نوع مقاله : پژوهشی
تازه های تحقیق
عنوان مقاله English
نویسندگان English
The safe and reliable operation of process industries largely depends on human reliability in performing safety-critical tasks, particularly under emergency conditions. Emergency response scenarios are among the most important approaches for enhancing organizational preparedness against industrial accidents; therefore, improving their execution process is of significant importance. Despite the development of various Human Reliability Assessment methods, previous studies have mainly focused on estimating human error probabilities, with limited attention to identifying key performance influencing factors and translating assessment results into practical improvement actions. This study proposes a process improvement framework based on Human Reliability Assessment, named DMAIC-HRA. The proposed framework was applied to a toxic and hazardous gas leak emergency response scenario in an oil refinery up to the stage of developing improvement actions. An integrated SLIM–SHERPA approach was developed to assess human reliability by combining human error identification with reliability estimation. The results indicated that the overall human reliability of the investigated process was 87.09%. Among the seventeen analyzed activities, the highest human error probability was related to the “Notification to the Control Center” activity (0.1148), while the lowest was associated with the “Interview” activity (0.0048). Based on the assessment findings, corrective actions were proposed to improve the emergency response process. The proposed framework provides a systematic approach for identifying human performance weaknesses, reducing the likelihood of human error, and enhancing safety management in high-risk process industries. Although the case study results may not be directly generalizable to other organizations, the proposed framework can be adapted for assessing and improving various organizational processes.
کلیدواژهها English
Copyright © Fereshteh Mashhadi, Mohammadreza Vasili, Seyed Mohammad Kazemi, Mehdi Jahangiri, Mahdi Karbasian
License
This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.
