Human factor risk assessment of a maintenance operation in offshore process system

Noroozi, Alireza (2013) Human factor risk assessment of a maintenance operation in offshore process system. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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It is known that "human error" is the primary cause of the majority of incidents occurring in process activities. Such incidents can lead to unacceptable outcomes. Each year, there are billions of dollars lost and many injuries/deaths occurring as a result of human error which could have been avoided. Human factors play an important role in causation of these human errors leading to losses. Human factor is the information about human characteristics and behavior controlling human performance. Human errors are inevitable due to the noticeable role of human in operation, maintenance, analysis, decision making, and expert judgments, particularly in complex systems. To reduce the human error, the methods of Human Error Probabilities (HEPs) have been identified. Each technique has its own advantages and disadvantages and may need to be tailored for use within a specific scenario. The focus of this research is to develop comprehensive methodologies to estimate the HEPs in pre and post-maintenance procedures of process facilities. It also develops a risk-based methodology to investigate the reliability of human performance in harsh and cold environments. The methods "Success Likelihood Index Method (SLIM) and Human Error Assessment and Reduction Technique (HEART) HEART" have been used for this purpose. Using HEART methodology, the HEP in different scenarios in an offshore platform is estimated. Also, the high-risk activities in pre and post maintenance of process equipment are identified and the HEPs are reduced through a risk-based decision- making methodology. -- SLI methodology is used to calculate the HEP of the procedures for removing process components from service and returning the equipment to service as a possible failure scenario. Consequences and the individual risks are assessed for each component, and then the overall risk is estimated by adding these individual risks. Also, the HEP is assessed by integrating the SLIM with the Technique for Human Error Rate Prediction (THERP) to generate the nominal HEP data when sufficient information is not available.

Item Type: Thesis (Doctoral (PhD))
Item ID: 11150
Additional Information: Includes bibliographical references.
Department(s): Engineering and Applied Science, Faculty of
Date: 2013
Date Type: Submission
Library of Congress Subject Heading: Process control; Human engineering; Industrial safety.

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