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Analyzing Human Error in Municipal Water Systems Using Systematic Human Error Reduction and Prediction Approach SHERPA Method
Author(s) -
Behzad Fouladi Dehaghi,
Ali Rastin,
Maryam Malekzadeh,
Leila Ibrarahimi Ghavamabadi
Publication year - 2017
Publication title -
jundishapur journal of health sciences
Language(s) - English
Resource type - Journals
eISSN - 2252-0627
pISSN - 2252-021X
DOI - 10.5812/jjhs.59536
Subject(s) - human error , computer science , interview , task (project management) , non sampling error , error detection and correction , control (management) , action (physics) , reliability engineering , artificial intelligence , algorithm , engineering , physics , systems engineering , quantum mechanics , political science , law
Background: The perception that water treatment and supply systems are not safe against accident and human errors as well as disease outbreaks is growing. Many major events around the world have been attributed to human error. In general, human errors are defined as situations where planned series of mental or physical activities fail to achieve its desired result. Methods: This cross-sectional study was performed to predict human error in the Khorramabad water treatment plant. Human error in the telemetry control room as well as relevant units was assessed with standard charts, tables, and reference work sheets. At first, all different activities of the unit were considered after interviewing the workers as well as consulting with supervisors and also by hierarchical task analysis HTA. Then the SHERPA method was applied to identify potential human errors. Results: Seventy-nine human errors were identified in various job tasks. Results showed that 51.8% of them are action errors, 38.4% are checking errors, 7.59% are retrieval errors, 0.006% is communication errors, and 0% for selection errors. Conclusions: It can therefore be concluded that the most prevalent errors are checking and action errors. Thus, it is suggested that work instructions, staff training, and employing inspection operators to monitor the performances should be considered as a priority. Furthermore, it can be concluded that SHERPA is appropriate for many industries such as water treatment plants.

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