Skip to main content
SpringerLink
Log in

An integrated model of dynamic cellular manufacturing and supply chain system design

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In a global dynamic environment, there is a need to develop organizations and facilities significantly more flexible and responsive. This work proposes an integrated model of dynamic cellular manufacturing and supply chain design with consideration of various issues such as multi-plant locations, multiple markets, multi-time periods, reconfiguration, etc. The model objective was to minimize the sum of various costs such as facility/plant to market transportation cost, part holding cost at a facility/plant, part outsourcing cost, machine procurement cost, machine maintenance overhead cost, machine repair cost, production loss cost due to machine breakdown, machine operation cost, setup cost, tool consumption cost, inter-cell travel cost, intra-cell travel cost, and system reconfiguration cost for the entire planning time horizon. To study the model, three procedures—LINGO, artificial immune system, and hybrid artificial immune system—are used to perform computational experiment on some problems from existing literature. The best result generally is found by the hybrid artificial immune system algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ahkioon S, Bulgak AA, Bektas T (2009) Cellular manufacturing system design with routing flexibility, machine procurement, production planning & dynamic system reconfiguration. Int J Prod Res 47(6):1573–1600

    Article  MATH  Google Scholar 

  2. Akturk MS, Turkcan A (2000) Cellular manufacturing system design using a holonistic approach. Int J Prod Res 38:2327–2347

    Article  MATH  Google Scholar 

  3. Argoneto P, Bruccoleri M, Lo Nigro G, Perrone G, Noto La Diega S, Renna P (2008) Production planning in production networks. Springer, London

    Book  Google Scholar 

  4. Askin RG, Subramanian SP (1987) A cost-based heuristic for group technology configuration. Int J Prod Res 25:101–113

    Article  Google Scholar 

  5. Askin RG, Selim HM, Vakharia AJ (1997) A methodology for designing flexible cellular manufacturing systems. IIE Trans 29:599–610

    Google Scholar 

  6. Balakrishnan J, Cheng C (2007) Multi-period planning and uncertainty issues in cellular manufacturing: a review and future directions. Eur J Oper Res 177:281–309

    Article  MATH  Google Scholar 

  7. Balakrishnan J, Cheng CH (2005) Dynamic cellular manufacturing under multi period planning horizons. J Manuf Technol Manag 16:516–530

    Article  Google Scholar 

  8. Baykasoglu A, Gindy NNZ, Cobb RC (2001) Capability based formulation and solution of multiple objective cell formation problems using simulated annealing. Integr Manuf Syst 12:258–274

    Article  Google Scholar 

  9. Carrie AS (1973) Numerical taxonomy applied to group technology and plant layout. Int J Prod Res 11:399–416

    Article  Google Scholar 

  10. Chandra C, Janis G (2007) Supply chain configuration: concepts, solutions and applications. Springer Science+Business Media, LLC, New York

    Google Scholar 

  11. Defersha FM, Chen M (2006) Machine cell formation using a mathematical model and a genetic-algorithm-based heuristic. Int J Prod Res 44(12):2421–2444

    Article  MATH  Google Scholar 

  12. Defersha FM, Chen M (2008) A parallel multiple Markov chain simulated annealing for multi period manufacturing cell formation. Int J Adv Manuf Tech 37:140–156

    Article  Google Scholar 

  13. Heragu SS, Chen JR (1998) Optimal solution of cellular manufacturing system design: benders’ decomposition approach. Eur J Oper Res 107:175–192

    Article  MATH  Google Scholar 

  14. Jayaswal S, Adil G (2004) Efficient algorithm for cell formation with sequence data, machine replications and alternative process routings. Int J Prod Res 42:2419–2433

    Article  Google Scholar 

  15. Khoo LP, Situmdrang TD (2003) Solving the assembly configuration problem for modular products using an immune algorithm approach int. J Prod Res 41(15):3419–3434

    Article  MATH  Google Scholar 

  16. Koren Y (2009) Personalized production paradigm. Umic.edu. November

  17. Koren Y (2005) Beyond reconfigurable manufacturing system. CIRP 3rd International Conference on Reconfigurable Manufacturing, 2005. Ann Arbor, Michigan, 10–12 May

  18. Logendran R (1990) A workload based model for minimizing total intercell and intracell moves in cellular manufacturing. Int J Prod Res 28:913–925

    Article  Google Scholar 

  19. Lokesh K, Jain PK (2008) Part-machine group formation with operation sequence, time and production volume. Int J Simul Model 7(4):198–209

    Article  Google Scholar 

  20. Lokesh K, Jain PK (2009) Part-machine group formation with ordinal-ratio level data and production volume. Int J Simul Model 8(2):90–101

    Article  Google Scholar 

  21. Lokesh K, Jain PK (2010) Concurrently part-machine group formation with important production data. Int J Simul Model 9(1):5–16

