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Token-based pull production control systems: an introductory overview

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Abstract

Since the advent of Kanban, pull systems have been widely used in practice and have been widely studied by researchers. During the last decades, several types of pull systems have emerged. Numerous articles have been published to introduce new paradigms or new principles for just-in-time systems as well as new approaches to evaluate them or to optimize their performance. An important feature of these systems, which is common to many other production control systems, is the use of tokens, which usually consist of cards that authorize certain production tasks to be performed. Tokens can be used in various manners to control production and can be combined with several other mechanisms with the objective of reducing the work in progress and the lead times, while meeting customers’ demand. This article proposes an introductory overview of existing research works in this area. In this respect, we suggest a classification of pull-inspired production control systems, which allows us to distinguish up to 18 different systems. For each type of system, we study its basic principles, the flow control strategy, and the parameters affecting its performance. This survey aims at facilitating the understanding of the different proposals made by researchers and highlighting their common points and differences.

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References

  • Akturk M. S., Erhun F. (1999) An overview of design and operational issues of kanban systems. International Journal of Production Research 37(17): 3859–3881

    Article  Google Scholar 

  • Alfieri, A., & Matta, A. (2010). Mathematical programming representation of pull controlled single-product serial manufacturing systems. Journal of Intelligent Manufacturing. Published online (January 2010). doi:10.1007/s10845-009-0371-x.

  • Al-Tahat M. D., Mukattash A. M. (2006) Design and analysis of production control scheme for Kanban-based JIT environment. Journal of the Franklin Institute. Modeling, Simulation and Applied Optimization 343(4–5): 521–531

    Google Scholar 

  • Bechte, W. (1984). Steuerung der Durchlaufzeit durch belastungsorientierte Auftragsfreigabe bei Werkstattfertigung. Forschrittberichte VDI-Z, Reihe 2, Nr. 70 (VDI-Verlag).

  • Berkley B. J. (1992) A review of the kanban production control research literature. Production and Operations Management 1(4): 393–411

    Article  Google Scholar 

  • Bonney M. C., Zhang Z., Head M. A., Tien C. C., Barson R. J. (1999) Are push and pull systems really so different?. International Journal of Production Economics 59(1–3): 53–64

    Article  Google Scholar 

  • Bonvik A. M., Couch C. E., Gershwin S. B. (1997) A comparison of production-line control mechanisms. International Journal of Production Research 25(3): 789–804

    Article  Google Scholar 

  • Buzacott J. A. (1989) Queueing models of kanban and MRP controlled production systems. Engineering Cost and Production Economics 17: 3–20

    Article  Google Scholar 

  • Buzacott J. A., Shanthikumar J. G. (1992) General approach for coordinating production in multiple-cell manufacturing systems. Production and Operations Management 1(1): 34–52

    Article  Google Scholar 

  • Buzacott J. A., Shanthikumar J. G. (1993) Stochastic models of manufacturing systems. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  • Chang T. M., Yih Y. (1994) Generic Kanban systems for dynamic environments. International Journal of Production Research 32: 889–902

    Article  Google Scholar 

  • Chryssolouris G. (2006) Manufacturing systems: Theory and practice. Springer, New York

    Google Scholar 

  • Cochran J. K., Kaylani H. A. (2008) Optimal design of a hybrid push/pull serial manufacturing system with multiple part types. International Journal of Production Research 46(4): 949–965

    Article  Google Scholar 

  • Cochran J. K., Kim S.-S. (1998) Optimum junction point location and inventory levels in serial hybrid push/pull production systems. International Journal of Production Research 36(4): 1141–1155

    Article  Google Scholar 

  • Dallery Y., Liberopoulos G. (2000) Extended Kanban control system: Combining Kanban and base stock. IIE Transactions 32(4): 369–386

    Google Scholar 

  • Deleersnyder J. L., Hodgson T. J., King R. E., O’Grady P. J., Savva A. (1992) Integrating Kanban type pull systems and MRP type push systems: Insights from a Markovian model. IEE Transactions 24(3): 43–56

