Skip to main content
SpringerLink
Log in

An effective methodology for cell formation and intra-cell machine layout design in cellular manufacturing system using parts visit data and operation sequence data

  • Technical Paper
  • Published:
Journal of the Brazilian Society of Mechanical Sciences and Engineering Aims and scope Submit manuscript

Abstract

Cellular manufacturing is an efficient approach for implementing the principles of Group Technology in a manufacturing environment. Most of the previous studies in CMS have focused mainly on cell formation problem. However, only few researches have discussed on CFP and CLP, simultaneously. In this paper, we present a new heuristic approach based on modified flow matrix which simultaneously considers cell formation, intracellular machine layout, exceptional elements and voids issues in the CMS design using sequence data and number of parts visit data between the machines. Above-mentioned data provide valuable information about the various jobs in a manufacturing system. The objective of our proposed approach is to group similar parts and corresponding different machines in same cells and additionally considering the sequence of machines, exceptional elements and voids.   Moreover, our proposed approach considers inter-cell movement, backward movements, number of voids and number of operations. A new performance measure modified group technology efficacy is proposed for evaluating the performance of the proposed methodology. Two well-known benchmark problems from the literature are considered and results are compared with the existing methods. The results clearly demonstrated that our proposed approach outperforms the previously proposed methods.

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

Abbreviations

P :

Index for parts (p = 1,2,…,P)

i :

Index for machines (i = 1,2,…,M)

k :

Index for cells (k = 1,2,…,C)

S = \([S_{ip} ]\) :

Represent the machine–part incidence matrix using sequence data

\(S_{ip}\) :

The sequence of pth part in ith machine, =0 if the part does not need the machine, >0, and an ordinal number representing the location in the complete sequence

\(P_{k}\) :

Number of parts in cell k

\(M_{k}\) :

Number of machines in cell k

\(V_{k}\) :

Number of voids in cell k

\(N_{\text{op}}\) :

Total number of operations in the system

\(N_{t}\) :

Total number of possible intercellular movements

\(N_{\text{opc}}\) :

Total number of operations within the cells

P :

Number of parts

References

  1. Mcauley J (1972) Machine grouping for efficient production. Prod Eng 51:53–57

    Article  Google Scholar 

  2. Seiffodini H (1989) Single linkage V/S average linkage clustering in machine cells formation applications. Comput Ind Eng 16:419–426

    Article  Google Scholar 

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

    Article  Google Scholar 

  4. Waghodekar PH, Sahu S (1984) Machine-component cell formation in group technology MACE. Int J Prod Res 22:937–948

    Article  Google Scholar 

  5. Chandrasekharan MP, Rajagopalan R (1987) ZODIAC-an algorithm for concurrent formation of part-families and machine-cells. Int J Prod Res 25:835–850

    Article  MATH  Google Scholar 

  6. Srinivasan G, Narendran TT (1991) GRAFICS-a non-hierarchical clustering algorithm for group technology. Int J Prod Res 29:463–478

    Article  Google Scholar 

  7. Kusiak A (1987) The generalised group technology concept. Int J Prod Res 25:561–569

    Article  Google Scholar 

  8. Mahdavi I, Javadi B, Fallah-alipour K, Slomp J (2007) Designing a new mathematical model for cellular manufacturing system based on cell utilization. Appl Math Comput 190:662–670

    Article  MathSciNet  MATH  Google Scholar 

  9. Srinivasan G, Narendran TT, Mahedevan M (1990) An assignment model for the part-families problem in group technology. Int J Prod Res 29:463–478

    Article  Google Scholar 

  10. Viswanathan (1995) Configuring cellular manufacturing systems: a quadratic integer programming and a simple interchange heuristic. Int J Prod Res 33:361–376

    Article  MATH  Google Scholar 

  11. Burbidge JL (1977) A manual method for production flow analysis. Prod Eng 56:34–38

    Article  Google Scholar 

  12. Burbidge JL (1989) Production flow analysis. Clarendon Press, Oxford

    Google Scholar 

  13. Gonçalves JF, Resende MGC (2004) An evolutionary algorithm for manufacturing cell formation. Comput Ind Eng 47:247–273

