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Module-based machinery design: a method to support the design of modular machine families for reconfigurable manufacturing systems

Abstract

Increased demand for a greater variety of products has forced many companies to rethink their strategies to offer more product variants without sacrificing production efficiency. Consequently, to satisfy this demand for customized products in shorter lead time and lower costs, production systems must be highly reactive and reconfigurable. In this context, the concept of reconfigurable manufacturing systems (RMS) emerged in the late 1990s to overcome the limitations of traditional manufacturing in rapidly and cost-efficiently respond to changing market conditions. However, the traditional development process of special-purpose machines to meet the requirements of change turned into an expensive and time-consuming task, challenging practitioners and scholars for reducing the impact of variety on the manufacturing costs. In order to aid the transition towards the reconfigurability from an engineering design perspective, this article introduces the Module-Based Machinery Design, a method to support the conceptual and system-level design of modular machine families for RMS. The contributions of this research include (i) the organization of existing methods and techniques for designing module-based product families into a coherent framework intended for developing machine families for RMS. (ii) The proposition of a design method that accomplishes the majority of RMS characteristics through the use of modularity. (iii) The introduction of the Adherence Index, a measure to indicate the level of utilization of basic, auxiliary and adaptive modules within a module-based machine variant. (iv) Finally, the analytical evidence of an RMS implementation through the design process of a family of modular floor level palletizers.

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References

  1. Zhu B, Li Y, Feng G (2017) A fuzzy optimisation method for product variety selection under uncertainty constraints. Int J Comput Integr Manuf 30(6):606–615

    Article  Google Scholar 

  2. Simpson TW, Jiao JR (2014) Advances in product family and product platform design. Springer New York, New York

    Book  Google Scholar 

  3. Roland Berger Strategy Consultants, Mastering product complexity, 2012

  4. Jiao J, Simpson TW, Siddique Z (2007) Product family design and platform-based product development: a state-of-the-art review. J Intell Manuf 18(1):5–29

    Article  Google Scholar 

  5. Antunes JAV, Alvarez R, Bortolotto P, Klippel M, de Pellegrini I (2008) Sistemas de produção: Conceitos e práticas para projetos e gestão da produção enxuta. Bookman, Porto Alegre

    Google Scholar 

  6. Kull H (2015) Mass Customization: Opportunities, methods, and challenges for manufacturers, vol. 1. Apress

  7. Marseu E, Kolberg D, Birtel M, Zühlke D (2016) Interdisciplinary engineering methodology for changeable cyber-physical production systems. IFAC-PapersOnLine 49(31):85–90

    Article  Google Scholar 

  8. Rösiö C, Säfsten K (2013) Reconfigurable production system design—theoretical and practical challenges. J Manuf Technol Manag 24(7):998–1018

    Article  Google Scholar 

  9. Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G, van Brussel H (1999) Reconfigurable manufacturing systems. CIRP Ann 48(2):527–540

    Article  Google Scholar 

  10. Koren Y (2006) General RMS characteristics. Comparison with dedicated and flexible systems. In: D AI (ed) Reconfigurable manufacturing systems and transformable factories. Springer, Berlin, pp 27–45

    Chapter  Google Scholar 

  11. Andersen A-L, Brunoe TD, Nielsen K (2015) Reconfigurable manufacturing on multiple levels: literature review and research directions. IFIP Adv Inf Commun Technol 459:266–273

    Article  Google Scholar 

  12. Andersen A-L, Brunoe TD, Nielsen K, Rösiö C (2017) Towards a generic design method for reconfigurable manufacturing systems: analysis and synthesis of current design methods and evaluation of supportive tools. J Manuf Syst 42:179–195

    Article  Google Scholar 

  13. Mehrabi MG, Ulsoy AG, Koren Y (2000) Reconfigurable manufacturing systems: key to future manufacturing. J Intell Manuf 11:403–419

    Article  Google Scholar 

  14. Schuh G, Lenders M, Nussbaum C, Kupke D (2009) Design for Changeability. In: Changeable and Reconfigurable Manufacturing Systems, 1st edn. Springer-Verlag London Limited, London, pp 251–266

  15. Lameche K, Najid NM, Castagna P, Kouiss K (2017) Modularity in the design of reconfigurable manufacturing systems. IFAC-PapersOnLine 50(1):3511–3516

    Article  Google Scholar 

  16. Mpofu K, Kumile CM, Tlale NS (2008) Design of reconfigurable machine systems: knowledge based approach. J Konbin 8(1):135–144

