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Modularity assessment in reconfigurable manufacturing system (RMS) design: an Archived Multi-Objective Simulated Annealing-based approach

  • Hichem Haddou BenderbalEmail author
  • Mohammed Dahane
  • Lyes Benyoucef
ORIGINAL ARTICLE

Abstract

Enhancing productivity, reducing inaccuracy and avoiding time waste at changeover are considered major drivers in manufacturing system design. One of the emerging paradigms concerned with these characteristics is reconfigurable manufacturing systems (RMSs). The high responsiveness and performance efficiencies of RMS make it a convenient manufacturing paradigm for and flexible enabler of mass customization. The RMS offers customized flexibility and a variety of alternatives as features thanks to its reconfigurable machine tool (RMT). These machines represent a major component of RMS and are based on an adjustable, modular and reconfigurable structure. Hence, the system modularity is of great importance. This paper outlines a multi-objective approach to optimize the RMS design. Three objectives are considered: the maximization of the system modularity, the minimization of the system completion time and the minimization of the system cost. We developed a modularity-based multi-objective approach that uses an adapted version of the “Archived Multi-Objective Simulated Annealing” (AMOSA) method to solve the optimization problem by selecting from a set of candidate machines the most suitable ones. Implemented, the decision maker can use a multi-objective decision making tool based on the well-known “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) to choose the best solution in the Pareto front according to his preferences. We demonstrated the applicability of the proposed approach through an illustrative example and an analysis of the obtained numerical results.

Keywords

Reconfigurable manufacturing systems System design Modularity index Performance metrics Process plan Machine selection AMOSA TOPSIS 

