Fuzzy logic-based decision support system for automating ergonomics risk assessments |
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| Affiliation: | 1. Department of Mechanical Engineering, University of Alberta, 5th Floor, Donadeo Innovation Centre of Engineering, 9211 116 Street NW, Edmonton, Alberta, T6G 1H9, Canada;2. Department of Mechanical Engineering, University of Alberta, 10th Floor, Donadeo Innovation Centre of Engineering, 9211 116 Street NW, Edmonton, Alberta, T6G 1H9, Canada;1. Department of Occupational Health and Safety Engineering, Occupational Health and Safety Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran;2. Department of Occupational Health and Safety Engineering, Abadan University of Medical Sciences, Abadan, Iran;3. Department of Ergonomics, Research Center for Health Sciences, School of Public Health, Hamadan University of Medical Sciences, Iran;1. Department of Industrial Engineering, Tsinghua University, Beijing, 100084, China;2. School of Management, Shanghai University, Shanghai, 200444, China;1. Department of Industrial Engineering, Seoul National University, Seoul, South Korea;2. Department of Safety Engineering, Incheon National University, Incheon, South Korea;3. Institute for Industrial Systems Innovation, Seoul National University, Seoul, South Korea;1. Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA;2. Naval Medical Research Unit – Dayton, Wright-Patterson Air Force Base, Ohio, USA;3. Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA;4. Air Force Research Laboratory, 711th Human Performance Wing, Wright-Patterson Air Force Base, Ohio, USA;1. Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, 14260, USA;2. Farmer School of Business, Miami University, Oxford, OH, 45056, USA |
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| Abstract: | Workers in the modular construction industry are frequently exposed to ergonomic risks, which may lead to injuries and lower productivity. In light of this, researchers have proposed a number of ergonomics risk assessment methods to identify design flaws in work systems, thereby reducing ergonomic discomfort and boosting workplace productivity. However, organizations often disregard ergonomics risk assessments due to a lack of convenient tools and knowledge. Therefore, this study proposes a fuzzy logic-based decision support system to help practitioners to automatically and comprehensively assess the ergonomic performance of work systems. For comprehensive assessment of ergonomic risk, the proposed decision support system considers physical, environmental, and sensory factors. Specifically, the decision support system comprises eight fuzzy expert systems that output a composite risk score, called an “ergonomic risk indicator”, that indicates the overall level of ergonomic risk present in a given work system. The performance of the proposed decision support system is then evaluated using a real-world case study in a modular construction facility by comparing the results of the decision support system with the facility's occupational injury reports. The results prove the effectiveness of the decision support system. Overall, the decision support system is capable of generating a composite risk score, the ergonomic risk indicator, and the proposed high-level architecture and design represent significant contributions for the enhancement of health and safety in the modular construction industry. |
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| Keywords: | Ergonomics risk assessment Fuzzy expert system Decision support system Artificial intelligence Performance evaluation Modular construction |
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