    Article  Google Scholar 

  22. Lokesh K, Jain PK (2010) Dynamic cellular manufacturing systems design—a comprehensive model & HHGA. Adv Prod Eng Manag J 5(3):151–162

    Google Scholar 

  23. Lokesh K, Jain PK (2011) Dynamic cellular manufacturing systems design—a comprehensive model. Int J Adv Manuf Tech 53(1–4):14–34. doi:10.1007/s00170-010-2842-9

    Google Scholar 

  24. Manzini R, Gebennini E (2008) Optimization models for the dynamic facility location and allocation problem. Int J Prod Res 46(8):2061–2086

    Article  MATH  Google Scholar 

  25. Melo MT, Nickel S, Saldanha-da-Gama F (2009) Facility location and supply chain management—a review. Eur J Oper Res 196:401–412, 10.1016/j.ejor.2008.05.007

    Article  MathSciNet  MATH  Google Scholar 

  26. Mungwattana A (2000) Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility. PhD thesis, Virginia Polytechnic Institute and State University, Blackburg, VA

  27. Rao PP, Mohanty RP (2003) Impact of cellular manufacturing on supply chain management: exploration of interrelationships between design issues. Int J Manuf Technol Manag 5:507–520

    Google Scholar 

  28. Rheault M, Drolet J, Abdulnour G (1995) Physically reconfigurable virtual cells: a dynamic model for a highly dynamic environment. Comput Ind Eng 29(1–4):221–225

    Article  Google Scholar 

  29. Safaei N, Mehrabad SM, Ameli MSJ (2008) A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. Eur J Oper Res 185:563–592

    Article  MATH  Google Scholar 

  30. Sankaran S, Kasilingam RG (1993) On cell size and machine requirements planning in group technology systems. Eur J Oper Res 69:373–383

    Article  MATH  Google Scholar 

  31. Schaller J (2007) Designing & redesigning cellular manufacturing systems to handle demand changes. Comp Ind Eng 53:478–490

    Article  Google Scholar 

  32. Schaller J (2008) Incorporating cellular manufacturing into supply chain design. Int J Prod Res 46(17):4925–4945

    Article  MATH  Google Scholar 

  33. Seifoddini H (1989) Duplication process in machine cells formation in group technology. IIE Trans 21:382

    Article  Google Scholar 

  34. Srinivasan G, Narendran TT, Mahaderan B (1990) An assignment model for the part families problem in group technology. Int J Prod Res 28:145–152

    Article  Google Scholar 

  35. Stanfel LE (1985) Machine clustering for economic production. Eng Costs Prod Econ 9:73–81

    Article  Google Scholar 

  36. Su CT, Hsu CM (1998) Multi-objective machine-part cell formation through parallel simulated annealing. Int J Prod Res 36:2185–2207

    Article  MATH  Google Scholar 

  37. Tavakkoli-Moghaddam R, Aryanezhad MB, Safaei N, Azaron A (2005) Solving a dynamic cell formation problem using metaheuristics. Appl Math Comput 170:761–780

    Article  MathSciNet  MATH  Google Scholar 

  38. Tompkins JA, White JA, Bozer YA, Tanchoco JMA (2003) Facility planning. Wiley, New York

    Google Scholar 

  39. US National Research Council (1998) Visionary manufacturing challenges for 2020

  40. Vila D, Martel A, Beauregard R (2006) Designing logistics networks in divergent process industries: a methodology and its application to the lumber industry. Int J Prod Econ 102:358–378

    Article  Google Scholar 

  41. Wang X, Tang J, Yung KL (2008) Optimization of multi-objectives dynamic cell formation problem using a scatter search approach. Int J Adv Manuf Technol 44:318–329

    Article  Google Scholar 

  42. Wicks EM, Reasor RJ (1999) Designing cellular manufacturing systems with dynamic part populations. IIE Trans 31:11–20

    Google Scholar 

  43. Wiendahl HP, Lutz S (2002) Production networks. Ann CIRP 51(2):573–587

    Article  Google Scholar 

  44. Wu B (2004) Handbook of manufacturing and supply systems desig : from strategy formulation to system operation. Taylor & Francis e-Library

  45. Xambre AR, Vilarinho PM (2003) A simulated annealing approach for manufacturing cell formation with multiple identical machines. Eur J Oper Res 151:434–446

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, I.M.I., New, Delhi, India

    Lokesh Kumar Saxena

  2. Department of Mechanical & Industrial Engineering, I.I.T., Roorkee, India

    P. K. Jain

Authors
  1. Lokesh Kumar Saxena
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. K. Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lokesh Kumar Saxena.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Saxena, L.K., Jain, P.K. An integrated model of dynamic cellular manufacturing and supply chain system design. Int J Adv Manuf Technol 62, 385–404 (2012). https://doi.org/10.1007/s00170-011-3806-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-011-3806-4

Keywords

Search

Navigation