    Article  Google Scholar 

  17. Bi ZM, Lang SYT, Shen W, Wang L (2008) Reconfigurable manufacturing systems: the state of the art. Int J Prod Res 46(4):967–992

    Article  MATH  Google Scholar 

  18. El Maraghy HA (2006) Flexible and reconfigurable manufacturing systems paradigms. Flex Serv Manuf J 17(4):261–276

    Google Scholar 

  19. Malhotra V, Raj T, Arora A (2010) Excellent techniques of manufacturing systems: RMS and FMS. Int J Eng Sci Technol 2(3):137–142

    Google Scholar 

  20. Zhang G, Liu R, Gong L, Huang Q (2006) An analytical comparison on cost and performance among DMS, AMS, FMS and RMS. In: D AI (ed) Reconfigurable manufacturing systems and transformable factories. Springer, Berlin, pp 659–673

    Chapter  Google Scholar 

  21. Mehrabi MG, Ulsoy AG, Koren Y, Heytker P (2002) Trends and perspectives in flexible and reconfigurable manufacturing systems. J Intell Manuf 13:135–146

    Article  Google Scholar 

  22. Abdi MR, Labib AW (2004) Feasibility study of the tactical design justification for reconfigurable manufacturing systems using the fuzzy analytical hierarchical process. Int J Prod Res 42(15):3055–3076

    Article  MATH  Google Scholar 

  23. Benkamoun N, Kouiss K, Huyet A-L (2015) An Intelligent Design Environment for Changeability Management - Application To, in ICED, pp 1–10

  24. Marion TJ, Thevenot HJ, Simpson TW (2007) A cost-based methodology for evaluating product platform commonality sourcing decisions with two examples. Int J Prod Res 45(22):5285–5308

    Article  MATH  Google Scholar 

  25. Park J, Simpson TW (2008) Toward an activity-based costing system for product families and product platforms in the early stages of development. Int J Prod Res 46(1):99–130

    Article  MATH  Google Scholar 

  26. Meyer MH, Lehnerd AP (1997) The power of product platforms. Free Press

  27. Erens F, Verhulst K (1997) Architectures for product families. Comput Ind 33(2–3):165–178

    Article  Google Scholar 

  28. T. W. Simpson, Z. Siddique, and J. (Roger) Jiao (2006) Product platform and product family design: methods and applications, 1st ed. Springer US

  29. Kong FB, Ming XG, Wang L, Wang XH, Wang PP (2009) On Modular Products Development. CERA 17(4):291–300

  30. Otto K, Hölttä-Otto K, Simpson TW, Krause D, Ripperda S, Ki Moon S (2016) Global views on modular design research: linking alternative methods to support modular product family concept development. J Mech Des 138(7):071101

    Article  Google Scholar 

  31. Du X, Jiao J, Tseng MM (2001) Architecture of product family: Fundamentals and methodology. CERA 9(4):309–325

  32. Ulrich K (1995) The role of product architecture in the manufacturing firm. Res Policy 24(3):419–440

    Article  Google Scholar 

  33. Jiao J, Tseng MM (2000) Fundamentals of product family architecture. Integr Manuf Syst 11(7):469–483

    Article  Google Scholar 

  34. Jiao J, Tseng MM (1999) A methodology of developing product family architecture for mass customization. J Intell Manuf 10(1):3–20

    Article  Google Scholar 

  35. Piran FAS, Lacerda DP, Antunes JAV, Viero CF, Dresch A (2016) Modularization strategy: analysis of published articles on production and operations management (1999 to 2013). Int J Adv Manuf Technol 86(1–4):507–519

    Article  Google Scholar 

  36. Martin MV, Ishii K (2002) Design for variety: developing standardized and modularized product platform architectures. Res Eng Des 13(4):213–235

  37. Meng X, Jiang Z, Huang GQ (2007) On the module identification for product family development. Int J Adv Manuf Technol 35(1–2):26–40

    Article  Google Scholar 

  38. Liu Z, Wong YS, Lee KS (2010) Modularity analysis and commonality design: a framework for the top-down platform and product family design. Int J Prod Res 48(12):3657–3680

    Article  MATH  Google Scholar 

  39. Emmatty FJ, Sarmah SP (2012) Modular product development through platform-based design and DFMA. J Eng Des 23(9):696–714