    Article  Google Scholar 

  • Duri C., Frein Y., Di Mascolo M. (2000a) Performance evaluation and design of base stock systems. European Journal of Operational Research 127(1): 172–188

    Article  Google Scholar 

  • Duri C., Frein Y., Lee H.-S. (2000b) Performance evaluation and design of a CONWIP system with inspections. International Journal of Production Economics 64(1–3): 219–229

    Article  Google Scholar 

  • Fernandes N. O., Carmo-Silva S. (2006) Generic POLCA—A production and materials flow control mechanism for quick response manufacturing. International Journal of Production Economics 104: 74–84

    Article  Google Scholar 

  • Framinan J. M., Gonzalez P. L., Ruiz-Usano R. (2003) The Conwip production control system: Review and research issues. Production Planning & Control 14(3): 255–265

    Article  Google Scholar 

  • Frein Y., Di Mascolo M., Dallery Y. (1995) On the design of generalized kanban control systems. International Journal of Operations in Production Management 15(9): 158–184

    Article  Google Scholar 

  • Gaury, E. G. A. (2000). Designing pull production control systems: Customization and robustness. (Phd. Thesis, Ed. Center, Tilburg University, The Netherlands).

  • Gaury E. G. A., Pierreval H., Kleijnen J. P. C. (2000) An evolutionary approach to select a pull system among Kanban, Conwip and Hybrid. Journal of Intelligent Manufacturing 11: 157–167

    Article  Google Scholar 

  • Gaury E. G. A., Pierreval H., Kleijnen J. P. C. (2001) A methodology to customize pull control systems. Journal of Operational Research Society 52(7): 789–799

    Article  Google Scholar 

  • Geraghty J., Heavey C. (2004) A comparison of Hybrid Push/Pull and CONWIP/Pull production inventory control policies. International Journal of Production Economics 91: 75–90

    Article  Google Scholar 

  • Gershwin S. B. (2000) Design and operation of manufacturing systems: The control-point policy. IIE Transactions 32(10): 891–906

    Google Scholar 

  • Ghrayeb O., Phojanamongkolkij N., Tan B. A. (2009) A hybrid push/pull system in assemble-to-order manufacturing environment. Journal of Intelligent Manufacturing 20(4): 379–387

    Article  Google Scholar 

  • Gilland W. (2002) A simulation study comparing performance of Conwip and bottleneck-based release rules. Production Planning & Control 13(2): 211–219

    Article  Google Scholar 

  • Goldratt E. M., Cox J. (1984) The Goal: An ongoing improvement process. North River Press, New York

    Google Scholar 

  • González-R P. L., Framinan J. M. (2009) The pull evolution: From Kanban to customised token-based systems. Production Planning & Control 20(3): 276–287

    Article  Google Scholar 

  • González-R P. L., Framinan J. M., Ruiz-Usano R. (2010) A multi-objective comparison of dispatching rules in a Drum-Buffer-Rope production control system. International Journal of Computer Integrated Manufacturing 23(2): 155–167

    Article  Google Scholar 

  • Graves R. J., Konopka J. M., Milne R. J. (1995) Literature review of material flow control mechanisms. Production Planning & Control 6(5): 395–403

    Article  Google Scholar 

  • Grossfeld-Nir A., Magazine M. (2002) Gated MaxWip: A strategy for controlling multistage production systems. International Journal of Production Research 40(11): 2557–2567

    Article  Google Scholar 

  • Gstettner S., Kuhn H. (1996) Analysis of production control systems Kanban and Conwip. International Journal of Production Research 34(11): 3253–3274

    Article  Google Scholar 

  • Hall, R. W. (1986). Synchro MRP: Combining KANBAN and MRP: The YAMAHA PYMAC. System I.E.M.P

  • Hodgson T. J., Wang D. (1991a) Optimal hybrid push/pull control strategies for a parallel multi-stage system: Part I. International Journal of Production Research 29(6): 1279–1287

