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Literature review of JIT-KANBAN system

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Abstract

In this paper, JIT (Just-In-Time)-KANBAN literature survey was carried out and presented. The introductory section deals with the philosophy of JIT, and the concept involved in the push and pull system. The blocking mechanisms in the kanban system are also discussed elaborately. Besides these sections, the importance of measure of performance (MOP) and the application of the same with respect to JIT-KANBAN are presented. The recent trends in the JIT-KANBAN are discussed under the heading “Special cases”. In this review, 100 state-of-art research papers have been surveyed. The directions for the future works are also presented.

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References

  1. Alabas C, Altiparmak F, Dengiz B (2002) A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans. J Oper Res Soc 53(8):907

    Article  MATH  Google Scholar 

  2. Petroni A, Rizzi A (2002) A Fuzzy logic based methodology to rank shop floor dispatching rules. Int J Prod Econ 76:99–108

    Article  Google Scholar 

  3. Bitran GR, Chang (1987) A mathematical programming approach to a deterministic Kanban system. Manage Sci 33:427–441

    MATH  Google Scholar 

  4. Blair, Berkley J (1992) A review of the kanban production control research literature. Prod Oper Manag 1:393–411

    Google Scholar 

  5. Brown KA, Mitchell TR (1991) A comparison of just in time and batch manufacturing the role of performance obstacles. Acad Manage J 34(4):906–917

    Article  Google Scholar 

  6. Chan FTS (2001) Effect of kanban size on just in time manufacturing system. Journal of Material Processing Technology 116:146–160

    Article  Google Scholar 

  7. Chaturvedi M, Golher DY (1992) Simulation modeling and analysis of JIT production system. Prod Plan Control 3(1):81–92

    Google Scholar 

  8. Christelle D, Yannick F, Lee H-S (2000) Performance evaluation and design of CONWIP system with inspection. Int J Prod Econ 64:219–229

    Article  Google Scholar 

  9. Panayiotou C G, Cassandras C G (1999) Optimization of kanban - based manufacturing systems. Automatica 35c:1521–1533

    Article  MathSciNet  Google Scholar 

  10. Co Henry C, Sharafali, Moosa (1997) Overlapping factor in Toyota's formula for computing the number of kanbans. IIE Trans 29(5):409–415

    Article  Google Scholar 

  11. Cook R L, Robert A (1996) Applying JIT principles to continuous process manufacturing supply chains. Prod Invent Manage J 37(1):12–17

    Google Scholar 

  12. Golhar Damodar Y, Stamm C L (1991) The just in time philosophy: a literature review. International J Prod Res 29(4):657–676

    Google Scholar 

  13. Davis WJ, Stubitz SJ (1987) Configuring a Kanban system using discrete optimization of multiple stochastic responses. Int J Prod Res 25:721–740

    Google Scholar 

  14. Deleersnyder JL, Hodgson TJ, Muller Malek H, O’Grady PJ (1989) Kanban controlled pull system an analytic approach. Manage Sci 35:1079–1091

    Google Scholar 

  15. Di Mascolo et al (1996) An analytical method for performance evaluation of kanban controlled production systems. Oper Res 44(1):50–64

    MATH  Google Scholar 

  16. Drexl et al (2001) Sequencing JIT mixed-model assembly lines under station-load and part-usage constraints. Manage Sci 47(3):480

    Article  Google Scholar 

  17. Hay E J (1988) The just in time break through. John Wiley & sons, New York

    Google Scholar 

  18. Vergara EF, Moutaz K, Zhigniew M (2002) An evolutionary algorithm for optimizing material flow in supply chain. Comput Ind Eng 43:407–421

    Article  Google Scholar 

  19. Gabrial T, Bicheno J, Galletly JE (1991) JIT manufacturing simulation. Industrial Management & Data system 91:4

    Google Scholar 

  20. Gravel M, Prince W (1988) Using the Kanban in a job shop environment. Int J Prod Res 26(6):1105–1118

    Google Scholar 

  21. Hemamalini B, Rajendran C (2000) Determination of the number of containers, production kanbans and withdrawal kanbans; and scheduling in kanban flowshop- Part I. Int J Prod Res 38(11):2529–2548

    Article  MATH  Google Scholar 

  22. Hemamalini B, Rajendran C (2000) Determination of the number of containers, production kanbans and withdrawal kanbans; and scheduling in kanban flowshop- Part II. Int J Prod Res 38(11):2549–2572

    Article  MATH  Google Scholar 

  23. Huang P (1991) World class manufacturing in 1990s integrating JIT,TQC,FA, and TPM with worker participation, modern production concept theory and application. Springer, Berlin Heidelberg New York 491–507

