The comparative study of evaluating human error assessment and reduction technique and cognitive reliability and error analysis method techniques in the control room of the cement industry

Document Type : Original Article

Authors
Amin Babaei Pouya
Ehsanollah Habibi
Department of Occupational Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
10.4103/2277-9183.157708
Abstract
Aims: The present study aimed to evaluate the assessment methods of human errors and compare the results of these techniques in order to introduce the precise method of human error assessment, and recognize the factors affecting the occurrence of these errors. Materials and Methods: This case study was done at three workstation control room of a cement industry in 2014. After determining the responsibilities and critical jobs by hierarchical task analysis, cognitive reliability and error analysis method (CREAM) and human error assessment and reduction technique (HEART) were used in order to analyze the human errors. Results: The results showed that in the CREAM method, the highest probability of error occurrence is related to monitoring and control (operator) with a probability of 0.207, and that of in the HEART method, is related to control signs (operator) with a probability of 0.416. The number of errors detected by CREAM and HEART method were 85 and 80, respectively. Time and cost of applying the CREAM methods were 235 h and 1175($), while those in the HEART techniques were 215 h and 1075($). Conclusion: We concluded that the highest probability of calculated errors relates to "monitoring and control (operator)," "controlling warning signs (operators)," and "cooperation in solving the problem (supervisor)" for both techniques. By considering the time and cost factors, HEART has superiority, while CREAM is better due to its extensive evaluation and the number of detected errors.

Keywords

International Journal of Environmental Health Engineering (IJEHE)
Volume 4, May
Spring 2015
Pages 1-5

  • Receive Date 30 January 2023