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Evaluation of Ergonomic Risks for Construction Workers Based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method

Author

Listed:
  • Yu Tao

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Hao Hu

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Jie Xue

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Zhipeng Zhang

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Feng Xu

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

Ergonomic risks critically impact workers’ occupational health, safety, and productivity, and thereby the sustainability of a workforce. In the construction industry, the physical demands and dynamic environment exposes workers to various ergonomic hazards. While previous research has mainly focused on postural risks, there is a need to broaden the scope to include more relevant factors and assess them systematically. This study introduces a multi-criteria decision framework integrating the Spherical Fuzzy Sets (SFSs) and Alternative Queuing Method (AQM) to evaluate and prioritize ergonomic hazards. First, SFSs are employed to quantify the linguistic expressions of experts, addressing the inherent vagueness and uncertainty. Then, an entropy-based objective weighting method is adopted to determine the criteria weights. Finally, AQM is utilized to generate the risk priority. The proposed method has been implemented in a real-life construction project, where “overexertion due to unreasonable task organization”, “hypertension and heart diseases”, and “existing WMSD record” are identified as the top three ergonomic hazards. Then, a thorough discussion of intervention strategies regarding different risk categories is presented to facilitate ergonomic interventions. This proposed decision support system can promote effective ergonomic risk management, benefiting workers’ health and well-being and contributing to the sustainable workforce development of the construction industry.

Suggested Citation

  • Yu Tao & Hao Hu & Jie Xue & Zhipeng Zhang & Feng Xu, 2024. "Evaluation of Ergonomic Risks for Construction Workers Based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:3950-:d:1390743
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    References listed on IDEAS

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    1. Wen Yi & Albert Chan, 2016. "Health Profile of Construction Workers in Hong Kong," IJERPH, MDPI, vol. 13(12), pages 1-15, December.
    2. Saeid Jafarzadeh Ghoushchi & Mohd Nizam Ab Rahman & Moein Soltanzadeh & Muhammad Zeeshan Rafique & Hernadewita & Fatemeh Yadegar Marangalo & Ahmad Rasdan Ismail, 2023. "Assessing Sustainable Passenger Transportation Systems to Address Climate Change Based on MCDM Methods in an Uncertain Environment," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    3. Lucia Botti & Martina Calzavara & Cristina Mora, 2021. "Modelling job rotation in manufacturing systems with aged workers," International Journal of Production Research, Taylor & Francis Journals, vol. 59(8), pages 2522-2536, April.
    4. Shraddha Palikhe & Mi Yirong & Byoung Yoon Choi & Dong-Eun Lee, 2020. "Analysis of Musculoskeletal Disorders and Muscle Stresses on Construction Workers’ Awkward Postures Using Simulation," Sustainability, MDPI, vol. 12(14), pages 1-13, July.
    5. Robert T. Clemen & Robert L. Winkler, 1985. "Limits for the Precision and Value of Information from Dependent Sources," Operations Research, INFORMS, vol. 33(2), pages 427-442, April.
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