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Line feeding optimization for Just in Time assembly lines: An application to the automotive industry

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  • Sali, Mustapha
  • Sahin, Evren

Abstract

The performance of mixed-model assembly lines used in sectors such as the automotive industry depends on the availability of a large number of components that have to be supplied to the line on time and at minimum cost. In such settings, components may have different features such as volume, weight, bill of material coefficient, etc. Additionally, a given component may have several alternative variants among which a single one is used in the assembly of end products. Each variant is thus characterized by a varying degree of usage rate. Hence, the diversity of parts requires the selection of the best assembly line feeding mode that aims at minimizing the average total operating cost which mainly consists of labor costs associated with parts preparation before assembly, transportation to the line, picking operations during assembly, as well as parts storage cost. This paper proposes an optimization model that assigns each individual component to the most efficient line feeding mode among three alternatives which are line stocking, kitting and sequencing modes. The developed mixed integer program is applied to a first tier supplier plant in the automotive sector. Based on this model, insight is gained on the trade-off to be considered when deciding the more appropriate line feeding mode for each individual component and how system parameters impact this trade-off.

Suggested Citation

  • Sali, Mustapha & Sahin, Evren, 2016. "Line feeding optimization for Just in Time assembly lines: An application to the automotive industry," International Journal of Production Economics, Elsevier, vol. 174(C), pages 54-67.
    • Handle: RePEc:eee:proeco:v:174:y:2016:i:c:p:54-67
    DOI: 10.1016/j.ijpe.2016.01.009
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    References listed on IDEAS

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    1. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 79443, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Mustapha Sali & Evren Sahin & Alain Patchong, 2015. "An empirical assessment of the performances of three line feeding modes used in the automotive sector: line stocking vs. kitting vs. sequencing," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1439-1459, March.
    3. Mustapha Sali & Evren Sahin & Alain Patchong, 2015. "An empirical assessment of the performances of three line feeding modes used in the automotive sector: line stocking vs. kitting vs. sequencing," Post-Print hal-01508414, HAL.
    4. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    5. Bozer, Yavuz A. & McGinnis, Leon F., 1992. "Kitting versus line stocking: A conceptual framework and a descriptive model," International Journal of Production Economics, Elsevier, vol. 28(1), pages 1-19, November.
    6. repec:dau:papers:123456789/14496 is not listed on IDEAS
    7. Battini, Daria & Faccio, Maurizio & Persona, Alessandro & Sgarbossa, Fabio, 2009. "Design of the optimal feeding policy in an assembly system," International Journal of Production Economics, Elsevier, vol. 121(1), pages 233-254, September.
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    Cited by:

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    2. Baller, Reinhard & Hage, Steffen & Fontaine, Pirmin & Spinler, Stefan, 2020. "The assembly line feeding problem: An extended formulation with multiple line feeding policies and a case study," International Journal of Production Economics, Elsevier, vol. 222(C).
    3. Mohammed Hichame Benbitour & Evren Sahin, 2018. "The use of internal cross-docking in just-in-time plants," Post-Print hal-01793491, HAL.
    4. Emilio Moretti & Elena Tappia & Veronique Limère & Marco Melacini, 2021. "Exploring the application of machine learning to the assembly line feeding problem," Operations Management Research, Springer, vol. 14(3), pages 403-419, December.
    5. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2022. "Risk assessment of energy investment in the industrial framework – Uncertainty and Sensitivity Analysis for energy design and operation optimisation," Energy, Elsevier, vol. 239(PA).
    6. Adenipekun, Ebenezer Olatunde & Limère, Veronique & Schmid, Nico André, 2022. "The impact of transportation optimisation on assembly line feeding," Omega, Elsevier, vol. 107(C).
    7. Schmid, Nico André & Limère, Veronique & Raa, Birger, 2021. "Mixed model assembly line feeding with discrete location assignments and variable station space," Omega, Elsevier, vol. 102(C).

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