Volume 9, Issue 2 (6-2019)                   J Health Saf Work 2019, 9(2): 105-112 | Back to browse issues page

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Karimie S, Mohammadfam I, Mirzaei Aliabadi M. Human Errors Assessment in the one of the control rooms of a petrochemical industrial company using the extended CREAM method and BN. J Health Saf Work 2019; 9 (2) :105-112
URL: http://jhsw.tums.ac.ir/article-1-6075-en.html
1- Department of Occupational Health Engineering, Occupational Health and Safety Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
2- Department of Health, Safety and Environment Management, Occupational Health and Safety Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran , mohammadfam@umsha.ac.ir
3- Department of Health, Safety and Environment Management, Occupational Health and Safety Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
Abstract:   (4190 Views)
Introduction: Nowadays, human error is one of the main causes of incidents in the industry. One of the vital characteristics of modern industries is that the precise control of key parts of the process is performed by operators from central control rooms, so an error by the control room staff can be disastrous. The present study is aimed at identifying and evaluating human errors in the control room of the petrochemical industry.  
Material and Methods: This is a descriptive-analytic case study that was conducted in a control room of the petrochemical industry. In this research, firstly by using hierarchical task analysis (HTA), the tasks in the control room were identified and analyzed. Then, using the extended CREAM method, possible human errors were identified, their cognitive category was determined, and their probabilities were calculated using a new approach based on BN.
Results: The results of the study showed that the most prevalent control modes for the Boardman and the senior board man were strategic and scrambled modes with error probabilities of 0.136 and 0.171, respectively.
Conclusion: According to the results obtained in the modeling section, BN can be proposed as an approach with high processing accuracy and also high accuracy in modeling human errors and problems with high input parameters affecting the output parameter.
Full-Text [PDF 650 kb]   (2069 Downloads)    
Type of Study: Research |
Received: 2019/05/30 | Accepted: 2019/05/30 | Published: 2019/05/30

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