    Article  Google Scholar 

  14. James TL, Brown EC, Keeling KB (2007) A hybrid grouping genetic algorithm for the cell formation problem. Comput Oper Res 34:2059–2079

    Article  MATH  Google Scholar 

  15. Nair GJ, Narendran TT (1998) CASE: a clustering algorithm for cell formation with sequence data. Int J Prod Res 36:157–179

    Article  MATH  Google Scholar 

  16. Mahdavi I, Mahadevan B (2008) CLASS: an algorithm for cellular manufacturing system and layout design using sequence data. Robot Comput Integr Manuf 24:488–497

    Article  Google Scholar 

  17. Vakharia AJ, Wemmerlov U (1990) Designing a cellular manufacturing system: a materials flow approach based on operations sequences. IIE Trans 22:84–97

    Article  Google Scholar 

  18. Selvam RP, Balasubramanian KN (1985) Algorithmic grouping of operation sequences. Eng Costs Prod Econ 9:125–134

    Article  Google Scholar 

  19. Tam KY (1988) An operation sequence based similarity coefficient for part family formations. J Manuf Syst 9:55–68

    Article  Google Scholar 

  20. Choobineh F (1988) A framework for the design of cellular manufacturing systems. Int J Prod Res 26:1161–1172

    Article  Google Scholar 

  21. Sarker BR, Xu Y (1998) Operation sequences-based cell formation methods: a critical survey. Prod Plan Control 9:771–783

    Article  Google Scholar 

  22. Boulif M, Atif K (2006) A new branch-&-bound-enhanced genetic algorithm for the manufacturing cell formation problem. Comput Oper Res 33:2219–2245

    Article  MATH  Google Scholar 

  23. Liao TW (1994) Design of line-type cellular manufacturing systems for minimum operating and material-handling costs. Int J Prod Res 32:387–397

    Article  MATH  Google Scholar 

  24. Heragu SS, Kakuturi SR (1997) Grouping and placement of machine cells. IIE Trans 29:561–571

    Google Scholar 

  25. Lee S-D, Chiang C-P (2001) A cut-tree-based approach for clustering machine cells in the bidirectional linear flow layout. Int J Prod Res 39:3491–3512

    Article  Google Scholar 

  26. Chiang C-P, Lee S-D (2004) A genetic-based algorithm with the optimal partition approach for the cell formation in bi-directional linear flow layout. Comput Integr Manuf 17:346–375

    Google Scholar 

  27. Houshyar A, McGinnis LF (1990) A heuristic for assigning facilities to locations to minimize WIP travel distance in a linear facility. Int J Prod Res 28:1485–1498

    Article  Google Scholar 

  28. Afentakis P (1989) A loop layout design problem for flexible manufacturing systems. Int J Flex Manuf Syst 1:175–196

    Article  Google Scholar 

  29. Kim CO, Baek JG, Baek JK (2004) A two-phase heuristic algorithm for cell formation problems considering alternative part routes and machine sequence. Int J Prod Res 42:3911–3927

    Article  MATH  Google Scholar 

  30. Yin Y, Yasuda K (2004) Reconsidering generalized similarity coefficient via a sequence ratio. Int J Ind Eng Theory Appl Pract 11:140–150

    Google Scholar 

  31. Yin Y, Yasuda K, Hu L (2005) Formation of manufacturing cells based on material flows. Int J Adv Manuf Technol 27:159–165

    Article  Google Scholar 

  32. 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 

  33. Hu GH, Chen YP, Zhou ZD, Fang HC (2007) A genetic algorithm for the inter-cell layout and material handling system design. Int J Adv Manuf Technol 34:1153–1163