    Google Scholar 

  24. Huang PY, Rees LP, Taylor BW (1983) A simulation analysis of Japanese Just In Time technique with Kanban for multi line multi stage production system. Decis Sci 14:326–344

    Google Scholar 

  25. Wang H, Wang H-P(Ben) (1999) Optimum number of kanban between two adjacent workstations in JIT system. Int J Prod Econ 22:179–188

    Article  Google Scholar 

  26. Hurrion RD (1997) An example of simulation optimization using a neural network metamodel: finding the optimum number of kanbans in a manufacturing system. J Oper Res Soc 48(11):1105–1112

    Article  MATH  Google Scholar 

  27. Imai M (1988) Will America corporate theme song be Just In Time ? J Qual Partic 21(2):26–28

    Google Scholar 

  28. Markham Ina S et al (1998) A rule induction approach for determining the number of kanbans in a Just in Time production system. Comput Ind Eng 34(4):717–727

    Article  Google Scholar 

  29. Israd David, Mosh Eben C (2003) How for should JIT vendor buyer relationship go? Int J Prod Econ 81:361–368

    Article  Google Scholar 

  30. Greene James H (1987) Production and inventory control hand book - American production & Inventory control society, Mc Graw Hill Book Company

  31. Jing-wen-Li (2003) Improving the performance of Job shop manufacturing with demand-pull production control by reducing setup/processing time variability. Int J Prod Econ 84:255–270

    Article  Google Scholar 

  32. Kakuro A (2002) New JIT A new management technology principle at Toyota. Int J Prod Econ 80:135–144

    Article  Google Scholar 

  33. Karmarker and Kekre (1989) Batching policy in kanban system. J Manuf Syst 8:317–328

    Article  Google Scholar 

  34. Kern et al (1996) Master production rescheduling policy in capacity-constrained just- in-time make-to-stock environments. Decis Sci 27(2):365–387

    Google Scholar 

  35. Khan, Lutfar R, Sarker R A (2002) An optimal batch size for a JIT manufacturing system. Comput Ind Eng 42(2–4):127

    Article  Google Scholar 

  36. Kimura O, Terade H (1981) Design and analysis of pull system a method of multistage production control. Int J Prod Res 19:241–253

    Google Scholar 

  37. Cua K O, Kathleen E, Mekone, Schroeder R G (2001) Relationship between implementation of TQM, JIT and TPM and manufacturing performance. J Oper Manag 19:675–694

    Article  Google Scholar 

  38. Krieg G, Kuhn H (2002) A decomposition method for multi product kanban systems with setup times and lost sales. IIE Trans 34(7):613

    Article  Google Scholar 

  39. Kulwiec R A (1997) The down side of JIT. Mod Mat Handl 52(10):3

    Google Scholar 

  40. Kutc S (1997) Optimal buffer allocation strategy for minimizing work in processinventory in un paced production lines. IIE Trans 29:81–88

    Google Scholar 

  41. Lai CL, Lee WB, W.H.Ip (2003) A study of system dynamics in Just in Time logistics. Journal of Material Processing Technology 138:265–269

    Article  Google Scholar 

  42. Lee CY Lin, Uzosoy CS, Wong R (1994) K., Implementation of demand pull system in a job shop environment. Int J Prod Res 32(11):2915–2927

    MATH  Google Scholar 

  43. Leyuan S, Shulimen (2003) Optimal buffer allocation in production lines. IIE Trans 35:1–10

    Article  Google Scholar 

  44. Lambrecht M, Segaert A (1990) Buffer stock allocation in serial and Assembly type of production line. Int J Oper Prod Manage 10:2

    Google Scholar 

  45. Markey M (1996) Examining a kanban material acquisition system. Ind Manage 38(3):22–26

    Google Scholar 

  46. Mason P A (1999) MRP II and kanban formula. Logist Focus 7:19–23

    Google Scholar 

  47. Kalchschmidt M, Giuliozotheri, Verganti R (2003) Inventory management in a multi echelon spare parts supply chain. Int J Prod Econ 81 & 82:397–413

    Article  Google Scholar 

  48. Mehmet S, Adbullah-Al-Jawini (1995) Simulation analysis of Just in Time production system. Int J Prod Econ 42:67–78

    Article  Google Scholar 

  49. Mohanasundaram KM, Natarajan K, Viswanathkumar, Radhakrishnan P, Rajendran C (2002) Scheduling rules for dynamic shop that manufacture multi-level jobs. Comput Ind Eng 44:119–131

    Article  Google Scholar 

  50. Monden Y (1983) Toyota production system. Ind Eng Manage press, - Atlanta

  51. Adam N R, Will J, Bertrand M, Surkis J (1987) Priority assignment procedure in multi level assembly jobshops. IIE Trans 19(3):317–328

