journal article·2020-03

The need for an internationally recognised standard for engineering failure analysis

Nigel K. Booker, Richard E. Clegg, Peter Knights, J.D. Gates

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Abstract

At present, the outcome of failure analysis is an opinion, albeit a considered one, based on the best facts available informed by a series of non-standardised diagnostic tests and experience. Acknowledging that there are many tools that have been developed and implemented successfully by failure analysts over many years, this paper specifically identifies the need for:a. an internationally recognised failure analysis standard; and.b. diagnostic accuracy guidelines.It is hypothesised that a standard is required to make the process repeatable so that the results can be peer reviewed, lessons learned, and the outcome be objective. Through a thorough literature review and the analysis of 132 failure analysis case studies, various failure analysis methodologies were identified, and diagnostic accuracy methodologies appraised. It was concluded that currently a failure analysis methodology is typically chosen by the analysts without a critical selection process. The methodology chosen is then applied according to their interpretation, which in turn yields a diagnostic decision. Consequently, the chosen methodology may not be the most accurate or expedient, which has the potential to increase the risk and cost of the decision-making process. It is recommended that a structured approach to decision analysis be established, leading to a set of diagnostic accuracy guidelines, which, once adopted and implemented by the engineering fraternity, allows the further development of an internationally recognised failure analysis standard, thereby reducing the risk of misdiagnosis and repetition of the failure.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Reliability and Maintenance Optimization · Quality and Safety in Healthcare · Software Reliability and Analysis Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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