4.1 Article

Multi-Criterion-Based Qualitative Comparative Analysis of Root Cause Methods: Application to Deepwater Horizon Oil Spill

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JOURNAL OF FAILURE ANALYSIS AND PREVENTION
卷 21, 期 5, 页码 1662-1682

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SPRINGERNATURE
DOI: 10.1007/s11668-021-01212-9

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Root cause analysis; Accident investigation; Deepwater horizon; Qualitative comparison; Decision-making

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Root cause analysis (RCA) is a process used to identify potential causes of accidents, with different RCA tools having their own pros and cons. This study compared five RCA tools using the Deepwater Horizon oil spill as a case study, finding that different tools have their own strengths and weaknesses in isolating root causes.
Root cause analysis (RCA) is a sequentially structured process that can be used for identifying the potential root causes for a particular accident, failure of which can lead to the recurrence of a similar event. Several techniques have emerged over the years as generic standards for identifying the root causes; each RCA tool and methodology has its pros and cons in its application. However, there has been no objective comparison between these various techniques for their applicability apart from the stated qualitative differences; this research gap forms as the base motivation for this research work. This study has identified five RCA tools based on popularity, the complexity of use, industrial application, and structure with the ultimate aim of providing extensive comparative results based on fundamental characteristics, flexibility and robustness, and finally, the scoring sheet. To provide objective results, the comparative study was focused on the catastrophic Deepwater Horizon oil spill. The results from the reality charting and fault tree analysis proved to be more derivative and explanatory in isolating the root causes; however, it was also found to be complicated in comparison with the other tools. On the other hand, fishbone provided results that were easier to infer but not entirely satisfactory for scenarios involving a complex interaction of multiple contributory factors. Selecting the right causal analysis tool is vital for obtaining relevant results with no excessive time consumption and less distractive factors in both proactive and reactive studies.

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