1. Proceedings
  2. I3M
  3. 2018
  4. MAS
  5. 10.46354/i3m.2018.mas.024

Approach to evaluating and planning industrial laundries by using discrete event simulation and performance measurement system

  • a David Weigert , 
  • b Frank Ryll ,
  • c Marcel Müller 
  • a,b Fraunhofer Institute for Factory Operation and Automation IFF, Magdeburg (Germany)
  • c Otto von Guericke University Magdeburg, Magdeburg (Germany)
Cite as
Weigert D., Ryll F., Müller M. (2018). Approach to evaluating and planning industrial laundries by using discrete event simulation and performance measurement system. Proceedings of the 17th International Conference on Modeling & Applied Simulation (MAS 2018), pp. 159-167. DOI: https://doi.org/10.46354/i3m.2018.mas.024

Abstract

Insufficient basic data, increasingly complex customer and product structures and a lack of transparency in the process structure increase the amount of laundry items in circulation, reduce machine utilization, delay deliveries and increase the error frequency. Competition is making it essential for laundries to operate quickly, reliably and cost effectively. The often non-transparent internal processes further worsen the economic situation of the companies. The evaluation of laundries based on logistic key figures has been solved individually and cumbersome until today. The reason is the partial lack of ability to determine the logistic performance indicator. The article presents on the one hand the implementation of a simulation study for the determination of the order of orders as well as the increase of the transparency by the development of a logistic performance measurement system using logistic indicators and characteristics.

References

  1. Arnold, D.; Isermann, H.; Kuhn, A.; Tempelmeier, H.; Furmans, K. (ed.): Handbuch Logistik. Berlin: Springer 2008.
  2. Avison, D.; Fitzgerald, G.: Information system development: Methodologies, techniques, and tools. London [etc.]: McGraw-Hill 2003.
  3. Cooper, M.C.; Ellram, L.M.: Characteristics of Supply Chain Management and the Implications for Purchasing and Logistics Strategy. The International Journal of Logistics Management 4 (1993) 2, p. 13–24.
  4. Devoldere, T.; Willems, B.; Duflou, J.R.; Dewulf, W.: The eco-efficiency of reuse centres critically explored – the washing machine case. International Journal of Sustainable Manufacturing 1 (2009) 3, p. 265.
  5. Gaul, W.; Both, M.: Computergestütztes Marketing. Berlin: Springer 1990.
  6. Gimenez, C.; Ventura, E.: Logistics‐production, logistics‐marketing and external integration. International Journal of Operations & Production Management 25 (2005) 1, p. 20–38.
  7. Grochla, E.: Erfolgsorientierte Materialwirtschaft durch Kennzahlen: Leitfaden zur Steuerung und Analyse der Materialwirtschaft. Baden-Baden: FBO-Verl. 1983.
  8. Guide, V.R.: Production planning and control for remanufacturing. Journal of Operations Management 18 (2000) 4, p. 467–483.
  9. Koether, R. (ed.): Taschenbuch der Logistik. München: Fachbuchverl. Leipzig im Carl-Hanser-Verl. 2011.
  10. Lassmann, W. (ed.): Wirtschaftsinformatik: Nachschlagewerk für Studium und Praxis. Wiesbaden: Gabler 2006.
  11. Mechel, C.: Ökoeffizienzanalyse zum Vergleich heterogener Unternehmen: Springer Fachmedien Wiesbaden GmbH 2017.
  12. Meyer, C.: Betriebswirtschaftliche Kennzahlen und Kennzahlen-Systeme. Sternenfels: Verl. Wiss. & Praxis 2007.
  13. Morris, M.; Carter, C.R.: Relationship Marketing and Supplier Logistics Performance. The Journal of Supply Chain Management 41 (2005) 4, p. 32–43.
  14. Müller, R.M.; Lenz, H.-J.: Business Intelligence. Berlin, Heidelberg: Springer Vieweg 2013.
  15. Nyhuis, P.; Wiendahl, H.-P.: Logistische Kennlinien: Grundlagen, Werkzeuge und Anwendungen. Berlin, Heidelberg: Springer 2012.
  16. Probst, H.-J.: Kennzahlen: Richtig anwenden und interpretieren. München: Redline Verlag 2014.
  17. Reichmann, T.; Kißler, M.; Baumöl, U.; Hoffjan, A.; Palloks-Kahlen, M.; Richter, H.J.; Schön, D.: Controlling mit Kennzahlen: Die systemgestützte  Controlling-Konzeption. München: Verlag Franz Vahlen 2017.
  18. Schneider, M.: Logistische Fertigungsbereichskennlinien. Düsseldorf: VDIVerl. 2004.
  19. Schönherr, M.: Wertorientiertes Logistikmanagement, Dissertation, 2015.
  20. Siegwart, H.; Reinecke, S.; Sander, S.: Kennzahlen für die Unternehmensführung. Bern: Haupt 2010.
  21. Swink, M.: The Influences of User Characteristics on Performance in a Logistics DSS Application. Decision Sciences 26 (1995) 4, p. 503–530.
  22. Watson, H.J.; Wixom, B.H.: The Current State of Business Intelligence. Computer 40 (2007) 9, p. 96–99.
  23. Weber, J.; Großklaus, A. (ed.): Kennzahlen für die Logistik. Stuttgart: Schäffer-Poeschel 1995.
  24. Wöhe, G.; Döring, U.: Einführung in die allgemeine Betriebswirtschaftslehre. München: Vahlen 2010.
  25. Yu, K.-W.: Terminkennlinie: Eine Beschreibungsmethodik für die Terminabweichung im Produktionsbereich. Düsseldorf: VDI-Verl. 2001.