuitive, the method developed should be very useful as a design tool.
\n\t\t\t\tHowever, in practice, optimization of the robot geometrical parameters should not be performed only in terms of workspace maximization. Some parts of the workspace are more useful considering a specific application. Indeed, the advantage of a bigger workspace can be completely lost if it leads to new collision in parts of it which are absolutely needed in the application. However, it’s not the case of the presented structure.
\n\t\t\tAn objective function is defined and used in optimization. Objective function contains workspace and transmission quality index. Optimization parameter was chosen as the link length L2. The constraints was established as 1<L2<1.2. After performing the optimization the following results were obtained:
\n\t\t\t\tMethod | \n\t\t\t\t\t\t\tGAOT Toolbox MATLAB | \n\t\t\t\t\t\t|
Goal functions | \n\t\t\t\t\t\t\tZ=W1∙T+W2∙W, W1 =0,7 and W2 =0,3 | \n\t\t\t\t\t\t\tL 2 = 1.1 | \n\t\t\t\t\t\t
Z=W1 ∙T+W2 ∙W, W1 =0,3 and W2 =0,7 | \n\t\t\t\t\t\t\tL 2 = 1.1556 | \n\t\t\t\t\t\t|
Z= W ∙T, W1 =1 and W2=0 | \n\t\t\t\t\t\t\tL 2 =1 | \n\t\t\t\t\t\t|
Z=W2∙W, W1 =0 and W2 =1 | \n\t\t\t\t\t\t\tL 2 =1.2 | \n\t\t\t\t\t\t
Results of Optimization for Different Goal Functions
Based on the presented optimization methodology we can conclude that the optimum design and performance evaluation of the Parallel Kinematics Machines is the key issue for an efficient use of Parallel Kinematics Machines. This is a very complex task and in this paper was proposed a framework for the optimum design considering basic characteristics of workspace, singularities and isotropy.
\n\t\t\tThe fundamental guidelines for genetic algorithm to optimal design of micro parallel robots have been introduced. It is concluded that with three basic generators selection, crossover and mutation genetic algorithm could search the optimum solution or near-optimal solution to a complex optimization problem of micro parallel robots. In the paper, design optimization is implemented with Genetic Algorithms (GA) for optimization considering transmission quality index, design space and workspace. Genetic algorithms (GA) are so far generally the best and most robust kind of evolutionary algorithms. A GA has a number of advantages. It can quickly scan a vast solution set. Bad proposals do not affect the end solution negatively as they are simply discarded. The obtained results have shown that the use of GA in such kind of optimization problem enhances the quality of the optimization outcome, providing a better and more realistic support for the decision maker.
\n\t\tOliviculture is one of the most ancient economic activities of the Mediterranean basin; therefore it is usually considered as a traditional sector and not able to positively enhance the economic and social development of European and North African countries where it is diffused.
\nToday, the olive miller has to directly face the market and all the multiple requirements of society. The growth of the olive miller company is linked to the development of its innovative capacity [1]. Understanding the factors that can determine the potential for innovation means understanding the main levers of intervention for the competitiveness and growth of an entrepreneurial activity [2] threatened by an evolving global context, which leads Italy in particular, among the European contest, to lose its positions of prestige always owned in the international context. In the last 20 years, we have therefore witnessed a “professional metamorphosis” of the role of the olive miller. In the last 20 years a metamorphosis occurred in the role of the olive miller inside his enterprise because the perspective with which the extraction process of extra-virgin olive oil can be considered, under a technological, chemical, biochemical, and sensorial point of view, has changed.
\nThe term “extraction” in the olive oil sector is, in fact, a word to be considered obsolete in the light of the progress of knowledge developed over the last 20 years [3, 4, 5, 6, 7, 8, 9]. The word “extraction” is referred to any operation with which one “extracts” something within a specific technical process. Applied to the olive oil sector, the term “extraction” implies the following misunderstanding: the bottled virgin olive oil (product obtained exclusively with the use of mechanical systems), under the chemical and sensory point of view, is the same contained (as small lipid drops) within the elaioplasts (the subcellular organelles specialized in storing lipids inside the cells of the drupe).
