PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Performance improvements in horizontally integrated production networks through real-time rescheduling in the event of disruptions

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Rescheduling is a frequently used reactive strategy in order to limit the effects of disruptions on throughput times in multi-stage production processes. However, organizational deficits often cause delays in the information on disruptions, so rescheduling cannot limit disruption effects on throughput times optimally. Our approach strives for an investigation of possible performance improvements in multi-stage production processes enabled by realtime rescheduling in the event of disruptions. We developed a methodology whereby we could measure these possible performance improvements. For this purpose, we created and implemented a simulation model of a multi-stage production process. We defined system parameters and varied factors according to our experiment design, such as information delay, lot sizes and disruption durations. The simulation results were plotted and evaluated using DoE methodology. Dependent on the factor settings, we were able to prove large improvements by real-time rescheduling regarding the absorption of disruption effects in our experiments.
Twórcy
  • University of Siegen, Institute of International Production Engineering and Management, Germany
  • University of Siegen, Institute of International Production Engineering and Management, Germany
  • University of Siegen, Institute of International Production Engineering and Management, Paul-Bonatz-Straße 9-11, 57076 Siegen, Germany
Bibliografia
  • [1] Schuh G. et al., (Monetary Value of in Time Deliveries): Decentralized, Market-Driven Coordination Mechanism Based on the Monetary Value of in Time Deliveries, [in:] Proceedings of Global Business Research Conference, Kathmandu, pp. 1–13, 2013.
  • [2] Christopher M., The Agile Supply Chain, Industrial Marketing Management, 29(1), 37–44, 2000, doi: 10.1016/S0019-8501(99)00110-8.
  • [3] Wagner J., Burggräf P., Dannapfel M., Fölling C., Assembly Disruptions – Empirical Evidence in the Manufacturing Industry of Germany, Austria and Switzerland, International Refereed Journal of Engineering and Science, 6(3), 15–25, 2017.
  • [4] Cowling P., Johansson M., Using real time information for effective dynamic scheduling, European Journal of Operational Research, 139(2), 230–244, 2002, https://doi.org/10.1016/S03772217(01)00355-1.
  • [5] Cauvin A.C.A., Ferrarini A.F.A., Tranvouez E T.E., Disruption management in distributed enterprises: A multi-agent modelling and simulation of cooperative recovery behaviours, International Journal of Production Economics, 122(1), 429–439, 2009, https://doi.org/10.1016/j.ijpe.2009.06.014.
  • [6] Schumacher J., Effizientes Störungsmanagement in der Produktion, ZWF Zeitschrift Für Wirtschaftlichen Fabrikbetrieb, 104(3), 206–209, 2009, https://doi.org/10.3139/104.110037.
  • [7] Sundstrom N., Lennartson B., Rescheduling affected operations – a purely predictive approach, 13th International Workshop on Discrete Event Systems (WODES), pp. 71–78, 2016, https://doi.org/10.1109/WODES.2016.7497828.
  • [8] Lehmann F., Störungsmanagement in der Einzelund Kleinserienmontage: Ein Beitrag zur EDVgestützten Montagesteuerung, Aachen: Shaker Verlag, 1992.
  • [9] Heil M., Entstörung betrieblicher Abläufe, Wiesbaden: Deutscher Universitäts-Verlag, 1995.
  • [10] Kampker A., Wagner J., Burggräf P., Bäumers Y., Criticality-focused, pre-emptive disruption management in low-volume assembly, Paper presented at the 23rd International Conference on Production Research – Operational Excellence towards sustainable development goals (SDG) trough Industry 4.0, Manila, August 2–5, 2015.
  • [11] Burggräf P., Wagner J., Lück K., Adlon T., Costbenefit analysis for disruption prevention in lowvolume assembly, Production Engineering, 11(3), 331–342, 2017, https://doi.org/10.1007/s11740-0170735-6.
  • [12] Jonsson P., Lesshammar M., Evaluation and improvement of manufacturing performance measurement systems – the role of OEE, International Journal of Operations & Production Management, 19(1), 55–78, 1999, doi: 10.1108/ 01443579910244223.
  • [13] Eversheim W., Störungsmanagement in der Montage, Düsseldorf: VDI-Verlag, 1992.
  • [14] Schwartz F., Störungsmanagement in Produktionssystemen, Aachen: Shaker Verlag, 2003.
  • [15] Brown M.C., The dynamic rescheduler: conquering the changing production environment, In Proceedings. The Fourth Conference on Artificial Intelligence Applications, pp. 175–180, 1988, https://doi.org/10.1109/CAIA.1988.196100.
