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A framework with revised rough-DEMATEL to capture and evaluate requirements for smart industrial product-service system of systems

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  • Zhiwen Liu
  • Xinguo Ming

Abstract

Smart industrial product-service system of systems (SiP-S3) is a new extension of industrial PSS via smart technology and SoS (system of systems) engineering. A framework with revised rough-DEMATEL method is proposed to capture and evaluate requirements for SiP-S3. From the various interactions in value stream mapping of SiP-S3, business, functional and non-functional requirements can be captured and converged into SiP-S3 requirements. Due to the interrelation between requirements of SiP-S3 and uncertainty of expert judgments, rough-DEMATEL is adopted but is revised in two aspects. Generally, SiP-S3 requirement items are plentiful, a set of programming code for rough set approximation is firstly given to reduce manual calculation burden. Moreover, compared to multiple operators of modified-CFCS (converting fuzzy values into crisp scores) plus SVL (single vector-length), a feasible and simpler operator of AVL (average vector-length) on rough-prominence and rough-relation is firstly devised to prioritise requirements. As such, roughness can be remained till at the end of calculation procedure to avoid uncertain assessment information loss. Surface mount technology (SMT) is not trivial in electronic manufacturing service industry, an illustrative case study of SMTE-S3 (SMT equipment-service system of systems) is demonstrated to verify feasibility and potential of proposal methodological framework.

Suggested Citation

  • Zhiwen Liu & Xinguo Ming, 2019. "A framework with revised rough-DEMATEL to capture and evaluate requirements for smart industrial product-service system of systems," International Journal of Production Research, Taylor & Francis Journals, vol. 57(22), pages 7104-7122, November.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:22:p:7104-7122
    DOI: 10.1080/00207543.2019.1577566
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    Cited by:

    1. Yuan Chang & Xinguo Ming & Xianyu Zhang & Yuguang Bao, 2023. "Modularization Design for Smart Industrial Service Ecosystem: A Framework Based on the Smart Industrial Service Identification Blueprint and Hypergraph Clustering," Sustainability, MDPI, vol. 15(11), pages 1-33, May.
    2. Marco Bertoni, 2019. "Multi-Criteria Decision Making for Sustainability and Value Assessment in Early PSS Design," Sustainability, MDPI, vol. 11(7), pages 1-27, April.
    3. Amjad Hussain & Muhammad Umar Farooq & Muhammad Salman Habib & Tariq Masood & Catalin I. Pruncu, 2021. "COVID-19 Challenges: Can Industry 4.0 Technologies Help with Business Continuity?," Sustainability, MDPI, vol. 13(21), pages 1-25, October.
    4. Qi-Zhen Zhang & Shan Jiang & Ran Liu & Hu-Chen Liu, 2020. "An Integrated Decision-Making Model for Analyzing Key Performance Indicators in University Performance Management," Mathematics, MDPI, vol. 8(10), pages 1-16, October.
    5. Sayem Ahmed & Hasin Md. Muhtasim Taqi & Yeasir Iqbal Farabi & Mohiuddin Sarker & Syed Mithun Ali & Bathrinath Sankaranarayanan, 2021. "Evaluation of Flexible Strategies to Manage the COVID-19 Pandemic in the Education Sector," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 22(2), pages 81-105, December.
    6. Hasin Md. Muhtasim Taqi & S. M. Shafaat Akhter Nur & Sheak Salman & Tazim Ahmed & Sudipa Sarker & Syed Mithun Ali & Bathrinath Sankaranarayanan, 2023. "Behavioural factors for Industry 4.0 adoption: implications for knowledge-based supply chains," Operations Management Research, Springer, vol. 16(3), pages 1122-1139, September.

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