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Optimization of Motorcycle Assembly Processes Based on Lean Manufacturing Tools

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Advances and Applications in Computer Science, Electronics and Industrial Engineering (CSEI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1078))

Abstract

Global competition and economic dynamism force the assembly industry to look for productive philosophies of improvement, optimizing processes, and resources. The challenge in the optimization process involves finding tools that will grant an optimal process. This article proposes a process optimization through the application of Lean Manufacturing tools, with the necessary guidelines analyzed and verified by computational simulation in a motorcycle assembler. Firstly, applying a plant distribution, together with the change of productive system, allowed the reduction of distances, elimination of unnecessary movements, and reprocessing. Then, Pull System reduced the stock of both the product in process and the final product in the warehouse, avoiding the generation of future waste and expenses due to overproduction. Finally, the use of the 5S tool entailed maintaining order and cleanliness inside the plant to facilitate the management of internal resources. In the study reported, an average reduction of 40% in assembly time and an average increase in production of 30% of all motorcycle models that were part of the study are achieved.

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Acknowledgments

This study is part of the research project “Modelo de Gestión para la Optimización de Procesos y Costos en la Industria de Ensamblaje,” supported by the Research Department of the University of Cuenca (DIUC). The authors gratefully acknowledge the contributions and feedback provided by the IMAGINE Project team; similarly, to the management and operational staff of the motorcycle assembly for their willingness to being analyzed as a case study.

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Authors and Affiliations

  1. Faculty of Chemical Sciences, Universidad de Cuenca, Cuenca, Ecuador

    Jonnathan Quezada & Juan Llivisaca

  2. Department of Computer Sciences, Faculty of Engineering, Universidad de Cuenca, Cuenca, Ecuador

    Lorena Siguenza-Guzman

Authors
  1. Jonnathan Quezada
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  2. Lorena Siguenza-Guzman
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  3. Juan Llivisaca
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Corresponding author

Correspondence to Juan Llivisaca .

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Editors and Affiliations

  1. Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland

    Jyrki Nummenmaa

  2. Faculty of Engineering in Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain

    Federico Pérez-González

  3. Department of Management, Escola Tècnica Superior d’Enginyeria Industrial de Barcelona (ETSEIB), Universitat Politècnica de Catalunya, Barcelona, Spain

    Bruno Domenech-Lega

  4. Division of Geotechnical Engineering and Geosciences; Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain

    Jean Vaunat

  5. Faculty of Software, Electronics and Industrial Engineering, Universidad Técnica de Ambato, Ambato, Ecuador

    Félix Oscar Fernández-Peña

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Quezada, J., Siguenza-Guzman, L., Llivisaca, J. (2020). Optimization of Motorcycle Assembly Processes Based on Lean Manufacturing Tools. In: Nummenmaa, J., Pérez-González, F., Domenech-Lega, B., Vaunat, J., Oscar Fernández-Peña, F. (eds) Advances and Applications in Computer Science, Electronics and Industrial Engineering. CSEI 2019. Advances in Intelligent Systems and Computing, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-030-33614-1_17

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  • DOI: https://doi.org/10.1007/978-3-030-33614-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33613-4

  • Online ISBN: 978-3-030-33614-1

  • eBook Packages: EngineeringEngineering (R0)

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