IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v67y2016i12d10.1057_jors.2016.32.html
   My bibliography  Save this article

Hierarchical game joint optimization for product family-driven modular design

Author

Listed:
  • Shuang Ma

    (Tianjin University)

  • Gang Du

    (Tianjin University)

  • Jianxin (Roger) Jiao

    (Georgia Institute of Technology)

  • Ruchuan Zhang

    (Tianjin University)

Abstract

Abstract Product family design takes advantage of modularity to enable product variety while maintaining mass production efficiency. Focusing on a set of similar product variants, product family modularity (PFM) is achieved by reusing common components and minimizing fulfillment costs throughout the product realization process. On the other hand, traditional modular design emphasizes technical system modularity (TSM) that focuses on a single product and is geared towards product decomposition in light of technical feasibility. While it is appealing to incorporate product family considerations into the prevailing modularization theories and methods, the key challenge lies in that TSM and PFM are essentially associated with different goals and decision criteria. This leads to a dilemma that TSM and PFM are competing in decision making for identification of modules by grouping similar components. Realizing the importance of game-theoretic decision making underlying product family-driven modular design, this paper proposes to leverage TSM and PFM within a coherent framework of joint optimization. A hierarchical game joint optimization model is developed in line with bilevel programming. A two-dimension evaluation criteria taxonomy is presented for TSM and PFM criteria measure. A bilevel nested genetic algorithm is put forward for efficient solution of the non-linear hierarchical joint optimization model. A case study of robotic vacuum cleaner modular design is reported to gain insight into joint optimization of TSM and PFM. Results and analyses demonstrate that the proposed hierarchical joint optimization model is robust and can empower modular design in cohesion with product family concerns.

Suggested Citation

  • Shuang Ma & Gang Du & Jianxin (Roger) Jiao & Ruchuan Zhang, 2016. "Hierarchical game joint optimization for product family-driven modular design," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(12), pages 1496-1509, December.
  • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:12:d:10.1057_jors.2016.32
    DOI: 10.1057/jors.2016.32
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2016.32
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. van Hoesel, Stan, 2008. "An overview of Stackelberg pricing in networks," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1393-1402, September.
    2. Xiao, Tiaojun & Choi, Tsan-Ming & Cheng, T.C.E., 2014. "Product variety and channel structure strategy for a retailer-Stackelberg supply chain," European Journal of Operational Research, Elsevier, vol. 233(1), pages 114-124.
    3. Aust, Gerhard & Buscher, Udo, 2012. "Vertical cooperative advertising and pricing decisions in a manufacturer–retailer supply chain: A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 223(2), pages 473-482.
    4. Seung Moon & Timothy Simpson & Soundar Kumara, 2010. "A methodology for knowledge discovery to support product family design," Annals of Operations Research, Springer, vol. 174(1), pages 201-218, February.
    5. Chen, Jing & Zhang, Hui & Sun, Ying, 2012. "Implementing coordination contracts in a manufacturer Stackelberg dual-channel supply chain," Omega, Elsevier, vol. 40(5), pages 571-583.
    6. Fixson, Sebastian K., 2007. "Modularity and Commonality Research: Past Developments and Future Opportunities," Working papers 37145, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. Esmaeili, M. & Aryanezhad, Mir-Bahador & Zeephongsekul, P., 2009. "A game theory approach in seller-buyer supply chain," European Journal of Operational Research, Elsevier, vol. 195(2), pages 442-448, June.
    8. Fixson, Sebastian K., 2007. "Modularity and Commonality Research: Past Developments and Future Opportunities," Working papers 37286, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Ulrich, Karl, 1995. "The role of product architecture in the manufacturing firm," Research Policy, Elsevier, vol. 24(3), pages 419-440, May.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:67:y:2016:i:12:d:10.1057_jors.2016.32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.palgrave-journals.com/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.