    Google Scholar 

  52. Nori VS, Sarker BR (1998) Optimum number of kanbans between two adjacent stations. Prod Plan Control 9:60–65

    Article  Google Scholar 

  53. Ohno K, Nakashima K, Kojima M (1995) Optimal number of two kinds of Kanbans in a JIT production system. Int J Prod Res 33:1387–1401

    MATH  Google Scholar 

  54. Ohno T (1988) Toyota production system beyond large scale production. Productivity Press, Cambridge

    Google Scholar 

  55. Ovalle O R, Marquez A C (2003) Exploring the utilization of CONWIP system for supply chain management. A comparison with fully integrated supply chain. Int J Prod Econ 83:195–215

    Article  Google Scholar 

  56. Panneerselvam R (1999) Production and operation management. Prentice Hall of India, New Delhi

    Google Scholar 

  57. Patrick R, Mc Mullen, Frazier G V (2000) A simulated annealing approach to mixed model sequencing with multiple objectives on Just in Time line. IIE Trans 32:679–686

    Article  Google Scholar 

  58. Brucker P, Heitmann S, Huricnk J (2003) Flow-Shop problems with intermediate buffers. OR-Spectrum 25:549–574

    Article  MATH  Google Scholar 

  59. Philipoom et al (1987) An investigation of the factor influencing the number of kanbans required in implementation of the JIT technique with Kanbans. Int J Prod Res 25(3):457–472

    Google Scholar 

  60. Philipoom PR, Rees LP, Taylor BW, Huang (1987) Dynamically adjusting the number of kanban system in JIT production system using estimated values of lead time. IIE Trans 19(2):199–207

    Google Scholar 

  61. Rajendran C (1999) Formations and heuristics for scheduling in kanban flow shop to minimize the sum of weighted flowtime,weighted tardiness and weighted earliness of containers. Int J Prod Res 37(5):1137–1158

    Article  MATH  MathSciNet  Google Scholar 

  62. Richard J, Tersine (1994) Principle of inventory and materials management. PTR Prentice hall Englood cliffs, New Jersey

    Google Scholar 

  63. Schonberger R (1987) World Class Manufacturing case Book implementing JIT & TQC. The Free Press, New York

    Google Scholar 

  64. Rosemary et al (2001) The production performance benefits from JIT implementation. J Oper Manage 19:81–96

    Article  Google Scholar 

  65. Rosemary R, Fullerton, Cheryl S, Mc Watters, Fawson C (2003) An examination of the relationship between JIT and financial performance. J Oper Manage 20:383–404

    Google Scholar 

  66. Bowden RO, Hall J D, Usher J M (1996) Integration of evolutionary programming and simulation to optimize a pull production system. Comput Ind Eng 31(1&2):217–220

    Article  Google Scholar 

  67. De Smet R, Ludo G (1998) Using simulation to evaluate the introduction of a kanban sub system within an MRP-Controlled manufacturing environment. Int J Prod Econ 56 & 57:111–122

    Article  Google Scholar 

  68. Salameh MK, Ghattas RE (2001) Optimal Just in Time buffer inventory for regular preventive maintenance. Int J Prod Econ 74:157–161

    Article  Google Scholar 

  69. Ryan S M, Choobineh F (2003) Total WIP and WIP mix for a CONWIP controlled jobshop. IIE Trans 35:405–418

    Article  Google Scholar 

  70. Ryan SM, Bruno B, Choobineh F F (2000) Determining inventory levels in CONWIP controlled jobshop. IIE Trans 32:105–114

    Article  Google Scholar 

  71. Sarker B R, Balan Chidambaram V (1996) Operations planning for kanbans between two adjacent workstations. Comput Ind Eng 31(1&2):221–224

    Article  Google Scholar 

  72. Sarker Bhaba, Balan Chidambaram V (1999) Operations planning for a multi-stage kanban system. Eur J Oper Res 112(2):284–303

    Article  MATH  Google Scholar 

  73. Seki Y, Hoshino N (1999) Transient behavior of a single-stage kanban system based on the queuing model. Int J Prod Econ 60 & 61:369–374

    Article  Google Scholar 

  74. Shahabudeen P, Krishnaiah K (1999) Design of a Bi-Criteria kanban system using Genetic Algorithm. Int J Manage syst 15(3):257–274

    Google Scholar 

  75. Shahabudeen P, Gopinath R, Krishnaiah K (2002) Design of bi-criteria kanban system using simulated annealing technique. Comput Ind Eng 41(4):355

    Article  Google Scholar 

  76. Shahabudeen P, Krishniah K, Thulasinarayanan (2003) Design of two card dynamic kanban system using a simulated annealing algorithm. International Journal Advanced Manufacturing Technology 21:754–759

