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Methodology for bottleneck identification in a production system when implementing TOC

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
For TOC (Theory of Constraints) implementation in a production system, the determination of the system’s bottleneck is a crucial step. Effective bottleneck identification allows setting priorities for the improvement of a production system. The article deals with a significant problem for the manufacturing industry related to the location of a bottleneck. The article aims for a detailed analysis of methods for bottleneck identification based on a comprehensive literature review and the design of a generalised methodology for bottleneck identification in the production system. The article uses two research methods, first, the combination of a narrative and scoping literature review, and second, the logical design. Several methods for bottleneck identification are reviewed and compared, finding some being similar, and others giving new insights into the evaluated production system. A methodology for bottleneck identification is proposed. It contains several detailed methods arranged in coherent steps, which are suggested to be followed when aiming for the recognition of a production system’s bottleneck. The proposed methodology is expected to be helpful in the practical TOC implementation. The presented methodology for the identification of bottlenecks in a production system is a practical tool for managers and experts dealing with TOC. However, it is still a conceptual proposal that needs to be tested empirically. The proposed methodology for bottleneck identification is an original concept based on the current literature output. It contributes to the production management theory as a practical managerial tool.
Rocznik
Strony
74--82
Opis fizyczny
Bibliogr. 32 poz., rys., tab.
Twórcy
  • Bialystok University of Technology, Poland
  • Bialystok University of Technology, Poland
Bibliografia
  • Betterton, C. (2012). Detecting bottlenecks in serial production lines - A focus on interdeparture time variance. International Journal of Production Research, 50(15), 4158-4174. doi: 10.1080/00207543.2011.596847
  • Chiang, S.Y., Kuo, C.T., & Meerkov, S.M. (2002). c-Bottlenecks in Serial Production Lines: Identification and Application. Mathematical Problems in Engineering, 7(6), 543-578. doi: 10.1109/CDC.1999.832820
  • Christophe, F., Coatanea, E., & Bernard, A. (2014). Conceptual Design. In L. Laperrière & G. Reinhart (Eds.), Encyclopedia of Production Engineering. Berlin, Germany: Springer. doi: 10.1007/978-3-642-20617- 7_6444
  • Dongping, Z., Xitian, T., & Junha, G. (2014). A Bottleneck Detection Algorithm for Complex Product Assembly Line Based on Maximum Operation Capacity. Mathematical Problems in Engineering, 3, 1-9. doi: 10.1155/2014/258173
  • Eaidgah, Y., Maki, A., Kurczewski, K., & Abdekhodaee, A. (2016).Visual management, performance management and continuous improvement: A lean manufacturing approach. International Journal of Lean Six Sigma, 7(2), 187-210. doi: 10.1108/IJLSS-09-2014-0028
  • French, M.J. (1999).Conceptual design for engineers, 2nd ed. London, United Kingdom: The Design Council. doi: 10.1007/978-3-662-11364-6
  • Hino, S. (2006). Inside the Mind of Toyota. New York, United States: Productivity Press.
  • Ikeziri, L.M., Souza, F.B.D., Gapta, M.C., & Camargo Fiorini, P.D. (2018). Theory of constraints: review and bibliometric analysis. International Journal of Production Research, 57(15-16), 5068-5102. doi: 10.1080/00207543.2018.1518602
  • Koliński, A., & Tomkowiak, A. (2010). Using the analysis of bottlenecks in production management. Gospodarka Materiałowa i Logistyka, 9, 16-21.
  • Law, A.M., & Kelton, D.W. (2000). Simulation Modeling & Analysis. McGraw Hill.
  • Lawrence, S.R., & Buss, A.H. (1994). Shifting production bottlenecks: causes, cures, and conundrums. Production and Operations Management, 3(1), 21-37. doi: 10.1111/j.1937-5956.1994.tb00107
  • Li, R., Hamada, K., & Shimozori, T. (2010). Erratum to: Development of a Theory of Constraints Based Scheduling System for Ship Piping Production. Journal of Shanghai Jiaotong University (Science), 15(3), 354- 362. doi: 10.1007/s12204-010-1041-z
  • Liker, J. (2004). The Toyota Way: 14 Management Principles from the World’s Greatest Manufacturer. New York, United States: McGraw-Hill.
