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An optimum scheduling method for multi-option product flows through production lineswithout intermediate buffers

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Języki publikacji
EN
Abstrakty
EN
The presented method is constructed for optimum scheduling in production lines with parallel machines and without intermediate buffers. The production system simultaneously performs operations on various types of products. Multi-option products were taken into account – products of a given type may differ in terms of details. This allows providing for individual requirements of the customers. The one-level approach to scheduling for multioption products is presented. The integer programming is used in the method – optimum solutions are determined: the shortest schedules for multi-option products. Due to the lack of the intermediate buffers, two possibilities are taken into account: no-wait scheduling, possibility of the machines being blocked by products awaiting further operations. These two types of organizing the flow through the production line were compared using computational experiments, the results of which are presented in the paper.
Twórcy
  • AGH University of Science and Technology, Faculty of Management, Chair of Operations Research, Al. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • [1] Varela M.L.H., Trojanowska J., Carmo-Silva S., Costa N.M.L., Machado J., Comparative simulation study of production scheduling in the hybrid and the parallel flow, Management and Production Engineering Review, 8, 2, 68–70, 2017.
  • [2] Chan F.T.S, Li N., Chung S.H., Saadat M., Management of sustainable manufacturing systems – a review on mathematical problems, International Journal of Production Research, 55, 4, 1210–1225, 2017.
  • [3] Hassani Z.I.M., Barkany A.E., Abbasi I.E., Jabri A., Darcherif A.M., Planning and scheduling of production system in conditioning line: industrial application, optimization and simulation approach, Management and Production Engineering Review, 10, 4, 3–10, 2019.
  • [4] Li X., Gao L., Zhang C., Shao X., A review on Integrated Process Planning and Scheduling, International Journal of Manufacturing Research, 5, 2, 161– 180, 2010.
  • [5] Sugimura N., Shrestha R., Tanimizu Y., Iwamura K., A study on integrated process planning and scheduling system for holonic manufacturing, Process Planning and Scheduling for Distributed Manufacturing, Springer, London, UK, 311–334, 2006.
  • [6] Soualhia M., Khomh F., Tahar S., Task Scheduling in Big Data Platforms: A Systematic Literature Review, The Journal of Systems and Software, 134, 170–189, 2017.
  • [7] Ruiz R., Vázquez-Rodriguez J.A., The Hybrid Flow Shop Scheduling Problem, European Journal of Operational Research, 205, 1, 1–18, 2010.
  • [8] Sawik T., Loading and scheduling of a flexible assembly system by mixed integer programming, European Journal of Operational Research, 154, 1, 1–19, 2004.
  • [9] Ronconi D.P., Birgin E.G., Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness, [in:] Ríos-Mercado R., Ríos-Solís Y. [Eds], Just-in-Time Systems. Springer Optimization and Its Applications, vol. 60, Springer, New York, 2012.
  • [10] Gonzales T.F. [Ed.], Handbook of Approximation Algorithms and Metaheuristics, Chaoman and Hall/CRC, New York, 2007.
  • [11] Behnamin J., Fatemi Ghomi S.M.T., Hybrid flowshop scheduling with machine and resource dependent processing times, Applied Mathematical Modelling, 35, 3, 1107–1123, 2011.
  • [12] Ribas I., Leinstein R., Framinan J.M., Review and classification of hybrid flowshop scheduling problems from a production system and a solution procedure perspective, Computers & Operations Research, 37, 8, 1439–1454, 2010.
  • [13] Magiera M., A relaxation heuristic for scheduling flowshops with intermediate buffers, Bulletin of the Polish Academy of Sciences. Technical Sciences, 61, 4, 929–942, 2013.
  • [14] Magiera M., Two-level of production scheduling for flow-shop systems with intermediate storages, in: Total Logistic Management, Annual 1, AGH University of Science and Technology, Kraków, 101–110, 2008.
  • [15] Castillo L. Borrajo D., Salido M.A., Oddi A. [Eds], Planning, scheduling and constraint satisfaction: from theory to practice, IOS Press, Amsterdam, 2005.
  • [16] Debnarova L., Krchova D., Kuric I., Group technology in context of the product classification, Advances in Sciences and Technology Research Journal, 8, 21, 78–81, 2014.
  • [17] Yadov A., Jayswal S.C., Modelling of flexible manufacturing system: a review, International Journal of Production Research, 56, 7, 2464–2487, 2017.
  • [18] Katragjini K., Vallada E., Ruiz R., Flow shop rescheduling under different types of disruption, International Journal of Production Research, 51, 3, 780–797, 2013.
  • [19] Vieira G.E., Herrmann J.W., Lin E., Rescheduling manufacturing systems: a framework of strategies, policies, and methods, Journal of Scheduling, 6, 39– 62, 2003.
  • [20] Magiera M., A no-wait scheduling method for assembly operations concerning multi-option electric devices, Przegląd Elektrotechniczny (Electrical Review), 94, 4, 187–190, 2018.
  • [21] Fourer R., Gay D., Kernighan B., AMPL, A Modelling Language for Mathematical Programming, Duxbury Press, Pacific Grove, CA, 2003.
  • [22] www.gurobi.com (Gurobi Optimizer), January 2019.
  • [23] Magiera M., A hierarchical method of planning of multi-option product flows through production lines [in Polish: Hierarchiczna metoda planowania przepływów wielowariantowych produktów przez linie produkcyjne], Automatyzacja procesów dyskretnych. Teoria i zastosowania, vol. I, Świerniak A., Krystek J. [Eds], Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, Gliwice, 171–183, 2016.
  • [24] Kaczmarczyk W., Valid inequalities for proportional lot-sizing and scheduling problem with fictitious microperiods, International Journal of Production Economics, 229, 236–247, 2020.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
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Bibliografia
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