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Method of rescheduling for hybrid production lines with intermediate buffers

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Języki publikacji
EN
Abstrakty
EN
A method of creating production schedules regarding production lines with parallel machines is presented. The production line setup provides for intermediate buffers located between individual stages. The method mostly concerns situations when part of the production machines is unavailable for performance of operations and it becomes necessary to modify the original schedule, the consequence of which is the need to build a new schedule. The cost criterion was taken into account, as the schedule is created with the lowest possible costs regarding untimely completion of products (e.g. fines for delayed product completion). The proposed method is relaxing heuristics, thanks to which scheduling is performed in a relatively short time. This was confirmed by the presented results of computational experiments. These experiments were carried out for the rescheduling of machine parts production.
Rocznik
Strony
213--231
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wzory
Twórcy
  • AGH University of Science and Technology, Department of Operations Research, al. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • [1] J. Behnamin and S. M. T. Fatemi Ghomi: Hybrid flowshop scheduling with machine and resource dependent processing times, Applied Mathematical Modelling, 35(3) (2011), 1107–1123, doi: 10.1016/j.apm.2010.07.057.
  • [2] S. Bysko, J. Krystek, Sz. Bysko, and R. Lenort: Buffer management in solving a real sequencing problem in the automotive industry – Paint Shop 4.0 concept, Archives of Control Sciences, 29(3) (2019), 507–527, doi: 10.24425/acs.2019.130203.
  • [3] L. Castillo, D. Borrajo, M. A. Salido, and A. Oddi, (ed.): Planning, scheduling and constraint satisfaction: from theory to practice, IOS Press, Amsterdam, 2005.
  • [4] F. T. S. Chan, N. Li, S. H., Chung, and M. Saadat: Management of sustainable manufacturing systems – a review on mathematical problems, International Journal of Production Research, 55(4) (2017), 1210–1225, doi: 10.1080/00207543.2016.1229067.
  • [5] R. Fourer, D. M. Gay, and B.W. Kernighan: AMPL, A Modelling Language for Mathematical Programming, Duxbury Press, Pacific Grove, CA, 2003.
  • [6] H. Furmańczyk and M. Kubale: Scheduling of unit-length jobs with bi-partite incompatibility graphs on four uniform machines, Bulletin of the Polish Academy of Sciences: Technical Sciences, 65(1) (2017), 29–34, doi: 10.1515/bpasts-2017-0004.
  • [7] T. F. Gonzales (ed.): Handbook of Approximation Algorithms and Metaheuristics, Chaoman and Hall/CRC, New York, 2007.
  • [8] K. Katragjini, E. Vallada, and R. Ruiz: Flow shop rescheduling under different types of disruption, International Journal of Production Research, 51(3) (2013), 780–797, doi: 10.1080/00207543.2012.666856.
  • [9] J. Y.-T. Leung (ed.): Handbook of scheduling. Algorithms, Models and Performance Analysis, A CRC Press Company, Boca Raton, New York, Washington D. C, 2004.
  • [10] M. Magiera: A relaxation heuristic for scheduling flowshops with intermediate buffers, Bulletin of the Polish Academy of Sciences: Technical Sciences 61(4) (2013), 929–942, doi: 10.2478/bpasts-2013-0100.
  • [11] M. Magiera: A multi-level method of support for management of product flow through supply chains, Bulletin of the Polish Academy of Sciences: Technical Sciences, 63(4) (2015), 933–946, doi: 10.1515/bpasts-2015-0106.
  • [12] M. L. Pindeo: Planning and Scheduling in Manufacturing and Services, Springer, 2009. METHOD OF RESCHEDULING FOR HYBRID PRODUCTION LINES WITH INTERMEDIATE BUFFERS 231
  • [13] I. Ribas, R. Leinstein, and J. M. Framinan: Review and classification of hybrid flowshop scheduling problems from a production system and a solution procedure perspective. Computers & Operations Research, 37(8) (2010), 1439–1454, doi: 10.1016/j.cor.2009.11.001.
  • [14] D. P. Ronconi and E. G. Birgin: 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, 60, Springer, New York, NY. 2012, doi: 10.1007/978-1-4614-1123-9_5.
  • [15] R. Ruiz and J. A. Vázquez-Rodriguez: The Hybrid Flow Shop Scheduling Problem, European Journal of Operational Research, 205(1) (2010), 1–18, doi: 10.1016/j.ejor.2009.09.024.
  • [16] J. C. Seck-Tuoh-Mora, J. Medina-Marin, E. S. Martinez-Gomez, E. S. Hernadez-Gress, N. Hernadez-Romero, and V. Volpi-Leon: Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem, Archives of Control Sciences, 29(2), (2019), 205–226, doi: 10.24425/acs.2019.12937.
  • [17] M. Soualhia, F. Khomh, and S. Tahar: Task Scheduling in Big Data Platforms: A Systematic Literature Review”. Journal of Systems and Software, 134 (2017), 170–189.
  • [18] H. Suwa and H. Sandoh: Methods for Online Scheduling, In: Online Scheduling in Manufacturing. Springer, London, (2013), 55–73.
  • [19] A. Tóth, T. Knuutila, and O. S. Nevalainen: Machine configuration and workload balancing of modular placement machines in multi-product PCB assembly, International Journal of Computer Integrated Manufacturing, 31(9), (2018), 815–830, doi: 10.1080/0951192X.2018.1429667.
  • [20] G. E. Vieira, J. W. Herrmann, and E. Lin: Rescheduling Manufaturing systems: A Framework of Strategies, Policies and Methods, Journal of Scheduling, 6(1) (2003), 39–62.
  • [21] A. Yadov and S. C. Jayswal: Modelling of flexible manufacturing system: a review, International Journal of Production Research, 56(7) (2017), 2464–2487, doi: 10.1080/00207543.2017.1387302.
  • [22] www.gurobi.com (Gurobi Optimizer, 2019).
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-618ba937-cfb4-42e2-ab91-ac5e3eb8c1cc
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