    Article  Google Scholar 

  34. Nouri H, Tang SH, Hang TBT, Anuar MK (2010) BASE: a bacteria foraging algorithm for cell formation with sequence data. J Manuf Syst 29:102–110

    Article  Google Scholar 

  35. Mahdavi I, Shirazi B, Mahdi Paydar M (2008) A flow matrix-based heuristic algorithm for cell formation and layout design in cellular manufacturing system. International J Adv Manuf Technol 39: 943–53

  36. Ahi A, Aryanezhad MB, Ashtiani B, Makui A (2009) A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method. Comput Oper Res 36(5):1478–1496

    Article  MATH  Google Scholar 

  37. Wu X, Chu CH, Wang Y, Yan W (2007) A genetic algorithm for cellular manufacturing design and layout. Eur J Oper Res 181:156–167

    Article  MATH  Google Scholar 

  38. Wu X, Chu CH, Wang Y, Yue D (2007) Genetic algorithms for integrating cell formation with machine layout and scheduling. Comput Ind Eng 53:227–289

    Google Scholar 

  39. Wu T-H, Chung S-H, Chang C-C (2009) Hybrid simulated annealing algorithm with mutation operator to the cell formation problem with alternative process routings. Exp Syst Appl 36(2):3652–3661

    Article  Google Scholar 

  40. Chan FTS, Lau KW, Chan LY, Choy KL (2006) Two-stage approach for machine-part grouping and cell layout problems. Robot Comput Integr Manuf 22: 217–238

  41. Chan FTS, Lau KW, Chan LY, Lo VHY (2008) Cell formation problemwith consideration of both intracellular and intercellular movements. Int J Prod Res 46(10):2589–2620

    Article  MATH  Google Scholar 

  42. Fariborz J, Tavakkoli-Moghaddam R, Golmohammadi A, Javadi B (2012) An Electromagnetism-like algorithm for cell formation and layout problem. Exp Syst Appl 39: 2172–2182

  43. Chang C-C, Wub T-H, Wu C-W (2013) An efficient approach to determine cell formation, cell layout and intracellular machine sequence in cellular manufacturing systems. Comput Ind Eng 66: 438–450

  44. Mahdavi I, Teymourian E, Baher NT, Kayvanfar V (2013) An integrated model for solving cell formation and cell layout problem simultaneously considering new situations. J Manuf Syst 32: 655–663

  45. Lee K, Ahn K-I (2013) GT efficacy: a performance measure for cell formation with sequence data. Int J Prod Res 51(20):6070–6081

    Article  Google Scholar 

  46. Aneke NAG, Carrie AS (1986) A design technique for the layout of multiproduct flow lines. Int J Prod Res 24:471–481

    Article  Google Scholar 

  47. Abue-zeid, Buseif IM, Zaidi GMEL (2006) Sequence and cost considerations of materials flow in the design of cellular manufacturing systems. In: 7th Asia pacific industrial engineering and management systems conference

  48. Kumar CS, Chandrasekharan MP (1990) Grouping efficacy: a quantitative criterion for goodness of block diagonal forms of binary matrices in group technology. Int J Prod Res 28:233–243

    Article  Google Scholar 

  49. Harhalakis G, Nagi R, Proth JM (1990) An efficient heuristic in manufacturing cell formation for group technology applications. Int J Prod Res 28:185–198

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, PSNA College of Engineering and Technology, Dindigul, 624622, India

    S. Raja

  2. Department of Mechanical Engineering, Velammal College of Engineering and Technology, Madurai, 625009, India

    V. Anbumalar

Authors
  1. S. Raja
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Anbumalar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Raja.

Additional information

Technical Editor: Fernando Antonio Forcellini.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raja, S., Anbumalar, V. An effective methodology for cell formation and intra-cell machine layout design in cellular manufacturing system using parts visit data and operation sequence data. J Braz. Soc. Mech. Sci. Eng. 38, 869–882 (2016). https://doi.org/10.1007/s40430-014-0280-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40430-014-0280-6

Keywords

Search

Navigation