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Managing Product Variety in Automobile Assembly: The Importance of the Sequencing Point

Author

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  • Jayashankar M. Swaminathan

    (Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Raleigh, North Carolina)

  • Thomas R. Nitsch

    (McKinsey & Company, Inc., Germany)

Abstract

In recent years, globalization of markets and increased consumer sophistication have led to an increase in the variety of products that customers demand and a consequent increase in the number of variants of any given product line that a manufacturer must supply. At the same time, an increasing number of companies have pushed the task of accommodating product variety up the supply chain to suppliers. This makes it increasingly difficult to understand where and how variety is accommodated. Based on our study of the automotive industry, we introduce the concept of a sequencing point, which we define as where component variants are placed in the sequence that final assembly requires. We discuss the implications of alternative sequencing-point-location strategy on management of product variety. For each strategy, we discuss associated trade-offs and provide short case studies.

Suggested Citation

  • Jayashankar M. Swaminathan & Thomas R. Nitsch, 2007. "Managing Product Variety in Automobile Assembly: The Importance of the Sequencing Point," Interfaces, INFORMS, vol. 37(4), pages 324-333, August.
    • Handle: RePEc:inm:orinte:v:37:y:2007:i:4:p:324-333
    DOI: 10.1287/inte.1060.0278
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    References listed on IDEAS

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    1. Robert R. Inman & Robert L. Bulfin, 1991. "Note---Sequencing JIT Mixed-Model Assembly Lines," Management Science, INFORMS, vol. 37(7), pages 901-904, July.
    2. David M. Upton, 1997. "Process Range in Manufacturing: An Empirical Study of Flexibility," Management Science, INFORMS, vol. 43(8), pages 1079-1092, August.
    3. Jayashankar M. Swaminathan & Sridhar R. Tayur, 2003. "Models for Supply Chains in E-Business," Management Science, INFORMS, vol. 49(10), pages 1387-1406, October.
    4. Stephen C. Graves, 1981. "A Review of Production Scheduling," Operations Research, INFORMS, vol. 29(4), pages 646-675, August.
    5. Andreas Drexl & Alf Kimms, 2001. "Sequencing JIT Mixed-Model Assembly Lines Under Station-Load and Part-Usage Constraints," Management Science, INFORMS, vol. 47(3), pages 480-491, March.
    6. Richard E. White & John N. Pearson & Jeffrey R. Wilson, 1999. "JIT Manufacturing: A Survey of Implementations in Small and Large U.S. Manufacturers," Management Science, INFORMS, vol. 45(1), pages 1-15, January.
    7. Jayashankar M. Swaminathan & Sridhar R. Tayur, 1998. "Managing Broader Product Lines through Delayed Differentiation Using Vanilla Boxes," Management Science, INFORMS, vol. 44(12-Part-2), pages 161-172, December.
    8. John Paul MacDuffie & Kannan Sethuraman & Marshall L. Fisher, 1996. "Product Variety and Manufacturing Performance: Evidence from the International Automotive Assembly Plant Study," Management Science, INFORMS, vol. 42(3), pages 350-369, March.
    9. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    10. Ulrich, Karl, 1995. "The role of product architecture in the manufacturing firm," Research Policy, Elsevier, vol. 24(3), pages 419-440, May.
    11. Hau L. Lee & Christopher S. Tang, 1997. "Modelling the Costs and Benefits of Delayed Product Differentiation," Management Science, INFORMS, vol. 43(1), pages 40-53, January.
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    Cited by:

    1. 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.
    2. Maximilian Stauder & Niklas Kühl, 2022. "AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 709-747, September.
    3. Marcel Lehmann & Heinrich Kuhn, 2020. "Modeling and analyzing sequence stability in flexible automotive production systems," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 366-394, June.
    4. Quetschlich, Mathias & Moetz, André & Otto, Boris, 2021. "Optimisation model for multi-item multi-echelon supply chains with nested multi-level products," European Journal of Operational Research, Elsevier, vol. 290(1), pages 144-158.
    5. 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).
    6. Taube, F. & Minner, S., 2018. "Resequencing mixed-model assembly lines with restoration to customer orders," Omega, Elsevier, vol. 78(C), pages 99-111.

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