    Article  Google Scholar 

  77. Sharadapriyadarshini, Rajendran C (1997) Scheduling in kanban-controlled flow shop with dual blocking mechanisms and missing operations for part types. Int J Prod Res 35(11):3133–3156

    Article  MATH  Google Scholar 

  78. Sharadapriyadarshini, Rajendran C (1997) Heuristics for scheduling in kanban system with dual blocking mechanisms. Eur J Oper Res 103:439–452

    Article  MATH  Google Scholar 

  79. Spearman ML, Woodruff DT, Hopp WJ (1990) CONWIP a pull alternative to Kanban. Int J Prod Res 28:879–894

    Google Scholar 

  80. Stefan Minner (2003) Multiple supplier-inventory model in supply chain management: a review. Int J Prod Econ 81&82:265–279

    Google Scholar 

  81. Stockton DJ, Lindley RJ (1995) Implementing kanban with high variety / load volume manufacturing environment. Int J Oper Prod Manage 15(7):47–59

    Article  Google Scholar 

  82. Sugimori Y et al (1977) Toyota production system and kanban system - materialization of just in time and respect for human system. Int J Prod Res 15(6):553–564

    Google Scholar 

  83. Swanson C A, Lankford W M (1998) Just In Time manufacturing. Bus Process Manag J 4(4):333

    Article  Google Scholar 

  84. Takashashi K, Nakamura N (2002) Decentralized reactive kanban system. Eur J Oper Res 139(2):262

    Article  Google Scholar 

  85. Tardif V, Maaseidvaag L (2001) An adaptive approach to controlling kanban systems. Eur J Oper Res 132(2):411

    Article  MATH  MathSciNet  Google Scholar 

  86. Tayfur A, Goang A S (2000) Pull type manufacturing system with multiple product types. IIE Trans 32:115–124

    Article  Google Scholar 

  87. Turbo days (N) Time since Jan 12 (1996) http://www/geocities.com/timesquare/1848/japan21.html

  88. Uday S, Karmarkar (1987) Lot-sizing and sequencing delays. Manage Sci 33:419–423

    Article  MATH  Google Scholar 

  89. Dudek Villeda R, Smith RML (1988) Increasing the production rate of just in time production system with variable operation times. Int J Prod Res 26(11):1747–1768

    Google Scholar 

  90. Vito A, Dassisti M, Okogbaa G O (1995) Approximation approach for performance analysis production lines under a kanban discipline. Int J Prod Econ 40:197–207

    Article  Google Scholar 

  91. Womack JP et al (1991) The machine that change the world - the story of lean production. Rawson /Harper perennial, New York

    Google Scholar 

  92. Womack JP, Jones DT (1994) From the lean production to lean enterprise. Harward Business Review 93–103

  93. Woolsey R ED, Bowden R O, Hall J D, Hadley W H (1999) Closed-form solution to kanban sizing problem. Prod Invent Manage J 40(1):1–3

    Google Scholar 

  94. Xiaobo Z, Ohno K (1997) Algorithms for sequencing mixed models on an assembly line in a JIT Production system. Comput Ind Eng 32(1):47–56

    Article  Google Scholar 

  95. Herer Yale T, Levishalom (2000) The Kanban Assignment problem- a non integral approach. Eur J Oper Res 120:260–276

    Article  MATH  Google Scholar 

  96. Yang (2000) Managing a flow line with single-Kanban, dual-Kanban or Conwip. Prod Oper Manage 9:349

    Google Scholar 

  97. Yannick F, Maria D, Yves D (1995) On the design as generalized kanban control system. Int J Oper Prod Manage 15:9

    Article  Google Scholar 

  98. Yavuz IH, Satir A (1995) A kanban based simulation study of a mixed model just in time manufacture line. Int J Prod Res 33(4):1027–1048

    MATH  Google Scholar 

  99. Yoichi S, Naoto H (1999) Transient behavior of single stage kanban system based on the queuing model. Int J Prod Econ 60 & 61:369–374

    Google Scholar 

  100. Yves D, Liberopoulos G (2000) Extended kanban control system: combining kanban and base stock. IIE Trans 32:369–386

    Article  Google Scholar 

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Acknowledgement

The authors thank the unanimous referees for their constructive criticisms, which helped them to improve the content and presentation of this review paper.

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  1. Neyveli Lignite Corporation, Neyveli, India

    C. Sendil Kumar

  2. Department of Management Studies, School of Management, Pondicherry University, Pondicherry 605 014, India

    R. Panneerselvam

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Correspondence to R. Panneerselvam.

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Sendil Kumar, C., Panneerselvam, R. Literature review of JIT-KANBAN system. Int J Adv Manuf Technol 32, 393–408 (2007). https://doi.org/10.1007/s00170-005-0340-2

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