\nThis concept is wrong. In fact, during all the operations that start from the crushing, passing, across the malaxation, and the centrifugal separation of oil, a complex mass transfer occurs of those minor components (constitutive of the fruit, phenols, or of neo-formation, volatile compounds) from different tissues (epicarp, pulp, pit and seed) that compose the drupe to triglycerides organized in plastoglobules [8, 9]. Considering the occurrence of these phenomena, of a physical, chemical and biochemical nature, which make virgin olive oils different from the other lipidic plant matrices by composition and sensory and health properties, it is necessary to introduce a new term in the olive sector vocabulary that accurately reflects specificity and uniqueness of the complex transformation to which the process presides. Therefore, the verb “to extract” has to be replaced by the verb “to elaborate,” already earlier adopted more than 10 years ago by Carlos Gómez Herrera of the Institute de la Grasa of Sevilla [10]. In fact, the verb “to elaborate” means “to develop a project through careful coordination and transformation of the basic elements to give them an arrangement and a complete form that responds to the desired purpose.” In the olive oil world, the elaboration process of virgin olive oil has to allow to the olive miller the obtainment of the planned quantitative and qualitative results. This goal has to be planned at the moment of the raw material evaluation, or even before during the fruit development stage, at the moment in which the choice of the harvesting period occurs, nodal elements for the purposes of defining the characteristics of the product, and the interception of the pre-established market target [11, 12]. The word “extraction” relegates the oil miller of the past to the role of mute spectator who oversees a process whose outcomes are often unknown to him. He is a simple worker assigned to a manual labor only, who is not able to build solid strategy business based on segmentation, target, and product positioning; the verb “to elaborate” innovates the role and skills of the miller. He becomes the craftsman or the artisan, the one who exercises an art intended as an activity that requires a complex of technical knowledge at the service of a particular attitude [13].
\nThe modern miller masters the technology and the technological innovations. He is able to use the machines, regulating the macroscopic parameters of processing (specific energy, times, temperatures, atmosphere in contact with the product, and quantity of process water), with the aim to “modulate” the enzymatic activities that take place at the microscope level in the olive paste, consciously modifying the chemical, organoleptic, and health characteristics of the resulting virgin oil [9]. The word “modular” is a term borrowed from the world of music that refers to the ability to vary a sound or a tone, to achieve a harmonious effect. It is an indispensable term to describe the activity of the miller that, in a very short period of time, must make a series of decisive choices to obtain an extra-virgin olive oil, with a pleasant overall sensation, due to the perception of its components, phenolics and volatiles, which act as olfactory-gustatory, tactile, and kinesthetic stimuli balance between them.
\nHowever, the relationship of the olive oil sector with technological innovation is controversial. The olive and olive oil sector can be considered a technologically conservative productive system, that is, with a limited introduction of innovations compared to other sectors of agro-food [14]. This approach is apparently consistent with the behavior of the typical consumer. Consumers are linked to a model of consumption of extra-virgin olive oil based on habit and bound to a taste that has consolidated over time. People are reluctant to change, despite the pressure of a communication and training activities aimed to increase in the culture of olive oil for the improvement of the competitiveness of high-quality products [15, 16].
\nOn the contrary, the global agri-food system seems to be constantly encouraged to develop innovations in products, processes, or services able to face an increasingly pressing demand for healthy, quality food, able to satisfy, at the same time, healthy and hedonistic needs, with certain origin, and that they can offer a strong experiential dimension. In the agri-food sector, therefore, the tendency of the market is the creation of a growing demand for an increasingly differentiated and segmented product, in countercurrent with the world of olive oil.
\nTechnological innovation, and the product segmentation that derives from it, is the only path that can be followed by the olive oil sector, which must increase competitiveness. The exploitation of technological innovations is the only useful tool to increase production efficiency, product quality, process sustainability, and ultimately the profitability of the sector.
\nPublic and private research bodies are constantly working on innovative approaches to develop new products, processes or organizational models in the olive oil sector. However, the conversion of these research results to industrial innovations considerably more complex than generally believed. In practice, not all inventions, that is, new solutions developed in laboratories in response to a technical problem, can be transformed into innovations, then into new products or processes suitable for commercial exploitation for a competitive supply chain advantage.
