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Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO

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  • Kandemir, Cagatay
  • Celik, Metin

Abstract

The error producing condition (EPC) values are decisive parameters of human error assessment and reduction technique (HEART). In order to conduct more effective and accurate safety analysis, the EPC values should be customized in accordance with the key aspects of the relevant disciplines. Since the maintenance and operational tasks in the ship engine room involve a vast number of particular actions, this study extends the current shipboard operations human reliability analysis (SOHRA) method by proposing marine engineering maintenance and operations specific error producing conditions (mmo-EPCs) via ship accident data. Moreover, the original human factor analysis and classification system for marine engineering operations (HFACS-MMO) is identified. By means of HFACS-MMO, marine maintenance and operations human reliability analysis (MMOHRA) is proposed. In the MMOHRA, the values of EPC5, EPC8, EPC12, EPC14, EPC16, EPC21, EPC32, EPC33 and EPC35 are substantially changed when comparing with similar approaches. A case study is also provided for benchmarking the proposed method. The findings of the case study show that the HEP results can change considerably with the MMOHRA. Since the mmo-EPCs are determined through obtained data from various ship accidents, MMOHRA can be utilized in safety practices regardless of ship types specifically in marine engineering field.

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  • Kandemir, Cagatay & Celik, Metin, 2021. "Determining the error producing conditions in marine engineering maintenance and operations through HFACS-MMO," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    • Handle: RePEc:eee:reensy:v:206:y:2021:i:c:s0951832020308048
    DOI: 10.1016/j.ress.2020.107308
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    6. Akide Cerci Ogmen & Ismail Ekmekci, 2022. "HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    7. Zhou, Jian-Lan & Yu, Ze-Tai & Xiao, Ren-Bin, 2022. "A large-scale group Success Likelihood Index Method to estimate human error probabilities in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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