| خلاصه مقاله | Abstract
Introduction: human errors are important factor in industrial incidents and can happen in all organizational level, In order to control human errors Should attended to identify the types and causes of errors and reduce the probability of their occurrence in the future by providing appropriate solutions. The purpose of this study was predictive and human error analyze among the unit members of producing possess, in an Urmia syringe plant.
Methodology: This study was descriptive-analytic that was done in one of Urmia syringe plant in 2015. After identifying the tasks of working operators, work tasks operators injection, printing, assembling and packaging was selected as important and sensitive tasks.The tasks of jobs were analyzed by using Hierarchical Task Analysis (HTA) then human error related to each task was identified with the help of checklist PHEA (predictive human error analysis). Finally, frequency and type of them was obtained by software SPSS-16.
Results:175 errors from between the 30 main task included of technical engineers, injection, print, assembling, primary packaging, secondary packaging, final packaging operators and sterile operators was evaluated. Human errors are included;103 errors concern to function errors, 25 errors concern to inspecting error, 10 errors concern to information recovery, 4 errors concern to information transaction, 15 errors concern to selection of suitable alternative and 18 errors concern to sequence. High Risk of exposure with errors found in sterile operators. Forgetting to perform an action (A3) was detected as the highest frequency of errors.
Conclusion: Since that human error cannot be eliminated completely, so that should be used the proper techniques to identify and evaluate them and finally, preventive solutions will be recommending by analyzing this errors which is including;engineering and management controls and use of protective equipment. Human errors can be analyzed in every job and be recommended the strategies to reduce them by using of predictive and human errors analysis method (PHEA). |