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References

  1. 1.
    Abdi MR, Labib AW (2003) A design strategy for reconfigurable manufacturing systems (RMSs) using analytical hierarchical process (AHP): a case study. Int J Prod Res 41(10):2273–2299CrossRefGoogle Scholar
  2. 2.
    Abdi MR, Labib AW (2004) Grouping and selecting products: the design key of reconfigurable manufacturing systems (RMSs). Int J Prod Res 42(3):521–546CrossRefGoogle Scholar
  3. 3.
    Andersen AL, Brunoe TD, Nielsen K (2015) Reconfigurable manufacturing on multiple levels: Literature review and research directions. In: IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2015 (no. Part I pp. 266-273). Springer, TokyoGoogle Scholar
  4. 4.
    Andersen AL, Nielsen K, Brunoe TD (2016) Prerequisites and barriers for the development of reconfigurable manufacturing systems for high speed ramp-up. Proc CIRP 51:7–12CrossRefGoogle Scholar
  5. 5.
    Andersen AL, Brunoe TD, Nielsen K, Rösiö C (2017a) Towards a generic design method for reconfigurable manufacturing systems: analysis and synthesis of current design methods and evaluation of supportive tools. J Manuf Syst 42:179–195CrossRefGoogle Scholar
  6. 6.
    Andrisano AO, Leali F, Pellicciari M, Pini F, Vergnano A (2012) Hybrid reconfigurable system design and optimization through virtual prototyping and digital manufacturing tools. Int J Interact Des Manuf 6(1):17–27CrossRefGoogle Scholar
  7. 7.
    Babu AS (2013) Reconfigurations of manufacturing systems—an empirical study on concepts, research, and applications. Int J Adv Manuf Technol 66(1–4):107–124Google Scholar
  8. 8.
    Bandyopadhyay S, Saha S, Maulik U, Deb K (2008) A simulated annealing-based multiobjective optimization algorithm: AMOSA. IEEE Trans Evol Comput 12(3):269–283CrossRefGoogle Scholar
  9. 9.
    Battaïa O, Dolgui A, Guschinsky N (2016a) Decision support for design of reconfigurable rotary machining systems for family part production. Int J Prod Res 55:1–18Google Scholar
  10. 10.
    Battaïa O, Dolgui A, Guschinsky N (2016b) Integrated process planning and system configuration for mixed-model machining on rotary transfer machine. Int J Comput Integr Manuf 55:1–16Google Scholar
  11. 11.
    Bensmaine A, Dahane M, Benyoucef L (2013) A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment. Comput Ind Eng 66(3):519–524CrossRefGoogle Scholar
  12. 12.
    Bi ZM, Lang SY, Shen W, Wang L (2008) Reconfigurable manufacturing systems: the state of the art. Int J Prod Res 46(4):967–992CrossRefzbMATHGoogle Scholar
  13. 13.
    Bollinger J, Benson DK, Cloud N (1998) Visionary manufacturing challenges for 2020. National Research Council. Visionary manufacturing challenges for 2020. Committee on visionary manufacturing challenges, board on manufacturing and engineering design, commission on engineering and technical systems. National Research Council Report. National Academy Press, Washington, DCGoogle Scholar
  14. 14.
    Chaube A, Benyoucef L, Tiwari MK (2012) An adapted NSGA-2 algorithm based dynamic process plan generation for a reconfigurable manufacturing system. J Intell Manuf 23(4):1141–1155CrossRefGoogle Scholar
  15. 15.
    Chen L, Xi FJ, Macwan A (2005) Optimal module selection for preliminary design of reconfigurable machine tools. J Manuf Sci Eng 127(1):104–115CrossRefGoogle Scholar
  16. 16.
    Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  17. 17.
    Deif AM, ElMaraghy WH (2006) A systematic design approach for reconfigurable manufacturing systems. In Advances in design. Springer, London, pp 219–228Google Scholar
  18. 18.
    Delorme X, Malyutin S, Dolgui A (2016) A multi-objective approach for design of reconfigurable transfer lines. IFAC-PapersOnLine 49(12):509–514CrossRefGoogle Scholar
  19. 19.
    ElMaraghy H (2005) Flexible and reconfigurable manufacturing systems paradigms. Int J Flex Manuf Syst 17(4):261–276CrossRefzbMATHGoogle Scholar
  20. 20.
    ElMaraghy HA (2007) Reconfigurable process plans for responsive manufacturing systems, digital enterprise technology: Perspectives & future challenges. In: Cunha PF, Maropoulos PG (eds) Springer Science, ISBN: 978-0-387-49863-8, pp 35-44Google Scholar
  21. 21.
    ElMaraghy H (2009) Changing and evolving products and systems—models and enablers. In: ElMaraghy H (ed) Changeable and reconfigurable manufacturing systems. Springer-Verlag, London, pp 25–45CrossRefGoogle Scholar
  22. 22.
    Esmaeilian B, Behdad S, Wang B (2016) The evolution and future of manufacturing: a review. J Manuf Syst 39:79–100CrossRefGoogle Scholar
  23. 23.
    Farid AM (2008) Facilitating ease of system reconfiguration through measures of manufacturing modularity. Proc Inst Mech Eng B J Eng Manuf 222(10):1275–1288CrossRefGoogle Scholar
  24. 24.
    Fredriksson P (2006) Mechanisms and rationales for the coordination of a modular assembly system: the case of Volvo cars. Int J Oper Prod Manag 26(4):350–370MathSciNetCrossRefGoogle Scholar
