Prediction and analysis of human errors on the Boiler operator using PHEA method: A case study in dairy industry

Gholam Abbas Shirali; Zeinab Nezamodini; Mahboubeh Movafagpour

Jentashapir Journal of Cellular and Molecular Biology

Official Journal of Ahvaz Jundishapur University of Medical Sciences

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Prediction and analysis of human errors on the Boiler operator using PHEA method: A case study in dairy industry

Authors:

Gholam Abbas Shirali¹,

Zeinab Nezamodini²,

Mahboubeh Movafagpour^3,*

1Assistant professor, Depatment of Occupational Health, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

2Lecturer, Depatment of Occupational Health, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

3MSc Student of Occupational Health, Depatment of Occupational Health, School of Health, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Jentashapir Journal of Cellular and Molecular Biology:Vol. 4, issue 5; e94116

Published online:Oct 30, 2013

Article type:Research Article

Received:May 20, 2019

Accepted:Dec 12, 2012

How to Cite:Gholam Abbas ShiraliZeinab NezamodiniMahboubeh MovafagpourPrediction and analysis of human errors on the Boiler operator using PHEA method: A case study in dairy industry.4(5):e94116.

Abstract

Background: Although advances in technology and increased use of production machinery have decreased manpower role, many industrial sites have exposed human resources to various dangers and a small mistake can often cause irreversible injuries. The purpose of this study was to analyze certain jobs and to detect the possible human errors in the steam boiler room of dairy industry using the PHEA method.

Materials and Methods: In this study data were collected through two steps: In the first step, using observation, investigation, and documentation techniques, all tasks of involved employees in process were identified. Then, with respect to the obtained results, critical tasks were selected to analyze the human errors. In the second step, the error description (and consequences resulted from it) were determined. Several action plans for mitigation and elimination of human errors are also recommended.

Results: The results have shown that most errors were characterized as "control is not true," with 110 repetitions, and the second type of errors "does not do the control" were obtained with 108 repetitions. For identified errors, 11 cases with 453 frequencies were identified. Most human-error causes were found as the forgotten, negligence and busy factors with the frequencies of 117,111, 111, respectively.

Conclusion: The results showed that PHEA technique can be used as an effective method to detect human errors and assess the consequences of the hazards resulted from the errors in the complex tasks.

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