by Dr A.D. Painting and Dr D. Sanders
Despite various tools and systems that can monitor complex engineering environments, bad things happen regularly in all types of engineering industries. An intelligent system that could monitor certain indicators no matter the complexity of the engineering industry and could predict the potential situations that may lead to catastrophic mishaps and could reduce loss of human life and property.
In this article, 10 catastrophic mishaps were researched to identify their root causes and root cause combinations. These mishaps can be found across a broad spectrum of engineering fields, including oil, gas, nuclear, rail, air and space. The failure types identified in the investigation reports were grouped under common trait headings and their efficacy was tested using a qualitative fault tree of credible catastrophic failure scenarios. The traits were adjusted to signify various levels of failure and the prototype system readily identified their impact.
While near real-time monitoring and trend analysis was investigated and shown to produce an intelligent system that could predict catastrophe, one of the surprising outputs was the need to standardize investigative reports and audits of existing systems. Reporting in the same “technical language” and looking for specific condition levels for each of the traits would, without doubt, provide a true picture of asset condition and allow for funding prioritization, as well as the dissemination of findings to all engineering industries.
Journal of System Safety (2016), Vol 52(3), pages 23-30.