\nIn the olive oil sector, the levers that guide research and development of innovations are constituted by the need to favor, during the extraction process, the separation of the highest quantity of oil, and of the best quality, modulating appropriately the complex series of physical transformations, chemical-physical, chemical, and biochemical within the olive paste. The increase in yield and product quality is an antithetical objective, which cannot be achieved simultaneously with the currently widespread technologies but which must be pursued to guarantee fair profitability for the operators of the sector.
\nInnovations can be distinguished by the degree of novelty with respect to existing technology, organization, and demand, in two different types: incremental innovations and radical innovations. Incremental innovations involve the improvement of a process, of a product or service with respect to a specific existing model or process. Radical innovations represent a break with existing products or processes. From these innovations, in some cases, new industries or market segments can arise. Incremental innovations are very numerous, while radical ones are rarer.
\nConsidering the machinery for the oil sector, the last radical innovation is represented by the introduction of centrifugal separation of oils and the transformation of the obsolete pressure extraction system, characterized by low working capacity, high labor demand, and poor hygienic standards, in the modern “continuous” system, highly effective and efficient. This innovation dates back to the 1970s. It involved the need to combine the decanter, the centrifuge with horizontal axis that continuously separates the oil from the olive paste, with the malaxers. The malaxer is a machine that operates in batch and that is necessary to favor, thanks to the heat exchange and agitation, the coalescence of minute droplets of oil into larger diameter drops, able to be separated in a centrifugal field and to guarantee satisfactory yields [8, 9].
\nMost of the incremental innovations developed in the last 30 years have had the purpose to improve the performance of the malaxers. The aim of these innovation was optimizing the machine geometry and the heat exchange (also by means the introduction of heat exchangers), improving the ratio between volumes of olive paste and exchange surface, to reduce treatment times and the number of malaxers necessary to guarantee continuity to the process. Observing the principles on which the incremental innovations were based, it is possible to state that the levers experimented to design new machines, able to improve the extraction yields and reduce the residual fat present in the by-products, are, on the physical point of view, the same principles on which traditionally the olive oil technology has always been based: heating and stirring to reduce the viscosity of the olive paste. We can consider, with good margins of certainty, that every technological effort based on the optimization of these three factors has reached the apex of applicability and that the machines currently on the market are the best performing. The perspectives for improvement are technically feasible if we persevere with the already consolidated approaches.
\nLooking at the characteristics of the oil by-products, it is clear that there is still room to increase the efficacy and efficiency of the machines destined for olive oil extraction. And here it is perhaps the case to dwell on the terms “effectiveness” and “efficiency,” often used indistinctly as synonyms but which actually reflect two distinct concepts. Effectiveness, in fact, indicates the ability to achieve the set objective, while efficiency evaluates the ability to do so using the minimum necessary resources. In the case of olive plant engineering, we can say that a technology is effective if it is able to increase yields and antioxidant content by reducing the losses in by-products and is effective if it achieves these goals in a sustainable manner, reducing energy costs for the benefit of business economies and the impact on the environment.
\nEffectiveness and efficiency can be achievable goals also thanks to the use of emerging technologies [17, 18, 19]. Emerging technologies are technologies available at the experimental level, which have already shown advantages in other fields of application and whose developments are now considered extremely promising in the coming decades. In the case of the extraction of extra-virgin olive oil, emerging technologies must ensure the simultaneous achievement of two different effects: a mechanical and a thermal effect. The mechanical effect comprises the breakage of the cells passed intact to the crusher and the release of further oil and minor compounds. The mild thermal effect is useful to accelerate, by means of the hydrophobic effect, the coalescence of minute lipid droplets. Among the emerging technologies that are spreading in the food industry, candidates to become real-scale plants in the oil sector in the near future, there are microwaves and ultrasounds [20, 21, 22, 23, 24, 25].
\nMicrowaves are electromagnetic radiations with frequencies between 300 MHz and 300 GHz [21]. They determine powerful and macroscopic thermal effects in the matrix due to the effect that the electromagnetic radiation exerts on the polar molecules, such as water. The polar molecules rotate with high frequency to align their dipole to the electromagnetic field, generating frictions with the adjacent molecules that induce a rapid and inhomogeneous heating. Because of thermal spots, areas where there is concentration, due to the inhomogeneity of the radiation and a high thermal increase, the dilatation of the aqueous phase of the cytoplasm induces a mild mechanical action of breaking of the cell walls.
