IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v33y2022i3d10.1007_s10845-020-01668-w.html
   My bibliography  Save this article

A clustering approach for modularizing service-oriented systems

Author

Listed:
  • Omar Ezzat

    (Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Henri Fayol Institute)

  • Khaled Medini

    (Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Henri Fayol Institute)

  • Xavier Boucher

    (Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Henri Fayol Institute)

  • Xavier Delorme

    (Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Henri Fayol Institute)

Abstract

Companies are seeking more and more to offer customized goods and services to customers to be able to satisfy their needs. Several methods emerged to fulfill the needs of customization without affecting the performance of the company. Modularity has been considered as an effective method to address the challenges regarding variety management in the product and service domain. It has been addressed in the product domain but rarely in the service domain. This paper aims to provide a method to modularize a service-oriented system that consists of products and services. The method uses a set of modularization criteria and clustering techniques to form service-oriented system modules (product and/or service modules). The output of the clustering process is evaluated using indicators to provide decision-makers with insights into potentially preferred clustering alternatives. A test case is presented in order to show the applicability of the method.

Suggested Citation

  • Omar Ezzat & Khaled Medini & Xavier Boucher & Xavier Delorme, 2022. "A clustering approach for modularizing service-oriented systems," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 719-734, March.
    • Handle: RePEc:spr:joinma:v:33:y:2022:i:3:d:10.1007_s10845-020-01668-w
    DOI: 10.1007/s10845-020-01668-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-020-01668-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-020-01668-w?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. 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.
    2. Aurelio Montalto & Serena Graziosi & Monica Bordegoni & Luca Di Landro & Michael Johannes Leonardus Tooren, 2020. "An approach to design reconfigurable manufacturing tools to manage product variability: the mass customisation of eyewear," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 87-102, January.
    3. Na Zhang & Yu Yang & Yujie Zheng & Jiafu Su, 2019. "Module partition of complex mechanical products based on weighted complex networks," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1973-1998, April.
    4. Lau Antonio, K.W. & Yam, Richard C.M. & Tang, Esther, 2007. "The impacts of product modularity on competitive capabilities and performance: An empirical study," International Journal of Production Economics, Elsevier, vol. 105(1), pages 1-20, January.
    5. Zhang, Min & Guo, Hangfei & Huo, Baofeng & Zhao, Xiande & Huang, Jianbo, 2019. "Linking supply chain quality integration with mass customization and product modularity," International Journal of Production Economics, Elsevier, vol. 207(C), pages 227-235.
    6. Samyeon Kim & Seung Ki Moon, 2019. "Eco-modular product architecture identification and assessment for product recovery," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 383-403, 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. Sihan Huang & Guoxin Wang & Shiqi Nie & Bin Wang & Yan Yan, 2023. "Part family formation method for delayed reconfigurable manufacturing system based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2849-2863, August.

    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. Barbosa, Luziane Machado & Lacerda, Daniel Pacheco & Piran, Fabio Antonio Sartori & Dresch, Aline, 2017. "Exploratory analysis of the variables prevailing on the effects of product modularization on production volume and efficiency," International Journal of Production Economics, Elsevier, vol. 193(C), pages 677-690.
    2. Fabricio Eidelwein & Fabio Antonio Sartori Piran & Daniel Pacheco Lacerda & Aline Dresch & Luis Henrique Rodrigues, 2018. "Exploratory Analysis of Modularization Strategy Based on the Theory of Constraints Thinking Process," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(2), pages 111-122, June.
    3. Federica Murmura & Laura Bravi & Gilberto Santos, 2021. "Sustainable Process and Product Innovation in the Eyewear Sector: The Role of Industry 4.0 Enabling Technologies," Sustainability, MDPI, vol. 13(1), pages 1-16, January.
    4. Pero, Margherita & Stößlein, Martin & Cigolini, Roberto, 2015. "Linking product modularity to supply chain integration in the construction and shipbuilding industries," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 602-615.
    5. Scaringella, Laurent & Burtschell, François, 2017. "The challenges of radical innovation in Iran: Knowledge transfer and absorptive capacity highlights — Evidence from a joint venture in the construction sector," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 151-169.
    6. Na Liu & Pui-Sze Chow & Hongshan Zhao, 2020. "Challenges and critical successful factors for apparel mass customization operations: recent development and case study," Annals of Operations Research, Springer, vol. 291(1), pages 531-563, August.
    7. Zhigang Fan & Fei Dai & Mingu Kang & Kihyun Park & Gukseong Lee, 2024. "Combining internal functional integration with product modularization and supply chain alignment for achieving mass customization," Operations Management Research, Springer, vol. 17(3), pages 1197-1212, September.
    8. Yuming Guo, 2023. "Towards the efficient generation of variant design in product development networks: network nodes importance based product configuration evaluation approach," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 615-631, February.
    9. Wang, Shuai & Ma, Shuang, 2023. "Is product customization always beneficial in the context of C2M platforms? A signaling theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    10. 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.
    11. Hong, Paul & Doll, William J. & Revilla, Elena & Nahm, Abraham Y., 2011. "Knowledge sharing and strategic fit in integrated product development proejcts: An empirical study," International Journal of Production Economics, Elsevier, vol. 132(2), pages 186-196, August.
    12. Ming Zhang & Jianjun Zhu & Ponnambalam Kumaraswamy & Hehua Wang, 2019. "Evolutionary Game Analysis of the Effects of Problem Size and the Problem Proposing Mechanism on the Problem Processing Mechanism in a New Main Manufacturer–Supplier Collaborative System," Mathematics, MDPI, vol. 7(7), pages 1-19, July.
    13. Sihan Huang & Guoxin Wang & Shiqi Nie & Bin Wang & Yan Yan, 2023. "Part family formation method for delayed reconfigurable manufacturing system based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2849-2863, August.
    14. Shiva Moslemi & Hamidreza Izadbakhsh & Marzieh Zarinbal, 2019. "A new reliable performance evaluation model: IFB-IER–DEA," OPSEARCH, Springer;Operational Research Society of India, vol. 56(1), pages 14-31, March.
    15. Byungjoo Paek & Joohyun Kim & Joonyoung Park & Heesang Lee, 2019. "Outsourcing Strategies of Established Firms and Sustainable Competitiveness: Medical Device Firms," Sustainability, MDPI, vol. 11(17), pages 1-28, August.
    16. Dekkers, Rob & Chang, C.M. & Kreutzfeldt, Jochen, 2013. "The interface between “product design and engineering” and manufacturing: A review of the literature and empirical evidence," International Journal of Production Economics, Elsevier, vol. 144(1), pages 316-333.
    17. 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.
    18. Zhang, Min & Zhao, Xiande & Qi, Yinan, 2014. "The effects of organizational flatness, coordination, and product modularity on mass customization capability," International Journal of Production Economics, Elsevier, vol. 158(C), pages 145-155.
    19. Cabigiosu, Anna & Zirpoli, Francesco & Camuffo, Arnaldo, 2013. "Modularity, interfaces definition and the integration of external sources of innovation in the automotive industry," Research Policy, Elsevier, vol. 42(3), pages 662-675.
    20. Liu, Jiawen & Gong, Yeming (Yale) & Zhu, Joe & Zhang, Jinlong, 2018. "A DEA-based approach for competitive environment analysis in global operations strategies," International Journal of Production Economics, Elsevier, vol. 203(C), pages 110-123.

    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:spr:joinma:v:33:y:2022:i:3:d:10.1007_s10845-020-01668-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.