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Introductory Chapter: Production Engineering

Written By

Majid Tolouei-Rad

Published: 23 November 2022

DOI: 10.5772/intechopen.108307

From the Edited Volume

Production Engineering and Robust Control

Edited by Majid Tolouei-Rad, Pengzhong Li and Liang Luo

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1. Introduction

Production engineering is a broad term covering many activities involved in the production life cycle of industrial products. The term itself is interchangeably used with manufacturing engineering as manufacturing is the backbone of production engineering.

There have been many developments in the domain of production engineering in recent years as reported in the literature. These include developments of new methods in production methods and systems and optimization for improving productivity or maximizing profit. For example, drilling as the most used production process is still the subject of study for improvement by contemporary researchers, and many of these works can be found in the literature [1, 2, 3, 4, 5, 6, 7, 8]. There are also reports on the improvements of conventional and nonconventional production processes [9, 10, 11], optimization of processes [6, 12, 13], and enhancement of properties [14]. In addition, there are many reports in the literature on the development of production systems including quality control, process planning, and production planning and control systems [15, 16, 17, 18, 19, 20, 21, 22, 23].

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2. Production processes

As shown in Figure 1, production engineering is broadly covering production processes and production systems, and each of these includes various operations. Production processes alter the shape, geometry, and properties of the workpiece enabling it to perform its function. Processing operations may include the enhancement of properties of the workpiece by means of heat treatment operations and improving the quality of the workpiece surfaces using surface processing operations. There is a variety of manufacturing operations including conventional and nonconventional methods. Generally, conventional manufacturing processes are preferred as these are often more economical and the equipment needed is readily available. However, in some cases, the use of nonconventional manufacturing processes is inevitable despite imposing higher costs. For example, Figure 2 shows a flat metal part with a complex external shape and many internal cut geometries. This part is cut from an 8 mm thickness AISI 304 L stainless steel plate. It is a relatively thick plate of hard-to-machine stainless steel material, making its production problematic using conventional methods. The use of a nonconventional method such as Abrasive Water Jet Machining (AWJM) makes this a relatively easy operation. This part is taken from a research work studying the optimization of AWJM process parameters for improving productivity [24]. Another example is shown in Figure 3 where a complex lattice structure is formed by connecting multiple curved surfaces with thin wall thicknesses. The material of this part is 316 stainless steel which is hard to machine, and its complex geometry and small wall thickness make its production impossible with conventional methods. It is produced by additive manufacturing (AM) also known as 3D printing from a powder-like material. This part is printed layer by layer using a layer thickness of 25 micrometers where powder-like metal particles are melted using a powerful laser beam in a process known as selective laser melting (SLM). The process is costly, and the rate of production is low; however, making it possible to produce some complex geometries that would have not been impossible otherwise.

Figure 1.

Classification of activities in production engineering.

Figure 2.

Map of Australia with embedded geometrical shapes cut from an 8 mm thickness AISI 304 L stainless steel plate using abrasive water jet machining (AWJM). (a) Side view. (b) Top view.

Figure 3.

A lattice structure printed from 316 stainless steel power using the selected laser melting (SLM) technique.

Cutlery items such as spoons and forks are examples of single-part products where no joining or assembly operations are needed after the single-part product is manufactured. However, most products consist of more than one part and there is a need for joining or assembling of these parts. The number of parts in a product where assembly or joining processes are needed can go from two to millions. A screwdriver has 2, a typical car has about 20,000, and the largest passenger aircraft has over 4 million parts that are individually manufactured and assembled to form a complex product with many assemblies and subassemblies. Many types of joining, and assembly operations are used in production plants. Some are permanent joining methods such as welding, brazing, soldering, riveting, and adhesives; and some provide the possibility of disassembly where mechanical fasters such as bolts and nuts or screws are used.

Quality control is often considered the last step of the production cycle although modern manufacturing strategies state that quality must be built into the product and must be incorporated during manufacturing and assembly operations. In either case, the quality of the product must be tested and verified before it leaves the production plant.

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3. Production systems

In general, production processes are referred to those operations where there is a need for physical contact of the product with processing equipment, or the worker; and a physical contact is not needed when the product is processed by production systems. Although some noncontact quality control methods are used, in most quality control activities there is a need for measuring the dimensional accuracy of the product or its properties requiring physical contact. Yet the quality control information is widely used in production systems for analysis of production where there is no need for physical contact. The assessment of product quality does not end in the production plant and it is still under quality assessment after delivering to the customer and beginning its service life. This is possible by receiving feedback from the customer and also by providing after-sales services. Accordingly, as shown in Figure 1, quality control is an activity that relates itself to both production processes and production systems.

In the literature, the production systems are also referred to as manufacturing support systems as processing operations cannot be accomplished without these activities. In addition to quality control, production systems include process planning and production planning and control systems. When a product is to be produced, one of the first steps is to design the product such that it meets the intended specifications. The number of parts, assemblies and subassemblies, processing operations, and equipment should all be identified in an activity known as process planning. Various methods of process planning and the level of detailed information provided on the process sheet varies in different production plants.

Production planning and control (PPC) takes into consideration the logistics problems such as how many products are to be produced in a day or in a year, how long the production line will continue producing the part or product considering market demands, what are the raw material and equipment requirements for responding to production needs, and so on. When production begins there is a need for production control to ensure that production is running smoothly, will be meeting the planned completion dates, and any potential problems that could disrupt a smooth production are identified and tackled.