    Article  Google Scholar 

  • Hodgson T. J., Wang D. (1991b) Optimal hybrid push/pull control strategies for a parallel multi-stage system: Part II. International Journal of Production Research 29(7): 1453–1460

    Article  Google Scholar 

  • Hopp W. J., Spearman M. L. (2000) Factory physics: Foundations of manufacturing management, 2nd edn. Irwin/McGraw-Hill, IrwinBurr Ridge, IL

    Google Scholar 

  • Karaesmen F., Dallery Y. (2000) A performance comparison of pull type control mechanisms for multi-stage manufacturing. International Journal of Production Economics 68(1): 59–71

    Article  Google Scholar 

  • Khojasteh-Ghamari Y. (2009) A performance comparison between Kanban and CONWIP controlled assembly systems. Journal of Intelligent Manufacturing 20(6): 751–760

    Article  Google Scholar 

  • Kimball G. E. (1988) General Principles of inventory control. International Journal of Manufacturing and Operations Management 1: 119–130

    Google Scholar 

  • Kotani S. (2008) Optimal method for changing the number of kanbans in the e-Kanban System and its applications. International Journal of Production Research 45(24): 5789–5809

    Article  Google Scholar 

  • Lage Junior M., Godinho Filho. M. (2010) Variations of the Kanban system: Literature review and classification. International Journal of Production Economics 125(1): 13–21

    Article  Google Scholar 

  • Lambrecht M., Segaert A. (1990) Buffer stock allocation and assembly type production lines. International Journal of Operations & Production Management 10(2): 47–61

    Article  Google Scholar 

  • Land M. J. (2009) Cobacabana (control of balance by card-based navigation): A card-based system for job shop control. International Journal of Production Economics 117(1): 97–103

    Article  Google Scholar 

  • Lavoie P., Gharbi A., Kenne J.-P. (2010) A comparative study of pull control mechanisms for unreliable homogenous transfer lines. International Journal of Production Economics 124(1): 241–251

    Article  Google Scholar 

  • Li J.-W. (2003) Improving the performance of job shop manufacturing with demand-pull production control by reducing set-up/processing time variability. International Journal of Production Economics 84(3): 255–270

    Article  Google Scholar 

  • Liberopoulos G., Dallery Y. (2000) A unified framework for pull control mechanisms in multi-stage manufacturing systems. Annals of Operations Research 93: 325–355

    Article  Google Scholar 

  • Lödding, H., & Wiendahl, H. P., (2000). Decentralized WIP-oriented manufacturing control (DEWIP). A systematic approach to shop floor control. In 33rd CIRP International Seminar on Manufacturing System, pp. 170–175.

  • Lödding H., Yu K. W., Wiendahl H. P. (2003) Decentralized WIP-oriented manufacturing control (DEWIP). Production Planning and Control 14(1): 42–54

    Article  Google Scholar 

  • Matta A., Dallery Y., Di Mascolo M. (2005) Analysis of assembly systems controlled with kanbans. European Journal of Operational Research 166(2): 310–336

    Article  Google Scholar 

  • Mitra D., Mitrani I. (1990) Analysis of a Kanban discipline for cell coordination. Management Science 36(12): 1548–1566

    Article  Google Scholar 

  • Monden Y. (1983) Toyota production system. Industrial Engineering and Management Press, Atlanta

    Google Scholar 

  • Nahavandi N. (2009) CWIPLII, a mechanism for improving throughput and leadtime inunbalanced flowline. International Journal of Production Research 47(11): 2921–2941

    Article  Google Scholar 

  • Paris J. L., Pierreval H. (2001) A distributed evolutionary simulation optimization approach for the configuration of multiproduct Kanban systems. International Journal of Computer Integrated Manufacturing 14(5): 421–430

    Article  Google Scholar 

  • Perros, H. G. & Altiok, T., (1986). Approximate analysis of open networks of queues with blocking: Tandem configuration. IEEE Transactions on Software Engineering, SE-12, 450–461.

