1. Proceedings
  2. I3M
  3. 2023
  4. EMSS
  5. 10.46354/i3m.2023.emss.037

Increasing the output of prefab production lines - simulation aid to guide the improvement process

  • a Wolfgang Grenzfurtner,
  • b Elena Pichler,
  • c Manfred Gronalt 
  • b,c Boku - University of Natural Resources and Life Sciences, Institute of Production and Logistics, Feistmantelstrasse 4, 1180 Vienna, AUSTRIA
  • a University of Bayreuth, Life Science Faculty: Food, Nutrition and Health, Campus Kulmbach, Fritz-Hornschuch-Straße 13, 95326 Kulmbach, GERMANY
Cite as
Grenzfurtner, W., Pichler, E. and Gronalt, M. (2023). Increasing the output of prefab production lines - simulation aid to guide the improvement process. Proceedings of the 35rd European Modeling & Simulation Symposium (EMSS 2023). DOI: https://doi.org/10.46354/i3m.2023.emss.037

Abstract

The walls of prefabricated houses are produced at dedicated production sites. The wall element production system in industrialized prefabrication is a special form of mixed model assembly line, where all the different walls needed to assemble a house on site are usually prefabricated on one or more lines. Each wall has different characteristics that affect the processing time of the activities at each work station. Special attention must be given to modeling design variants to cover the wide range of customer requirements and to ensure production feasibility. This paper presents a bottleneck analysis for this specific production process and shows how to link the product data with the processes in the discrete event simulation model built with SIMIO. The model has been validated with real production data. The simulation experiments consider several scenarios regarding the baseline scenario as well as material and sequence changes in the process and the flexibilization of the employee assignment. The results clearly reveal bottleneck workstations and provide guidelines for improving overall production output. A subsequent research project will test the use of the model for real-time production planning using online data from production.

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