  25. 25.
    Gadalla M, Xue D (2016) Recent advances in research on reconfigurable machine tools: a literature review. Int J Prod Res 55:1–15Google Scholar
  26. 26.
    Galan R, Racero J, Eguia I, Garcia JM (2007) A systematic approach for product families formation in reconfigurable manufacturing systems. Robot Comput Integr Manuf 23(5):489–502CrossRefGoogle Scholar
  27. 27.
    Goyal KK, Jain PK, Jain M (2013) A novel methodology to measure the responsiveness of RMTs in reconfigurable manufacturing system. J Manuf Syst 32(4):724–730CrossRefGoogle Scholar
  28. 28.
    Guan X, Dai X, Qiu B, Li J (2012) A revised electromagnetism-like mechanism for layout design of reconfigurable manufacturing system. Comput Ind Eng 63(1):98–108CrossRefGoogle Scholar
  29. 29.
    Gupta A, Jain PK, Kumar D (2015) Configuration selection of reconfigurable manufacturing system based on performance. Int J Ind Syst Eng 20(2):209–230Google Scholar
  30. 30.
    Gurumurthy JP (1998) ‘Life-cycle Modularity in Product Design,’ M.S. Thesis, University of AlabamaGoogle Scholar
  31. 31.
    Gyulai D, Monostori L (2017) Capacity management of modular assembly systems. J Manuf Syst 43:88–99CrossRefGoogle Scholar
  32. 32.
    Haddou Benderbal H, Dahane M, Benyoucef L (2015a) “A new flexibility index for machines selection in RMS design problem: Multi-objective approach.” CIE45 Conference Proceedings Volumes (Papers Online) Metz (France), 28–30 October 2015Google Scholar
  33. 33.
    Haddou Benderbal H, Dahane M, Benyoucef L (2015b) “A new robustness index for machines selection in reconfigurable manufacturing system.” Proceedings of 6th IEEE international conference on Industrial Engineering and Systems Management (IESM), Seville, Spain, 21–23 October, 1019–1026Google Scholar
  34. 34.
    Haddou Benderbal H, Dahane M, Benyoucef L (2016) Hybrid heuristic to minimize machine’s unavailability impact on reconfigurable manufacturing system using reconfigurable process plan. IFAC-PapersOnLine 49(12):1626–1631CrossRefGoogle Scholar
  35. 35.
    Haddou Benderbal H, Dahane M, Benyoucef L (2017) Flexibilitybased multi-objective approach for machines selection in reconfigurable manufacturing system (RMS) design under un- availability constraints. Int J Prod Res 55(20):6033–6051Google Scholar
  36. 36.
    Hasan F, Jain PK, Kumar D (2013) Machine reconfigurability models using multi-attribute utility theory and power function approximation. Proc Eng 64:1354–1363CrossRefGoogle Scholar
  37. 37.
    Hasan F, Jain PK, Kumar D (2014) Performance issues in reconfigurable manufacturing system. DAAAM Int Sci Book Paper 24:295–310Google Scholar
  38. 38.
    Heisel U, Meitzner M (2006) Progress in reconfigurable manufacturing systems. In: Dashchenko AI (ed) Reconfigurable manufacturing systems and transformable factories. Springer Verlag, Berlin/Heidelberg, pp 47–62Google Scholar
  39. 39.
    Hsieh S, Hung CR (2004) Feasibility study of modular plant for 300 mm-IC fabrications. J Intell Manuf 15(2):233–244CrossRefGoogle Scholar
  40. 40.
    Hwang CL, Lai YJ, Liu TY (1993) A new approach for multiple objective decision making. Comput Oper Res 20(8):889–899CrossRefzbMATHGoogle Scholar
  41. 41.
    Katz R, Moon YM (2000) Virtual arch type reconfigurable machine tool design: principles and methodology. Ann Arbor 1001:48109Google Scholar
  42. 42.
    Koren Y (2006) General RMS characteristics. Comparison with dedicated and flexible systems In: Dashchenko A.I. (ed) Reconfigurable manufacturing systems and transformable factories. Springer Verlag, Berlin/Heidelberg, pp 27–46Google Scholar
  43. 43.
    Koren Y (2010) The global manufacturing revolution: Product-process-business integration and reconfigurable systems (Vol. 80). John Wiley & Sons, HobokenGoogle Scholar
  44. 44.
    Koren Y, Shpitalni M (2010) Design of reconfigurable manufacturing systems. J Manuf Syst 29(4):130–141. doi: 10.1016/j.jmsy.201101.001
  45. 45.
    Koren Y, Ulsoy AG (2002) Vision, principles and impact of reconfigurable manufacturing systems. Powertrain Int, 5(3): pp 14–21Google Scholar
  46. 46.
    Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G, Van Brussel H (1999) Reconfigurable manufacturing systems. CIRP Ann Manuf Technol 48(2): pp 527–540Google Scholar
  47. 47.
    Kumar L, Jain PK (2010) Dynamic cellular manufacturing systems design—a comprehensive model & HHGA. Adv Prod Eng Manage J 5(3):151–162Google Scholar
  48. 48.
    Maniraj M, Pakkirisamy V, Jeyapaul R (2015) An ant colony optimization–based approach for a single-product flow-line reconfigurable manufacturing systems. Proc Inst Mech Eng B J Eng Manuf 231(7): 1229-1236Google Scholar
  49. 49.
    Mehrabi MG, Ulsoy AG, Koren Y (2000) Reconfigurable manufacturing systems: key to future manufacturing. J Intell Manuf 11(4):403–419CrossRefGoogle Scholar
  50. 50.
