IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v508y2018icp359-366.html
   My bibliography  Save this article

A quantitative model of universalization, serialization and modularization on equipment systems

Author

Listed:
  • Yin, Liang
  • He, Ming-Li
  • Xie, Wen-Bo
  • Yuan, Fei
  • Chen, Duan-Bing
  • Su, Yang

Abstract

Universalization, serialization and modularization are the three most important metrics in standardization of manufacturing. Developing with innovation of modern large-scale industrial production, a variety of methods were proposed to help enterprises to improve products’ applicability, prevent trade barriers, and promote technical cooperation. Meanwhile, some metrics were designed to evaluate or optimize these standardized procedures. However, no systematically quantitative model has been proposed to evaluate the standardization of equipment so far. In order to break the barrier, a quantitative analysis based evaluation model of equipment system is proposed in this paper, in which, universalization, serialization and modularization indices are defined based on heterogeneous information network. Comparing the results performed by the proposed model with experts’ evaluation, the metrics in proposed model can reveal the objective standardization of equipments.

Suggested Citation

  • Yin, Liang & He, Ming-Li & Xie, Wen-Bo & Yuan, Fei & Chen, Duan-Bing & Su, Yang, 2018. "A quantitative model of universalization, serialization and modularization on equipment systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 359-366.
  • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:359-366
    DOI: 10.1016/j.physa.2018.05.120
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118306642
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2018.05.120?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. King, John R, 1980. "Machine-component group formation in group technology," Omega, Elsevier, vol. 8(2), pages 193-199.
    2. Piran, Fabio Antonio Sartori & Lacerda, Daniel Pacheco & Camargo, Luis Felipe Riehs & Viero, Carlos Frederico & Dresch, Aline & Cauchick-Miguel, Paulo Augusto, 2016. "Product modularization and effects on efficiency: An analysis of a bus manufacturer using data envelopment analysis (DEA)," International Journal of Production Economics, Elsevier, vol. 182(C), pages 1-13.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alessandro Fontana & Andrea Barni & Deborah Leone & Maurizio Spirito & Agata Tringale & Matteo Ferraris & Joao Reis & Gil Goncalves, 2021. "Circular Economy Strategies for Equipment Lifetime Extension: A Systematic Review," Sustainability, MDPI, vol. 13(3), pages 1-28, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. S Kumar & D A Nottestad & E E Murphy, 2009. "Effects of product postponement on the distribution network: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 471-480, April.
    2. Işık Biçer & Florian Lücker & Tamer Boyacı, 2022. "Beyond Retail Stores: Managing Product Proliferation along the Supply Chain," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1135-1156, March.
    3. Mitroussi, K. & Abouarghoub, W. & Haider, J.J. & Pettit, S.J. & Tigka, N., 2016. "Performance drivers of shipping loans: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 438-452.
    4. Mustafa Doğru & A. Kok & G. Houtum, 2013. "Newsvendor characterizations for one-warehouse multi-retailer inventory systems with discrete demand under the balance assumption," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(3), pages 541-559, September.
    5. Sharda, Bikram & Akiya, Naoko, 2012. "Selecting make-to-stock and postponement policies for different products in a chemical plant: A case study using discrete event simulation," International Journal of Production Economics, Elsevier, vol. 136(1), pages 161-171.
    6. Kai-Lung Hui, 2004. "Product Variety Under Brand Influence: An Empirical Investigation of Personal Computer Demand," Management Science, INFORMS, vol. 50(5), pages 686-700, May.
    7. Daniel Adelman & George L. Nemhauser & Mario Padron & Robert Stubbs & Ram Pandit, 1999. "Allocating Fibers in Cable Manufacturing," Manufacturing & Service Operations Management, INFORMS, vol. 1(1), pages 21-35.
    8. Song, Zhe & Kusiak, Andrew, 2010. "Mining Pareto-optimal modules for delayed product differentiation," European Journal of Operational Research, Elsevier, vol. 201(1), pages 123-128, February.
    9. Li Chen & Yao Cui & Hau L. Lee, 2021. "Retailing with 3D Printing," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 1986-2007, July.
    10. Jain, Apurva, 2007. "Value of capacity pooling in supply chains with heterogeneous customers," European Journal of Operational Research, Elsevier, vol. 177(1), pages 239-260, February.
    11. Iman Ghalehkhondabi & Dusan Sormaz & Gary Weckman, 2016. "Multiple customer order decoupling points within a hybrid MTS/MTO manufacturing supply chain with uncertain demands in two consecutive echelons," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 976-997, December.
    12. Wang, Chia-Nan & Nguyen, Xuan-Tho & Le, Thi-Dao & Hsueh, Ming-Hsien, 2018. "A partner selection approach for strategic alliance in the global aerospace and defense industry," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 190-204.
    13. Gunasekaran, Angappa & Ngai, Eric W.T., 2009. "Modeling and analysis of build-to-order supply chains," European Journal of Operational Research, Elsevier, vol. 195(2), pages 319-334, June.
    14. Hillier, Mark S., 2002. "Using commonality as backup safety stock," European Journal of Operational Research, Elsevier, vol. 136(2), pages 353-365, January.
    15. Mila Nambiar & David Simchi‐Levi & He Wang, 2021. "Dynamic Inventory Allocation with Demand Learning for Seasonal Goods," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 750-765, March.
    16. Sam Ransbotham & Sabyasachi Mitra, 2010. "Target Age and the Acquisition of Innovation in High-Technology Industries," Management Science, INFORMS, vol. 56(11), pages 2076-2093, November.
    17. Ngniatedema, Thomas & Fono, Louis Aimé & Mbondo, Georges Dieudonné, 2015. "A delayed product customization cost model with supplier delivery performance," European Journal of Operational Research, Elsevier, vol. 243(1), pages 109-119.
    18. Mabel C. Chou & Geoffrey A. Chua & Huan Zheng, 2014. "On the Performance of Sparse Process Structures in Partial Postponement Production Systems," Operations Research, INFORMS, vol. 62(2), pages 348-365, April.
    19. Wong, Hartanto & Potter, Andrew & Naim, Mohamed, 2011. "Evaluation of postponement in the soluble coffee supply chain: A case study," International Journal of Production Economics, Elsevier, vol. 131(1), pages 355-364, May.
    20. John A. Buzacott & Rachel Q. Zhang, 2004. "Inventory Management with Asset-Based Financing," Management Science, INFORMS, vol. 50(9), pages 1274-1292, September.

    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:eee:phsmap:v:508:y:2018:i:c:p:359-366. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.