HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process
Akide Cerci Ogmen () and
Ismail Ekmekci
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Akide Cerci Ogmen: Occupational Health and Safety Program, Institute of Science and Technology, Istanbul Commerce University, Istanbul 34854, Turkey
Ismail Ekmekci: Department of Industrial Engineering, Faculty of Engineering, Istanbul Commerce University, Istanbul 34854, Turkey
Sustainability, 2022, vol. 14, issue 17, 1-16
Abstract:
The assessment of human reliability is crucial in serious processes and operations, such as planned maintenance, unplanned maintenance, and troubleshooting in a coal-fired thermal power plant, as the nature of these processes poses significant threats. When the literature is examined, the evaluation of human reliability in any type of power plant, especially coal-fired thermal power plants, is limited. In order to fill this gap, we systematically assessed human reliability in an accident that occurred during a repair of a tube failure in a boiler in a coal-fired thermal power plant. The HEART (human error assessment and reduction technique) method was used in a hybrid way alongside the fuzzy AHP and SWARA (step weight assessment ratio analysis) methods. Although the HEART method is a practical, understandable, and easy-to-implement human reliability assessment method, the APOE (assessment of the proportion effect) value depends on the decision of a single decision maker. This study aimed to eliminate this deficiency and compare human error possibilities using HEART–fuzzy AHP and HEART–SWARA methods. This hybrid method can be used in the operation of all coal-fired thermal power plants and provides practical contributions to minimize human error.
Keywords: human reliability; HEART–fuzzy AHP; HEART–SWARA; the tube failure in the boiler process; coal-fired thermal power plant (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:17:p:10838-:d:902450
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