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A systematic decision-making method for evaluating design alternatives of product service system based on variable precision rough set

Author

Listed:
  • Zaifang Zhang

    (Shanghai University)

  • Danhua Xu

    (Shanghai University)

  • Egon Ostrosi

    (Université de Technologie de Belfort-Montbéliard)

  • Li Yu

    (Shanghai University of Finance and Economics)

  • Beibei Fan

    (Shanghai University)

Abstract

Product service systems (PSS) have led global manufacturers to change from providing product only to offering both product and its services as a whole. The existing decision-making methods have difficulties in evaluating design alternatives systematically during PSS conceptual design process involving cognition vagueness and related complex factors. A new systematic decision-making method is developed for judging these alternatives. PSS is divided into multiple-modules associated with function characteristics and then evaluated by using the outputs of parallel houses of quality (HoQs). HoQs can efficiently deal with customer requirements and the relationships between product and service. A variable precision rough set-based approach is proposed to evaluate these alternatives, which can flexibly handle subjectivity and vagueness during the decision-making process. An optimizing model of least squares model is used to integrate individual judgments into a consensus group judgment. A non-deterministic ranking method is developed to identify optimal alternative based on the final judgments which are obtained by using a rough weighted geometric mean method. The proposed method is validated through a real-world case study for a horizontal directional drilling machine.

Suggested Citation

  • Zaifang Zhang & Danhua Xu & Egon Ostrosi & Li Yu & Beibei Fan, 2019. "A systematic decision-making method for evaluating design alternatives of product service system based on variable precision rough set," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1895-1909, April.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:4:d:10.1007_s10845-017-1359-6
    DOI: 10.1007/s10845-017-1359-6
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    References listed on IDEAS

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    1. V. Krishnan & Karl T. Ulrich, 2001. "Product Development Decisions: A Review of the Literature," Management Science, INFORMS, vol. 47(1), pages 1-21, January.
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    Cited by:

    1. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    2. Rui Wang & Xiangyu Guo & Shisheng Zhong & Gaolei Peng & Lin Wang, 2022. "Decision rule mining for machining method chains based on rough set theory," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 799-807, March.
    3. Zaifang Zhang & Darao Xu & Egon Ostrosi & Hui Cheng, 2020. "Optimization of the Product–Service System Configuration Based on a Multilayer Network," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    4. Tin-Chih Toly Chen & Yu-Cheng Wang & Chin-Hau Huang, 2020. "An Evolving Partial Consensus Fuzzy Collaborative Forecasting Approach," Mathematics, MDPI, vol. 8(4), pages 1-19, April.

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