\nUltrasounds are sound waves with frequencies from 20 kHz to some GHz, higher than the audible limit of the human ear. At low frequencies, between 20 and 40 kHz, they determine an evident mechanical effect, due to the phenomenon of cavitation, which contributes significantly to the breakage of the intact past cells to the crusher, freeing the lipid content (Figure 1); the thermal effect is mild and negligible [20].
\nCavitation breaks the intact past cells to the crusher freeing the lipid content. Picture by courtesy of Weber Ultrasonics AG.
Tests aimed at measuring the ability of the two technologies to be transferred in the design of real-scale plants and implemented in modern full-scale mills have been realized, and the performances in terms of effectiveness and efficiency have been measured.
\nFrom the point of view of effectiveness, and therefore of the capacity to increase extraction yields, the theoretical premises based on the intrinsic characteristics of the two technologies have been confirmed by the experimental evidence. In relation to the heating times, the microwaves showed the ability to significantly reduce the duration of the malaxation with the same extraction yields. On the contrary, the mechanical action of the ultrasounds, clearly superior to the mechanical action of the microwaves, combined a noticeable increase in extraction yields with a time reduction.
\nTwo technologies compared with two antithetical effects. What strategies can be applied to design the plant that will most likely contribute to the improvement of the process?
\nAlongside the efficacy observations summarized in terms of contraction of the malaxation times (one-tenth for the microwaves and one third for the ultrasounds), the considerations in terms of efficiency were decisive. The tests carried out in order to measure the efficiency of the processes have revealed how the microwaves represent a technology, at present, extremely energizing and not compatible with the more recent guidelines of the industry 4.0, which privilege processes able to preserve the natural resources.
\nExperimental evidence has led to the exclusion of the industrial scale-up of microwave technology: the only advantage constituted by the significant contraction of processing times did not match the desired increase in yields [21]; the lack of energy efficiency, moreover, represented a threat of increasing production costs incompatible with the production context that offers limited margins of profit.
\nPromising, on the contrary, was the premise for the implementation of ultrasound technology linked to the positive increase in yield, the mild thermal effect, and the high energy efficiency: three evidences that opened the prospect of achieving the goal of increasing yields and the concentration of minor compounds, reducing production costs, and improving company profit margins [20, 23, 24, 25].
\nHow is it possible to pass from the batch laboratory device, which is able to treat limited quantities of olive paste (about 3 kg) to plants that operate continuously, working tens of quintals of olives?
\nIt is here that it becomes fundamental to combine the multidisciplinary skills of the research groups. From the collaboration between knowledge areas, food technologies, food chemistry, and mechanical engineering, a design strategy has been realized. The starting point was the definition of the ideal geometry and then on the energy calculations necessary to create a plant able to guarantee the conversion of the conditions tested in batch (lab-scale) in an ultrasonic treatment administered continuously (full-scale).
\nIn terms of geometry, the construction of an ultrasonic system must start from the characteristics of the transducers present on the market and from the flexibility that these can offer during the design phase, also with a look at the possibility of realizing plant solutions suited to the different working capacities of the oil mills. The most commonly used transducers are the so-called probe transducers. The first prototypes made have favored this model because it integrates well with the triple tube heat exchangers already widespread on the market. This combination was chosen to maximize the effects of ultrasound, which are emphasized by the simultaneous heating of the oil paste, which, by reducing the viscosity of the fluid, promotes the propagation of the wave in the medium. Fluid dynamic simulation tests, carried out simultaneously with the experimental tests, have however highlighted some limitations of this geometry, proving how long, tortuous, and costly is the path necessary to develop an innovation.
\nSo the next step was the design and build of an ultrasound system based on the use of plate transducers. An octagonal section system has been created that combines ultrasonic treatment with heat exchange (Figure 2). It allows a thermal conditioning of the olive paste aimed at both heating and cooling, depending on the environmental and territorial context in which the technology is implemented. The sizing, based on the calculation of the specific energy to be administered, has shown that the amount of energy necessary to maximize the advantages obtainable from the use of ultrasound, for frequencies between 20 and 40 kHz, is equal to about 18,000 J/kg. 18,000 J/kg is a number that can mean nothing if not compared to other process operations [25]. In order to make clear the meaning of ultrasonic treatment, it is sufficient to think that the specific energy transferred from a mechanical crusher is approximately 30,000–36,000 J/kg.