  • [16] Wu S.D., Storer R.H., Chang P.-C., A rescheduling procedure for manufacturing systems under random disruptions, In New Directions for Operations Research in Manufacturing, Berlin, Heidelberg: Springer, 1992.
  • [17] Abumaizar R.J., Svestka J.A., Rescheduling job shops under random disruptions, International Journal of Production Research, 35(7), 2065–2082, 1997, https://doi.org/10.1080/002075497195074.
  • [18] Akturk M.S., Gorgulu E., Match-up scheduling under a machine breakdown, European Journal of Operational Research, 112(1), 81–97, 1999, https://doi.org/10.1016/S0377-2217(97)00396-2.
  • [19] Cauvin A.C.A., Ferrarini A.F.A., Tranvouez E.T.E., Disruption management in distributed enterprises: a multi-agent modelling and simulation of cooperative recovery behaviours, International Journal of Production Economics, 122(1), 429–439, 2009, https://doi.org/10.1016/j.ijpe.2009.06.014.
  • [20] Tang L., Zhang Y., Parallel machine scheduling under the disruption of machine breakdown, Industrial and Engineering Chemistry Research, 48(14), 6660– 6667, 2009, https://doi.org/10.1021/ie801868f.
  • [21] Qi X., Bard J.F., Yu G., Disruption management for machine scheduling: The case of SPT schedules, International Journal of Production Economics, 103(1), 166–184, 2006, https://doi.org/ 10.1016/j.ijpe.2005.05.021.
  • [22] Xu X., Shang J., Wang H., Chiang W.C., Optimal production and inventory decisions under demand and production disruptions, International Journal of Production Research, 54(1), 287–301, 2015, https://doi.org/10.1080/00207543.2015.1073402.
  • [23] Man K.F., Tang K.S., Kwong S., Ip W.H., Genetic algorithm to production planning and scheduling problems for manufacturing systems, Production Planning & Control, 11(5), 443–458, 2000, doi: 10.1080/09537280050051942.
  • [24] Mattfeld D.C., Bierwirth C., An efficient genetic algorithm for job shop scheduling with tardiness objectives, European Journal of Operational Research, 155(3), 616–630, 2004, doi: 10.1016/S03772217(03)00016-X.
  • [25] Tay J.C., Ho N.B., Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems, Computers & Industrial Engineering, 54(3), 453–473, 2008.
  • [26] Brynjolfsson E., McAfee A., Big Data: The Management Revolution, Harvard Business Review, 90(10), 60–68, 2012.
  • [27] Yu W., The effect of IT-enabled supply chain integration on performance, Production Planning & Control, 26(12), 945–957, 2015, https://doi.org/10.1080/09537287.2014.1002021.
  • [28] Acatech, Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0: Abschlussbericht des Arbeitskreises Industrie 4.0. Frankfurt am Main, 2013.
  • [29] Kieviet A., Digitalisierung der Wertschöpfung: Auswirkung auf das Lean Management, [in:] Erfolgsfaktor Lean Management 2.0, Ku¨nzel H. [Ed.], pp. 41–59, 2016, Berlin, Heidelberg: Springer, https://doi.org/10.1007/978-3-662-49752-4 3.
  • [30] Kaufmann T., Forstner L., Die horizontale Integration der Wertschöpfungskette in der Halbleiterindustrie – Chancen und Herausforderungen, [in:] Industrie 4.0 in Produktion, Automatisierung und Logistik, Bauernhansel T., ten Hompel M., Vogel-Heuser B. [Eds], pp. 359–367, 2014, Wiesbaden: Springer Fachmedien Wiesbaden, https://doi.org/10.1007/978-3-658-04682-8 18.
  • [31] Sprunt B., Sha L., Lehoczky J., Aperiodic task scheduling for Hard-Real-Time systems, RealTime Systems, 1(1), 27–60, 1989, https://doi.org/ 10.1007/BF02341920.
  • [32] Aken J.E. van, Management Research Based on the Paradigm of the Design Sciences: The Quest for Field-Tested and Grounded Technological Rules, Journal of Management Studies, 41(2), 219–246, 2004, https://doi.org/10.1111/j.14676486.2004.00430.x.
  • [33] VDI 3633-1:2014-12.2014, Simulation of systems in materials handling, logistics and production – Part 1: Fundamentals, Berlin: Beuth Verlag.
Uwagi
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-254e84f4-e898-437d-a08c-dd732da947ba
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.