Identifying emerging failure phenomena in complex systems through engineering data mapping

This paper addresses the issues involved in visualizing patterns in data sets by providing examples of interesting maps from the past, indicating some of the maps currently in use, and speculating on how these visual maps might be developed further and used in the future to discover problems in complex systems before they lead to failure. Guidance is proposed as to how to explore and map data from different technical perspectives in order to evoke potentially significant patterns from reliability data. The techniques presented have been developed by combining approaches to common cause failure (CCF) classification with multidimensional scaling (MDS) to produce a new method for exploratory engineering data mapping.