    Article  Google Scholar 

  40. Hanafy M, Elmaraghy H (2015) A modular product multi-platform configuration model. Int J Comput Integr Manuf 28(9):999–1014

    Article  Google Scholar 

  41. Goswami M, Daultani Y, Tiwari MK (2017) An integrated framework for product line design for modular products: product attribute and functionality-driven perspective. Int J Prod Res 55(13):3862–3885

    Article  Google Scholar 

  42. Fettermann D d C, Echeveste MES (2014) New product development for mass customization: a systematic review. Prod Manuf Res 2(1):266–290

    Google Scholar 

  43. Ulrich KT, Eppinger SD (2012) Product design and development: Fifth Edition

  44. Pahl G, Beitz W, Feldhusen J, Grote K-H (2007) Engineering design: a systematic approach, Springer, no. 2, p. 617

  45. Rozenfeld H et al. (2006) Gestão de Desenvolvimento de Produtos: Uma referência para a melhoria do processo, 1st ed. Editora Saraiva

  46. Mascle C, Zhao HP (2008) Integrating environmental consciousness in product/process development based on life-cycle thinking. Int J Prod Econ 112(1):5–17

    Article  Google Scholar 

  47. Charter M, Tischner U (2017) Sustainable solutions: developing products and services for the future. Routledge

  48. Xiao W, Du G, Zhang Y, Liu X (2018) Coordinated optimization of low-carbon product family and its manufacturing process design by a bilevel game-theoretic model. J Clean Prod 184:754–773

    Article  Google Scholar 

  49. Cox JF, Schleier JG (2010) Theory of constraints handbook. McGraw-Hill, New York

    Google Scholar 

  50. Hilier F, Lieberman G (2015) Introduction to operational research, 10th edn. McGraw-Hill, New York

    Google Scholar 

  51. Montgomery DC, Runger GC (2011) Applied statistics and probability for engineers, Fifth Edition, 5th ed. John Wiley & Sons, Ltd

  52. Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359–370

    Article  Google Scholar 

  53. Stone R, Wood K (2000) A heuristic method for identifying modules for product architectures. Des Stud 21:1–47

    Article  Google Scholar 

  54. Yoshimura M, Takeuchi A (1994) Concurrent optimization of product design and manufacturing based on information of users’ needs. CERA 2(1):33–44

  55. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B Methodol 39(1):1–38

    MathSciNet  MATH  Google Scholar 

  56. Abbas OA (2008) Comparisons between data clustering algorithms. Int Arab J Inf Technol 5(3):320–325

    Google Scholar 

  57. Suh NP (1998) Engineering design axiomatic design theory for systems. Res Eng Des 10:189–209

    Article  Google Scholar 

  58. Suh NP (2001) Axiomatic design: advances and applications. Oxford University Press, New York, p 528

    Google Scholar 

  59. Kusiak A, Chow WS (1987) Efficient solving of the group technology problem. J Manuf Syst 6(2):117–124

    Article  Google Scholar 

  60. Jung S, Simpson TW (2017) New modularity indices for modularity assessment and clustering of product architecture. J Eng Des 28(1):1–22

    Article  Google Scholar 

  61. Jiao J, Tseng MM (1999) A pragmatic approach to product costing based on standard time estimation. Int J Oper Prod Manag 19(7):738–755

    Article  Google Scholar 

  62. Kohlhase N, Birkhofer H (1996) Development of modular structures: the prerequisite for successful modular products. J Eng Des 7(3):279–291

    Article  Google Scholar 

  63. Popple RA (2009) The science of palletizing: how to choose the right system. Columbia Machine, Inc., Vancouver

    Google Scholar 

  64. DAN‐Palletizer. [Online]. Available: https://www.wrh-global.com.au/en/3677/DAN-Palletizer.htm. Accessed 28 Sep 2018

  65. Frank E, Hall MA, Witten IH (2016) The WEKA Workbench. Online Appendix for Data Mining: Practical Machine Learning Tools and Techniques

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Correspondence to Leandro Gauss.

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Gauss, L., Lacerda, D.P. & Sellitto, M.A. Module-based machinery design: a method to support the design of modular machine families for reconfigurable manufacturing systems. Int J Adv Manuf Technol 102, 3911–3936 (2019). https://doi.org/10.1007/s00170-019-03358-1

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Keywords

  • Reconfigurable manufacturing systems (RMS)
  • Modularity
  • Engineering design
  • Product family design
  • Platform-based product development