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A dynamic modeling to measure lean performance within lean attributes

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Abstract

In today’s competitive world lean manufacturing has become an important “role model” for two groups: academics and practitioners. Many organizations around the world have attempted to implement it but the lack of a clear understanding of the main attributes to leanness, lean performance and its measurement contribute to the failure of lean practices. It therefore seems necessary to provide a way to evaluate the impact of lean attributes using an approach to determine the criteria and key factors of leanness. Although there are numerous theoretical and practical studies that address lean tools and techniques, few studies focus systematically on measuring the influence of lean attributes on leanness. To fill the current gap, this paper presents an innovative approach to measure the value of the influence of lean attributes on manufacturing systems by using fuzzy membership functions. A lean attributes score is finally calculated to give managers and decision makers a real insight into the leanness level and to further improve it by acting appropriately in the manufacturing system. The model is dynamic, flexible, feasible, and easy to follow and implement. It enables a systematic measurement of the influence of lean attributes by producing a final integrated unit score.

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References

  1. Womack JP, Jones, DT, Roos D (2007) The machine that changed the world: the story of lean production—Toyota’s secret weapon in the global car wars that is now revolutionizing world industry. Free Press, ISBN 978-0743299794

  2. Drew J, McCallum B, Roggenhofer S (2004) Journey to Lean—making operational change stick. Palgrave Macmillan

  3. Kulaka O, Durmusoglua MB, Tufekci S (2005) A complete cellular manufacturing system design methodology based on axiomatic design principles. Comput Ind Eng 48:765–787

    Article  Google Scholar 

  4. Anvari AR, Mojahed M, Zulkifli N, Yusuff RM, Ismail Y, Hojjati SMH (2011) A group AHP-based tool to evaluate effective factors toward leanness in automotive industries. J Appl Sci. doi:10.3923/jas.20ll

  5. Anvari AR, Zulkifli N, Yusuff RM, Ismail, Y, Hojjati SMH (2011) A proposed dynamic model for a lean roadmap, Afr J Bus Manag 5(16): 6727-6737, Available online at http://www.academicjournals.org/AJBM

  6. Yimer AD, Demirli K (2010) A genetic approach to two-phase optimization of dynamic supply chain scheduling. Comput Ind Eng 58:411–422

    Article  Google Scholar 

  7. Rubio S, Corominas A (2008) Optimal manufacturing–remanufacturing policies in a lean production environment. Comput Ind Eng 55:234–242

    Article  Google Scholar 

  8. Cuatrecasas-Arbos L, Fortuny-Santos J, Vintro-Sanchez C (2011) The operations-time chart: a graphical tool to evaluate the performance of production systems—from batch-and-queue to lean manufacturing. Comput Ind Eng 61:661–675

    Google Scholar 

  9. Wan H-D, Chen FF (2008) A leanness measure of manufacturing systems for quantifying impacts of lean initiatives. Int J Prod Res 46(23):6567–6584

    Article  Google Scholar 

  10. Jayram J, Vickery S, Droge C (2008) Relationship building, lean strategy and firm performance: an exploratory study in the automotive supplier industry. Int J Prod Res 46(20):5633–5649

    Article  Google Scholar 

  11. Anvari AR, Ismail Y, Hojjati SMH (2011) A study on total quality management and lean manufacturing: through lean thinking approach. World Appl Sci J 12(9):1585–1596

    Google Scholar 

  12. Comm CL, Mathaisel DFX (2000) A paradigm for benchmarking Lean initiatives for quality improvement. Benchmark Int J 7(2):118–127

    Article  Google Scholar 

  13. Mason-Jones R, Naylor B, Towill DR (2000) Engineering the leagile supply chain. Int J Agil Manag Syst 2(1):54–61

    Article  Google Scholar 

  14. Mason-Jones R, Naylor B, Towill DR (2000) Lean, agile or leagile? Matching your supply chain to the marketplace. Int J Prod Res 38(17):4061–4070

    Article  Google Scholar 

  15. Naim MM, Gosling J (2011) On leanness, agility and leagile supply chains. Int J Prod Econ 131(1):342–354

    Article  Google Scholar 

  16. McIvor R (2001) Lean supply: the design and cost reduction dimensions. Eur J Purch Supply Manag 7:227–242

    Article  Google Scholar 

  17. Soriano-Meier H, Forrester PL (2002) A model for evaluating the degree of leanness of manufacturing: firms. Int J Integr Manuf Syst 13:104–109

    Article  Google Scholar 

  18. Vinodh S, Balaji SR (2011) Fuzzy logic based leanness assessment and its decision support system. Int J Prod Res 49(13):4027–4041

