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Human Factors Effects and Analysis in Maintenance: A Power Plant Case Study
Author(s) -
Sheikhalishahi Mohammad,
Azadeh Ali,
Pintelon Liliane,
Chemweno Peter
Publication year - 2017
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2065
Subject(s) - human reliability , risk analysis (engineering) , human error , reliability engineering , reliability (semiconductor) , task (project management) , control (management) , scheduling (production processes) , computer science , preventive maintenance , engineering , operations research , operations management , power (physics) , systems engineering , artificial intelligence , business , physics , quantum mechanics
This paper proposes a methodical approach for identifying and reducing human error in maintenance activities, the human factors effect and analysis. Human factors effect and analysis presents a roadmap for selecting significant human factors affecting maintenance management as well as the most effective solutions using cost–benefit analysis. Safety and operational consequences of each human factor are compared to preventive and recovery risk controls to select the preferred risk control method. Because human factor programs are not implemented in many maintenance departments, quantitative data are rare. Thus, expert judgment may help to compare potential solutions. In order to show the applicability of the proposed approach a power plant in Kenya is selected as a case study. Procedure usage, fatigue, knowledge and experience, and time pressure are identified as the most important human factors. Training, task planning /shift management, knowledge management, scheduling as well as incident report programs are the most cost‐effective solutions for performing human factors program. The proposed approach would improve system reliability by recognizing human related failures. Furthermore, unexpected incident and accident may be reduced having knowledge about potential risk factors. Copyright © 2016 John Wiley & Sons, Ltd.