\nThe inner part of the sono-heat-exchanger (on the left). The external structure of the sono-heat-exchanger (on the right).
The ultrasonic treatment, in this perspective, can be considered a sort of finishing of the crushing step. The ultrasonic treatment of the olive paste is fully classified as a mild technology. It is a delicate technology that allows to combine, for the first time in the history of the development of oil mills, the increase in yield (more than 1 kg of oil per 100 kg of olives) with the increase of the content in polyphenolic substances, minimizing the thermal and oxidative damage, demonstrated by the chemical analyzes aimed at the product classification and by the panel test.
\nThe use of ultrasound in the oil sector is part of key enabling technology, as it represents a technological solution capable of revitalizing the production system, and meets the social challenges related to food safety, sustainable agriculture, and bio-economy as it represents an efficient production system that can accelerate the conversion of companies toward sustainability.
\nUltrasounds also concretely open the way to a production model that, consistent with the principles of circular economy, leads the mills to exploit the potential to profitably integrate the use of differentiated pressing within the processing line. The use of the pitting machine, which is not widespread today due to the known yield losses, can be stimulated by the use of ultrasounds which have a positive effect on the extractability of the oil. The elimination of the core before the product enters the processing line has the advantage of increasing the working capacity of the plants and improving energy efficiency and offers the possibility of allocating the de-stoned pomace to more profitable purposes.
\nThe implementation of ultrasound in the olive oil extraction process is characterized by a high level of technological maturity (TRL, technology readiness levels) of 8, which corresponds to the development of the system and its validation on a real scale.
\nTable 1 shows the economic comparison between the traditional system and the innovative system with ultrasounds. The simulation is done on a crusher with a working capacity of 1500 kg/h that works 10 h a day for 80 days, about 3 months.
\nSimulation of economic budget comparison between the traditional system and the innovative system equipped with ultrasounds during a single harvesting season.
Assuming an average price of olives equal to €90 per quintal, and the selling price of oil equal to €7, without including in the comparison the premium price of oil extracted by ultrasound due to the increase in polyphenols and the highest health value, an increase in incomings of 116,700 euros is achieved. The return on investment can be quantified in just 2 years.
\nThe introduction of ultrasound in extra-virgin olive oil extraction is the first technology for the simultaneous increment of yield and quality of the product. The innovative EVOO process based on ultrasound extraction has several advantages useful to improve olive miller income: higher yield extraction, higher polyphenols, and lower bitter and pungent taste than traditional EVOO samples.
\nThis work has been supported by the AGER 2 Project, Grant No. 2016-0174, COMPETITIVE - Claims of Olive oil to iMProvE The market ValuE of the product. Ager is a project that creates a network of banking origin Foundations to support and to promote innovative research projects in the agri-food sector (Fondazione Cariplo, Fondazione Cassa di Risparmio di Bologna, Fondazione Cassa di Risparmio di Cuneo, Ente Cassa di Risparmio di Firenze, Fondazione Cassa di Risparmio di Ferrara, Fondazione Cassa di Risparmio Modena, Fondazione Cassa di Risparmio di Padova e Rovigo, Fondazione Cassa di Risparmio di Parma, Fondazione Cassa di Risparmio di Teramo, Fondazione Cassa di Risparmio di Trento e Rovereto, Fondazione Cassa di Risparmio di Udine e Pordenone, Fondazione di Venezia, Fondazione Cassa di Risparmio di Vercelli, Fondazione Cassa di Risparmio di Bolzano, Fondazione Cassa di Risparmio di Modena, Fondazione di Sardegna, Fondazione Cassa di Risparmio CON IL SUD).
\nThe author(s) declare(s) that there is no conflict of interest regarding the publication of this article.
This is a brief overview of the main steps involved in publishing with IntechOpen Compacts, Monographs and Edited Books. Once you submit your proposal you will be appointed a Author Service Manager who will be your single point of contact and lead you through all the described steps below.
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