    Google Scholar 

  • Pettersen J.-A., Segerstedt A. (2009) Restricted work-in-process: A study of differences between Kanban and CONWIP. International Journal of Production Economics 118(1): 199–207

    Article  Google Scholar 

  • Price W., Gravel M., Nsakanda A. L. (1994) A review of optimisation models of Kanban-based production systems. European Journal of Operational Research 75(1): 1–12

    Article  Google Scholar 

  • Pyke D. F., Cohen M. A. (1990) Push and pull in manufacturing and distribution systems. Journal of Operations Management 9(1): 24–43

    Article  Google Scholar 

  • Ramsay M. L., Brown S., Tabibzadeh K. (1990) Push, pull and squeeze shop floor control with computer simulation. Industrial Engineering 22(2): 39–45

    Google Scholar 

  • Sepehri M. M., Nahavandi N. (2007) Critical WIP loops: A mechanism for material flow control in flow lines. International Journal of Production Research 45(12): 2759–2773

    Article  Google Scholar 

  • Shanthikumar J. G., Yao D. D. (2007) John A. Buzacott and his pioneering contributions to manufacturing and service systems. Production and Operations Management 16(6): 657–664

    Article  Google Scholar 

  • Sharma S., Agrawal N. (2009) Selection of a pull production control policy under different demand situations for a manufacturing system by AHP-algorithm. Computers & Operations Research 36(5): 1622–1632

    Article  Google Scholar 

  • Spearman M. L., Hopp W. J. H., Woodruff D. L. (1989) A hierarchical control architecture for Constant Work-in-Process (CONWIP) production systems. Journal of Manufacturing Operation and Management 2: 147–171

    Google Scholar 

  • Spearman M. L., Woodruff D. L., Hoop W. J. (1990) Conwip: A pull alternative to Kanban. International Journal of Production Research 28(5): 879–894

    Article  Google Scholar 

  • Sugimori Y., Kusunoki K., Cho F., Uchikawa S. (1977) Toyota production system and kanban system materialization of just-in-time and respect-for-human system. International Journal of Production Research 15(6): 553–564

    Article  Google Scholar 

  • Suri R. (1998) Quick response manufacturing: A company-wide approach to lead time reduction. Productivity Press, Portland, OR

    Google Scholar 

  • Takahashi K., Myreshka , Hirotani D. (2005) Comparing CONWIP, synchronized CONWIP, and Kanban in complex supply chains. International Journal of Production Economics 93–94: 25–40

    Article  Google Scholar 

  • Uzsoy R., Martin-Vega L. A. (1990) Modelling Kanban-based demand-pull systems: A survey and critique. Manufacturing Review 3(3): 155–160

    Google Scholar 

  • Wang S., Sarker B. R. (2005) An assembly-type supply chain system controlled by kanbans under a just-in-time delivery policy. European Journal of Operational Research 162(1): 153–172

    Article  Google Scholar 

  • Wang S., Sarker B. R. (2006) Optimal models for a multi-stage supply chain system controlled by Kanban under just-in-time philosophy. European Journal of Operational Research 172: 179–200

    Article  Google Scholar 

  • Wiendahl H.-P. (1995) Load-oriented manufacturing control. Springer, Berlin

    Book  Google Scholar 

  • Wong C. Y., Johansen J. (2006) Making JIT retail a success: The coordination journey. International Journal of Physical Distribution and Logistics Management 36: 112–126

    Article  Google Scholar 

  • Xiaobo Z., Xu D., Zhang H., He Q. M. (2007) Modeling and analysis of a supply-assembly-store chain. European Journal of Operational Research 176: 275–294

    Article  Google Scholar 

  • Zipkin, P., (1989). A kanban-like production control system: analysis of simple models. Research Working Paper No. 89-1, Graduate School of Business, Columbia University, New York, NY 10027.

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Correspondence to Pedro L. González-R.

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González-R, P.L., Framinan, J.M. & Pierreval, H. Token-based pull production control systems: an introductory overview. J Intell Manuf 23, 5–22 (2012). https://doi.org/10.1007/s10845-011-0534-4

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