  • Lisiecka, K. (2013). TLS-Composition of Methods for Improving the Production Management System. Problemy Jakości, 7-8, 48-53.
  • Łopatowska, J. (2008). Aplication of TOC Thinking process in change of production planning and control process. Logistyka, 2, 86-94.
  • Łopatowska, J. (2017). Planning the implementation of projects in multi project environment using a critical chain. Zeszyty Naukowe Politechniki Śląskiej: Organizacja i Zarządzanie, 114, 303-316.
  • Puchkova, A., Le Romancer, J., & McFarlane, D.E. (2016). Balancing Push and Pull Strategies within the Production System. IFAC, 49(2), 66-71. doi: 10.1016/j.ifacol.2016.03.012
  • Robert, J., Bizzaro, P., & Selfe, C. (1997).The Harcourt Brace Guide to Writing in the Disciplines, New York, United States: Harcourt Brace.
  • Roser, C., Lorentzen, K., & Deuse, J. (2014). Reliable Shop Floor Bottleneck Detection for Flow Lines through Process and Inventory Observations. Robust Manufacturing Conference, Procedia CIRP, 19, 63-68. doi: 10.1016/j.procir.2014.05.020
  • Roser, Ch., Masaru, N., & Minoru, T. (2002). Shifting Bottleneck Detection. Winter Simulation Conference, edited by Enver Yucesan, CA, 1079-1086. doi: 10.1109/WSC.2002.1166360
  • Rother, M., & Shook, J. (1999). Learning to See: Value Stream Mapping to Add Value and Eliminate MUDA. Cambridge, United States: Lean Enterprise Institute.
  • Sims, T., & Wan, H. (2017). Constraint identification techniques for lean manufacturing systems. Robotics and Computer-Integrated Manufacturing, 43, 50-58. doi: 10.1016/j.rcim.2015.12.005
  • Skołud, B. (2006). Zarządzanie operacyjne-produkcja w małych i średnich przedsiębiorstwach [Operational management - production in small and medium-sized enterprises]. Gliwice, Polska: Wydawnictwo Politechniki Śląskiej.
  • Skołud, B. (2009). Decision making in the area of production flow management. Inżynieria Maszyn, 14(3), 7-18.
  • Thompson, G. (1999). Improving maintainability and reliability through design. London, United Kingdom: Professional Engineering Publishing.
  • Thürera, M., & Stevenson, M. (2018). Bottleneck-oriented order release with shifting bottlenecks: An assessment by simulation. International Journal of Production Economics, 197, 275-282. doi: 10.1016/j.ijpe.2018.01.010
  • Trojanowska, J., & Koliński, A. (2015). The impact of the application of TOC tools on selected indicators of production process efficiency. Logistyka, 4, 7-11.
  • Urban, W. (2019). TOC implementation in a medium-scale manufacturing system with diverse product rooting. Production & Manufacturing Research, 7(1), 178-194. doi: 10.1080/21693277.2019.1616002
  • Woeppel, M.J. (2009).Manufacturers Guide to Implementing Theory of Constraints. Warszawa, Poland: Mint Books.
  • Womack, J.P., & Jones, D.T. (1996). Lean Thinking: Banish Waste and Create Wealth in Your Corporation. New York, United States: Simon & Schuster.
  • Wrodarczyk, J. (2013). Two-Criteria Model of Product Mix Based on the Theory of Constraints. Studia Ekonomiczne, 163, 239-252.
  • Yua, Ch., & Matta, A. (2016). A statistical framework of data-driven bottleneck identification in manufacturing systems. International Journal of Production Research, 54(21), 6317-6332. doi: 10.1080/00207543.2015.1126681
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-691ad4b7-ce2c-4181-ab72-3fcd136f26e8
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