    Mesa J, Maury H, Arrieta R, Bula A, Riba C (2015) Characterization of modular architecture principles towards reconfiguration: a first approach in its selection process. Int J Adv Manuf Technol 80(1–4):221–232CrossRefGoogle Scholar
  51. 51.
    Mittal KK, Jain PK (2014) An overview of performance measures in reconfigurable manufacturing system. Proc Eng 69:1125–1129CrossRefGoogle Scholar
  52. 52.
    Mohapatra P, Benyoucef L, Tiwari MK (2013) Realising process planning and scheduling integration through adaptive setup planning. Int J Prod Res 51(8):2301–2323CrossRefGoogle Scholar
  53. 53.
    Moon YM, Kota S (2002) Design of reconfigurable machine tools. J Manuf Sci Eng 124(2):480–483CrossRefGoogle Scholar
  54. 54.
    Murata S, Kurokawa H, Yoshida E, Tomita K, Kokaji S (1998) A 3-D self-reconfigurable structure. In robotics and automation, 1998. Proceedings. IEEE International Conference on (Vol. 1, pp. 432-439). LeuveGoogle Scholar
  55. 55.
    Musharavati F, Hamouda ASM (2012) Enhanced simulated-annealing-based algorithms and their applications to process planning in reconfigurable manufacturing systems. Adv Eng Softw 45(1):80–90CrossRefGoogle Scholar
  56. 56.
    Nallakumarasamy G, Srinivasan PSS, Venkatesh Raja K, Malayalamurthi R (2011) Optimization of operation sequencing in CAPP using simulated annealing technique (SAT). Int J Adv Manuf Technol 54(5-8):721–728 doi: 10.1007/s00170-010-2977-8
  57. 57.
    Niroomand I, Kuzgunkaya O, Bulgak AA (2014) The effect of system configuration and ramp-up time on manufacturing system acquisition under uncertain demand. Comput Ind Eng 73:61–74CrossRefGoogle Scholar
  58. 58.
    Padayachee J, Bright G, Masekamela I (2009) Modular reconfigurable machine tools: design, control and evaluation. S Afr J Ind Eng 20(2):127–143Google Scholar
  59. 59.
    Pattanaik LN, Jain PK, Mehta NK (2007) Cell formation in the presence of reconfigurable machines. Int J Adv Manuf Technol 34(3–4):335–345CrossRefGoogle Scholar
  60. 60.
    Pham DT, Eldukhri EE, Peat B, Setchi R, Soroka A, Packianather MS, Thomas A, Dadam Y, Dimov S (2004) Innovative Production Machines and Systems (I*PROMS): A network of excellence funded by the EU sixth framework programme. Proceedings of the 2nd IEEE International Conference on Industrial Informatics, INDIN’04, (pp. 540–546). BerlinGoogle Scholar
  61. 61.
    Puik E, Telgen D, Moergestel L, Ceglarek D (2017) Assessment of reconfiguration schemes for reconfigurable manufacturing systems based on resources and lead time. Robot. Comput Integr Manuf 43: 30–38Google Scholar
  62. 62.
    Renna P (2017) A Decision investment model to design manufacturing systems based on a genetic algorithm and Monte-Carlo simulation. Int J Comput Integr Manuf 30(6):590-605Google Scholar
  63. 63.
    Rösiö C (2012) Supporting the design of reconfigurable production systems (Doctoral dissertation), Mälardalen University, SwedenGoogle Scholar
  64. 64.
    Rösiö C, Säfsten K (2013) Reconfigurable production system design–theoretical and practical challenges. J Manuf Technol Manag 24(7):998–1018CrossRefGoogle Scholar
  65. 65.
    Rosselli F (2003) FuTMaN: The Future of Manufacturing in Europe 2015-2020. The challenge for sustainability. In: Final Report for the European Commission. Directorate-General Joint Research CenterGoogle Scholar
  66. 66.
    Shaik AM, Rao VK, Rao CS (2015) Development of modular manufacturing systems—a review. Int J Adv Manuf Technol 76(5–8):789–802CrossRefGoogle Scholar
  67. 67.
    Tracht K, Hogreve S (2012) Decision making during design and reconfiguration of modular assembly lines. In: ElMaraghy H. (eds) Enabling manufacturing competitiveness and economic sustainability. Springer, Berlin, Heidelberg ISBN: 978-3-642-23860-4, pp 105–110Google Scholar
  68. 68.
    Tu Q, Vonderembse MA, Ragu-Nathan TS, Ragu-Nathan B (2004) Measuring modularity-based manufacturing practices and their impact on mass customization capability: a customer-driven perspective. Decis Sci 35(2):147–168CrossRefGoogle Scholar
  69. 69.
    Ulrich KT, Tung K (1991) Fundamentals of product modularity. In: Sharon (ed) Issues in design/manufacture integration. ASME, New York, pp 73–79Google Scholar
  70. 70.
    Wang GX, Huang SH, Shang XW, Yan Y, Du JJ (2016) Formation of part family for reconfigurable manufacturing systems considering bypassing moves and idle machines. J Manuf Syst 41:120–129CrossRefGoogle Scholar
  71. 71.
    Wang W, Koren Y (2012) Scalability planning for reconfigurable manufacturing systems. J Manuf Syst 31(2):83–91CrossRefGoogle Scholar
  72. 72.
    Yigit AS, Ulsoy AG, Allahverdi A (2002) Optimizing modular product design for reconfigurable manufacturing. J Intell Manuf 13(4):309–316CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  • Hichem Haddou Benderbal
    • 1
    Email author
  • Mohammed Dahane
    • 1
  • Lyes Benyoucef
    • 2
  1. 1.LGIPM Research LaboratoryLorraine UniversityMetzFrance
  2. 2.LSIS-UMR 7296Aix-Marseille UniversityMarseilleFrance

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