    Article  Google Scholar 

  19. Vinodh S, Chintha SK (2011) Leanness assessment using multi-grade fuzzy approach. Int J Prod Res 49(2):431–445

    Article  Google Scholar 

  20. Vinodh S, Chintha SK (2011) Application of fuzzy QFD for enabling leanness in a manufacturing organisation. Int J Prod Res 49(6):1627–1644

    Article  Google Scholar 

  21. Vinodh S, Vimal KEK (2011) Thirty criteria based leanness assessment using fuzzy logic approach. Int J Adv Manuf Technol. doi:10.1007/s00170-011-3658-y

  22. Shah R, Ward PT (2007) Defining and developing measures of Lean production. J Oper Manag 25(4):21

    Google Scholar 

  23. Brintrupa A, Ranasingheb D, McFarlanea D (2010) RFID opportunity analysis for leaner manufacturing. Int J Prod Res 47(18):5237–5243

    Google Scholar 

  24. George ML (2003) Lean six sigma for service. McGraw-Hill, New York

    Google Scholar 

  25. Sun S (2011) The strategic role of lean production in SOE’s development. Int J Bus Manag 6(2):160–168

    Google Scholar 

  26. Allen J, Robinson C, Stewart D (2001) Lean manufacturing: a plant floor guide. SME, Dearborn

    Google Scholar 

  27. Seyedhosseini SM, Taleghani AE, Bakhsha A, Partovi S (2011) Extracting leanness criteria by employing the concept of balanced scorecard. Expert Syst Appl. doi:10.1016/j.eswa.2011.02.095

  28. Dennis P (2002) Lean production simplified: a plain language guide to the world’s most powerful production system. Productivity, New York

    Google Scholar 

  29. Wan H-D, Chen F (2007) Quantifying leanness and agility of manufacturing systems. Proceedings of the Conference on Industrial Engineering Research, Atlanta

    Google Scholar 

  30. Lee M-C, Chang T (2010) Developing a lean design for Six Sigma through supply chain methodology. Int J Product Qual Manag 6(4):407–434

    Article  Google Scholar 

  31. Brown S, Blackmon K, Cousins P, Maylor H (2001) Operations management Policy, practice and performance improvement, Oxford ISBN 0 7506 4995 X

  32. Slack RA (1999) “The lean value principle in military aerospace product development” The Lean Aerospace Initiative. Report Series, RP99-01-16

  33. Ferrari E, Pareschi A, Persona A, Regattieri A (2002) TPM: situations and procedures for a soft introduction in Italian factories. TQM Mag 14:350–359

    Article  Google Scholar 

  34. Vinas T (2004) Biotechnology—better than lean manufacturing and information technology. Ind Week 253:30–39

    Google Scholar 

  35. Vitasek K (2005) Supply chain and logistics terms and glossary. Supply Chain Visions, US

    Google Scholar 

  36. Naylor BJ, Naim MM, Berry D (1999) Leagility: integrating the Lean and agile manufacturing paradigms. Int J Prod Econ 62:107–118

    Article  Google Scholar 

  37. Chamberlain P, Snowden LR, Padgett C, Saldana L, Roles J, Holmes L, Ward H, Soper J, Reid J, Sverk J (2011) A strategy for assessing costs of implementing new practices in the child welfare system: adapting the English cost calculator in the United States. Adm Policy Ment Health 38:24–31

    Article  Google Scholar 

  38. Naderi B, Zandieh M, Fatemi-Ghomi SMT (2009) Scheduling job shop problems with sequence-dependent setup times. Int J Prod Res 47(21):5959–5976

    Article  MATH  Google Scholar 

  39. Wilson L (2010) How to implement lean manufacturing. Mc Graw Hill New York. ISBN: 978-0-07-162508-1

  40. Rivera L, Chen F (2007) Measuring the impact of Lean tools on the cost–time investment of a product using cost–time profiles. Robot Comput Integr Manuf 23(6):684–689. doi:10.1016/j.rcim.2007.02.013

    Article  Google Scholar 

  41. Bowen P, Cattell K, Jay I (2011) Value management in the South African manufacturing industry: exploratory findings. Manag Decis 49(1):6–28. doi:10.1108/00251741111094419

    Article  Google Scholar 

  42. Drummond MF, Stoddard GI, Torrance GW (1987) Methods for economic evaluation of health care programs. Oxford University Press, Oxford

    Google Scholar 

  43. Murugaiah U, Jebaraj SBM, Marathamuthu S, Muthaiyah S (2010) Scrap loss reduction using the 5-whys analysis. Int J Qual Reliab Manag 27(5):527–540

