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Design and Implementation of a Fuzzy Expert System for an Ergonomic Performance Assessment in Modular Construction Operations Using the DMAIC Approach
Employees in construction industries are often exposed to ergonomic risks that can result in injuries and decrease productivity. To prevent ergonomic injuries, appropriate ergonomic risk assessments must be used to detect ergonomic issues and change the ergonomics of workstations in the industry. The study’s importance arises from the lack of rapid, robust, and integrated systems for conducting ergonomic risk assessments. Thus, this study is aiming to design a Fuzzy Expert System (FES) to continuously evaluate the physical, environmental, and sensory ergonomic performance to minimize ergonomic risks, injuries and improve productivity. The DMAIC (Define, Measure, Analyze, Improve, and Control) methodology is used as a general structure to be integrated with the proposed FES. It supports identifying the standard ergonomic metrics and their practical tolerances, collection of relevant data from the industry, determination of linguistic scales, and fuzzy rules based on the collected data to determine the ergonomic performance of the industry. This proposed FES is expected to help the industry avoid the challenges of relying only on individuals’ subjective inputs while performing ergonomic assessments and eliminating miscommunications among teams in the decision-making process. Three important reasons to use FES in ergonomic performance evaluation are (1) rapid and accurate assessments based on knowledge database, (2) extraction of insights from the FES, (3) elimination of common psychological biases associated with ergonomic performance reviews. The developed system has been implemented in a modular construction industry and is expected to conduct a rapid ergonomic assessment to support an ergonomic intervention plan.
Design and Implementation of a Fuzzy Expert System for an Ergonomic Performance Assessment in Modular Construction Operations Using the DMAIC Approach
Employees in construction industries are often exposed to ergonomic risks that can result in injuries and decrease productivity. To prevent ergonomic injuries, appropriate ergonomic risk assessments must be used to detect ergonomic issues and change the ergonomics of workstations in the industry. The study’s importance arises from the lack of rapid, robust, and integrated systems for conducting ergonomic risk assessments. Thus, this study is aiming to design a Fuzzy Expert System (FES) to continuously evaluate the physical, environmental, and sensory ergonomic performance to minimize ergonomic risks, injuries and improve productivity. The DMAIC (Define, Measure, Analyze, Improve, and Control) methodology is used as a general structure to be integrated with the proposed FES. It supports identifying the standard ergonomic metrics and their practical tolerances, collection of relevant data from the industry, determination of linguistic scales, and fuzzy rules based on the collected data to determine the ergonomic performance of the industry. This proposed FES is expected to help the industry avoid the challenges of relying only on individuals’ subjective inputs while performing ergonomic assessments and eliminating miscommunications among teams in the decision-making process. Three important reasons to use FES in ergonomic performance evaluation are (1) rapid and accurate assessments based on knowledge database, (2) extraction of insights from the FES, (3) elimination of common psychological biases associated with ergonomic performance reviews. The developed system has been implemented in a modular construction industry and is expected to conduct a rapid ergonomic assessment to support an ergonomic intervention plan.
Design and Implementation of a Fuzzy Expert System for an Ergonomic Performance Assessment in Modular Construction Operations Using the DMAIC Approach
Lecture Notes in Civil Engineering
Walbridge, Scott (Herausgeber:in) / Nik-Bakht, Mazdak (Herausgeber:in) / Ng, Kelvin Tsun Wai (Herausgeber:in) / Shome, Manas (Herausgeber:in) / Alam, M. Shahria (Herausgeber:in) / el Damatty, Ashraf (Herausgeber:in) / Lovegrove, Gordon (Herausgeber:in) / Govindan, A. (Autor:in) / Li, X. (Autor:in)
Canadian Society of Civil Engineering Annual Conference ; 2021
Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021 ; Kapitel: 31 ; 409-421
30.05.2022
13 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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