Disaster Prevention Through Intelligent Monitoring





catastrophes, monitoring, Bhopal, Texas City, Piper Alpha, Chernobyl, case studies


Despite various tools and systems that can monitor complex engineering environments, bad things still happen regularly in all types of engineering industries. An intelligent system designed to monitor certain indicators, regardless of engineering industry, that might predict catastrophes would ultimately reduce the potential for loss of human life and property.

In this article, 10 catastrophes were researched to identify their root causes and the various root cause combinations. These documented catastrophes covered a broad spectrum of engineering including oil, gas, nuclear, rail, air and space. The root causes identified in the investigation reports were grouped under 10 trait headings and their efficacy was tested using a qualitative fault tree of a credible catastrophic failure scenario. Each trait was adjusted to signify various levels of failure and fed into the prototype system representing the fault tree.

While near real-time monitoring and trend analysis was investigated and shown to support an intelligent system that might predict catastrophe, one of the surprising additional results from the research was highlighting the need to standardize the approach to investigative reports and audits of existing systems. Reporting in the same “technical language” and looking for specific condition levels for each of the traits could provide a true picture of asset condition and the required funding prioritization, as well as assisting the dissemination of findings to all engineering industries.

Author Biographies

Andrew Painting, Attis Engineering Solutions Ltd

Dr. Andrew Painting is the Director of the Attis Engineering Solutions Ltd. safety engineering consultancy and a Fellow of the Safety and Reliability Society. He spent 11 years before that working within Portsmouth dockyard, initially leading a team of safety engineers and finally as the Chief Engineer for the Naval base. Prior to that, he spent 23 years as a submariner in the Royal Navy. After 18 years of hands-on engineering, he started his academic training with a BSc in mechatronics and artificial intelligence, then earned an MSc in occupational and environmental health and safety management. Finally, he was awarded a Ph.D. for the design of “An Intelligent Monitoring System to Predict Catastrophic Incidents.”

David Sanders, University of Portsmouth

Dr. David Sanders leads the Systems Engineering Research Group and is the Engineering Research Degrees Coordinator at the University of Portsmouth. He is a Fellow of the Institution of Mechanical Engineers, Institution of Engineering Technology and the Higher Education Academy. His areas of research within the systems engineering research group include automation and robotics, computing and electronics, and environmental systems.”





How to Cite

Painting, A., & Sanders, D. (2017). Disaster Prevention Through Intelligent Monitoring. Journal of System Safety, 52(3), 23–29. https://doi.org/10.56094/jss.v52i3.118