References

  1. 1. Sobri SA, Heinemann R, Whitehead D. Carbon fibre reinforced polymer (CFRP) composites: Machining aspects and opportunities for manufacturing industries. In: Composite Materials: Applications in Engineering, Biomedicine and Food Science. Cham: Springer International Publishing; 2020. pp. 35-65
  2. 2. Aamir M, Tolouei-Rad M, Giasin K. Multi-spindle drilling of Al2024 alloy and the effect of TiAlN and TiSiN-coated carbide drills for productivity improvement. The International Journal of Advanced Manufacturing Technology. 2021;114(9):3047-3056
  3. 3. Tolouei-Rad M, editor. Drilling Technology. London, UK: IntechOpen; 2021 [Online]. Available from: https://www.intechopen.com/books/10375. DOI: 10.5772/intechopen.91561
  4. 4. Tolouei-Rad M, Aamir M. Introductory chapter: Drilling technology. In: Drilling Technology. London, UK: IntechOpen; 2021 [Online]. Available: https://www.intechopen.com/chapters/76535. DOI: 10.5772/intechopen.97648
  5. 5. Tolouei-Rad M, Aamir M. Analysis of the performance of drilling operations for improving productivity. In: Drilling Technology. London, UK: IntechOpen; 2021 [Online]. Available: https://www.intechopen.com/chapters/75613. DOI: 10.5772/intechopen.96497
  6. 6. Vafadar A, Hayward K, Tolouei-Rad M. Drilling reconfigurable machine tool selection and process parameters optimization as a function of product demand. Journal of Manufacturing Systems. 2017;45:58-69
  7. 7. Tolouei-Rad M, Shah A. Development of a methodology for processing of drilling operations. International Journal of Industrial and Manufacturing Engineering. 2012;6(12):2660-2664
  8. 8. Aamir M, Giasin K, Tolouei-Rad M, Ud Din I, Hanif MI, Kuklu U, Pimenov DY, Ikhlaq M. Effect of cutting parameters and tool geometry on the performance analysis of one-shot drilling process of AA2024-T3. Metals. 2021;11(6):854
  9. 9. Sahoo SP, Pandey K, Datta S. Performance of uncoated/coated carbide inserts during MQL (sunflower oil) assisted machining of Inconel 718 superalloy. Sādhanā. 2022;47(4):1-31
  10. 10. Jalali Azizpour M, Tolouei-Rad M. Evaluation of residual stress in HVOF stellite-6 coatings using non-contact drilling. Materials Research Express. 2019;6(6):066577
  11. 11. Xu M, Wei R, Li C, Kurniawan R, Chen J, Ko TJ. Comprehensive study on the cutting force modeling and machinability of high frequency electrical discharge assisted milling process using a novel tool. International Journal of Precision Engineering and Manufacturing-Green Technology. 2022;15:1-28
  12. 12. Aamir M, Tu S, Tolouei-Rad M, Giasin K, Vafadar A. Optimization and modeling of process parameters in multi-hole simultaneous drilling using taguchi method and fuzzy logic approach. Materials. 2020;13(3):680
  13. 13. Tolouei-Rad M, Bidhendi IM. On the optimization of machining parameters for milling operations. International Journal of Machine Tools and Manufacture. 1997;37(1):1-6
  14. 14. Tolouei-Rad M, Lichter E. The heat treatment analysis of e110 case hardening steel. Journal of Engineering Science and Technology. 2016;11(3):407-415
  15. 15. Muthiah KM, Huang SH. A review of literature on manufacturing systems productivity measurement and improvement. International Journal of Industrial and Systems Engineering. 2006;1(4):461-484
  16. 16. Tolouei-Rad M. Integration of part classification, cell formation and capacity adjustment. Journal of Achievements in Materials and Manufacturing Engineering. 2010;39(2):197-203
  17. 17. Tamás P, Illés B. Process improvement trends for manufacturing systems in industry 4.0. Academic Journal of Manufacturing Engineering. 2016;14(4):119-125
  18. 18. Tolouei-Rad M. Intelligent analysis of utilization of special purpose Machines for Drilling Operations. In: Intelligent Systems. London, UK: IntechOpen; 2012 [Online]. Available: https://www.intechopen.com/chapters/30663. DOI: 10.5772/36896
  19. 19. Zhao C, Li J, Huang N. Efficient algorithms for analysis and improvement of flexible manufacturing systems. IEEE Transactions on Automation Science and Engineering. 2015;13(1):105-121
  20. 20. Tolouei-Rad M. An efficient algorithm for automatic machining sequence planning in milling operations. International Journal of Production Research. 2003;41(17):4115-4131
  21. 21. Robinson A. Modern Approaches to Manufacturing Improvement: The Shingo System: The Shingo System. New York, USA: Routledge; 2017
  22. 22. Mula J, Poler R, García-Sabater JP, Lario FC. Models for production planning under uncertainty: A review. International Journal of Production Economics. 2006;103(1):271-285
  23. 23. Kang CW, Ramzan MB, Sarkar B, Imran M. Effect of inspection performance in smart manufacturing system based on human quality control system. The International Journal of Advanced Manufacturing Technology. 2018;94(9):4351-4364
  24. 24. Llanto JM, Vafadar A, Tolouei-Rad M. Multi-objective optimisation in abrasive waterjet contour cutting of AISI 304L. In: Production Engineering [Working Title]. London, UK: IntechOpen; 2022 [Online]. Available: https://www.intechopen.com/online-first/83563. DOI: 10.5772/intechopen.106817

Written By

Majid Tolouei-Rad

Published: 23 November 2022