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Simulation Model for Wire Harness Design in the Car Production Line Optimization Using the SimPy Library

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Listed:
  • Ruddy Guerrero

    (Institute of Smart Cities, Department Statistics, Computer Science, and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

  • Adrian Serrano-Hernandez

    (Institute of Smart Cities, Department Statistics, Computer Science, and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

  • Jose Pascual

    (Department Statistics, Computer Science, and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

  • Javier Faulin

    (Institute of Smart Cities, Department Statistics, Computer Science, and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

Abstract

The automotive industry is one of the most important economic sectors in the world. At the beginning, vehicles only had mechanical components, so the use of an automotive wire harness was not indispensable. Cars today are equipped with electronic components that, in addition to the basic operations of moving, turning, and stopping, perform more and more functions every day. Wiring harnesses are indispensable for controlling these electronic components. Automotive wiring harnesses have hundreds of variants, are principally manufactured with customized designs, and are measured specifically for each car. A large number of production variants increase labor hours, as well as rework, inventory, and manufacturing costs. Even when technologies exist to assist in the design of production lines, today, the design of production lines is mainly based on experience from previous cases. This paper aims to show how a discrete event simulation permits support for decision making for the proper design of assembly lines, as well as identifying possible unbalances in production lines and overloaded processes. In our work, we design and implement a discrete event simulation model of this production using the SimPy Python library. Finally, a case study in the automotive sector is presented, a production week is simulated, and the current plant configuration and possible improvement scenarios are analyzed.

Suggested Citation

  • Ruddy Guerrero & Adrian Serrano-Hernandez & Jose Pascual & Javier Faulin, 2022. "Simulation Model for Wire Harness Design in the Car Production Line Optimization Using the SimPy Library," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:7212-:d:837439
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    References listed on IDEAS

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    1. Marshall L. Fisher & Christopher D. Ittner, 1999. "The Impact of Product Variety on Automobile Assembly Operations: Empirical Evidence and Simulation Analysis," Management Science, INFORMS, vol. 45(6), pages 771-786, June.
    2. S Robinson, 2005. "Discrete-event simulation: from the pioneers to the present, what next?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 619-629, June.
    3. Tran, Dai-Duong & Vafaeipour, Majid & El Baghdadi, Mohamed & Barrero, Ricardo & Van Mierlo, Joeri & Hegazy, Omar, 2020. "Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    4. Thomas Klier & James Rubenstein, 2008. "Who Really Made Your Car? Restructuring and Geographic change in the Auto Industry," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wrmyc, November.
    5. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
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    Cited by:

    1. Beixin Xia & Mingyue Zhang & Yan Gao & Jing Yang & Yunfang Peng, 2023. "Design for Optimally Routing and Scheduling a Tow Train for Just-in-Time Material Supply of Mixed-Model Assembly Lines," Sustainability, MDPI, vol. 15(19), pages 1-16, October.

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