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Predicting human reliability based on probabilistic mission completion time using Bayesian Network

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  • Asadayoobi, N.
  • Taghipour, S.
  • Jaber, M.Y.

Abstract

This study considers the characteristics of a worker performing a sequence of tasks in a mission by developing a Bayesian Network model to predict reliability and mission completion time, the two measures of overall performance. The mission is broken down into tasks of different types, some of which may not be repeated back-to-back. A orker's initial task performance, learning, fatigue, and stress are the factors that affect the overall performance, and they vary by worker and task type'. Those characteristics and the task sequence plan are incorporated into a Bayesian Network to measure the performance of each task and, subsequently, the mission. Taking the task sequence plan into account adds a new dimension to the Bayesian Network as it counts the number of repetitions performed for each type of task, which allows linking the performance, learning, fatigue, and stress levels of a preceding task to a succeeding one. The developed model is general and can be applied to different real-life settings that are stressful and labour intensive. A numerical analysis is conducted to study how a worker's characteristics affect her/his reliability and the mission duration. The results are discussed, and managerial insights are presented.

Suggested Citation

  • Asadayoobi, N. & Taghipour, S. & Jaber, M.Y., 2022. "Predicting human reliability based on probabilistic mission completion time using Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:reensy:v:221:y:2022:i:c:s0951832022000060
    DOI: 10.1016/j.ress.2022.108324
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    References listed on IDEAS

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    4. Jo, Wooseok & Lee, Seung Jun, 2024. "Human reliability evaluation method covering operator action timing for dynamic probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
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    6. Wallius, Eetu & Klock, Ana Carolina Tomé & Hamari, Juho, 2022. "Playing it safe: A literature review and research agenda on motivational technologies in transportation safety," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    7. Tian-yuan, Ye & Lin-lin, Liu & He-wei, Pang & Yuan-zi, Zhou, 2023. "Bayesian Networks based approach to enhance GO methodology for reliability modeling of multi-state consecutive-k-out-of-n: F system," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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