Automated abnormality detection

Recent years have seen a huge growth in the complexity of manufacturing plant, and the measurement and control systems that it uses. Process control, condition indicating, performance measuring and QC parameters are routinely measured, howver the prupose to which this data is put are only two-fold: 1) keep the plant operating within a control regime and 2) assess the condition, performance and efficiency of the operating plant and hence of the process.
The project will investigate the feasibility of developing a novel automated algorithmic approach to abnormality detection (i.e. a simple and automated means of assessing whether a plant is deteriorating, drifting in terms of efficiency/performance or operating in a sub-optimal manner.