    Article  Google Scholar 

  44. Bicheno J (2004) The new lean toolbox: towards fast, flexible flow, 3rd edn. PICSIE, Buckingham

    Google Scholar 

  45. Hines P, Rich N (1997) The seven value stream mapping tools. Int J Oper Prod Manag 17(1):46–64

    Article  Google Scholar 

  46. Smith R, Hawkins B (2004) Lean maintenance: reduce costs, improve quality, and increase market share. Elsevier, New York

    Google Scholar 

  47. Smith RE (2011) Application of lean manufacturing tools in cash centers to improve operational efficiency, Magister Degree in Business Administration, Nelson Mandela Metropolitan University

  48. Taj S (2005) Applying lean assessment tools in Chinese hi-tech industries. Collage of Business Administration, University of Detroit Mercy, Detroit

    Google Scholar 

  49. Herron C, Braiden P (2006) A methodology for developing sustainable quantifiable productivity improvement in manufacturing companies. Int J Prod Econ Elsevier Publisher 104(1):143–153

    Article  Google Scholar 

  50. Crabill J, Harmon E, Meadows D, Milauskas R., Miller C, Nightingale D, Schwartz B, Shields T, Torrani B (2000) Production operations transition-to-Lean team. Description Manual, 1. Cambridge, MA, MIT, 5

  51. Yang SL, Li TF (2002) Agility evaluation of mass customization product manufacturing. J Mater Process Technol 129(1–3):640–644

    Article  Google Scholar 

  52. Beach R, Muhlemann AP, Price DHR, Paterson A, Sharp JA (2000) A review of manufacturing flexibility. Eur J Oper Res 122(1):41–57

    Article  MATH  Google Scholar 

  53. Delgado M, Verdegay JL, Vila V (1993) Linguistic decision making models. Int J Intell Syst 7(5):479–492

    Article  Google Scholar 

  54. Singh RK, Kumar S, Choudhuri AK, Tiwari MK (2006) Lean tool selection in a die casting unit: a fuzzy-based decision support heuristic. Int J Prod Res 44(7):1399–1429

    Article  Google Scholar 

  55. Zadeh L A (1965) Fuzzy sets. Information and Control 8(3): 338–353. doi:10.1016/S0019-9958(65)90241-X, 10.1016/S0019-9958(65)90241-X

  56. Zadeh LA (1983) Fuzzy logic as a basis for the management of uncertainly in expert systems. Fuzzy Set Syst 11:199–227

    Article  MathSciNet  MATH  Google Scholar 

  57. Bojadziev G, Bojadziev B (2007) “Fuzzy Logic for Business, Finance, and Management” 2nd ed., World Scientific Publishing Co. Pte. Ltd, 13: 15-19

  58. Lee J, Lee-Kwang H (2000) A method for ranking fuzzily fuzzy numbers. Proc Ninth IEEE Int Conf Fuzzy Syst 1:71–76

    Google Scholar 

  59. Matarazzo B, Munda G (2001) New approaches for the comparison of L–R fuzzy numbers: a theoretical and operational analysis. Fuzzy Set Syst 118:407–418

    Article  MathSciNet  MATH  Google Scholar 

  60. Yao JS, Lin FT (2000) Fuzzy critical path method based on signed distance ranking of fuzzy numbers. IEEE Trans Syst Man Cybern Syst Hum 30:76–82

    Article  Google Scholar 

  61. Yao JS, Wu K (2000) Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Set Syst 116:275–288

    Article  MathSciNet  MATH  Google Scholar 

  62. Abbasbandy S, Asady B (2006) Ranking of fuzzy numbers by sign distance. Inf Sci 176:2405–2416

    Article  MathSciNet  MATH  Google Scholar 

  63. Asady B, Zendehnam A (2007) Ranking fuzzy numbers by distance minimization, applied mathematical. Appl Math Model 31(11):2589–2598

    Article  MATH  Google Scholar 

  64. Tran L, Duckein L (2002) Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Set Syst 35:331–341

    Article  Google Scholar 

  65. Wang Z-X, Liu Y-J, Fan Z-P, Feng B (2009) Ranking L–R fuzzy number based on deviation degree. Inf Sci 179:2070–2077

    Article  MathSciNet  MATH  Google Scholar 

  66. Wang ML, Wang HF, Lung LC (2005) Ranking fuzzy number based on lexicographic screening procedure. Int J Inf Technol Decis Mak 4:663–678

    Article  Google Scholar 

  67. Li C (2011) A customised lean model for a Chinese Aerospace OEM (Original equipment manufacturer), Thesis (MS). Cranfield University School of Applied Sciences

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Correspondence to Alireza Anvari.

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Anvari, A., Zulkifli, N. & Yusuff, R.M. A dynamic modeling to measure lean performance within lean attributes. Int J Adv Manuf Technol 66, 663–677 (2013). https://doi.org/10.1007/s00170-012-4356-0

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