Model-Based Diagnosis under Real-World Constraints

I report on my experience over the past few years in introducing automated, model-based diagnostic technologies into industrial settings. In particular, I discuss the competition that this technology has been receiving from handcrafted, rule-based diagnostic systems that has set some high standards that must be met by model-based systems before they can be viewed as viable alternatives. The battle between model-based and rulebased approaches to diagnosis has been over in the academic literature for many years, but the situation is different in industry where rule-based systems are dominant and appear to be attractive given the considerations of efficiency, embeddability, and cost effectiveness. Traditionally, industrial diagnostic systems have been handcrafted to reflect the knowledge of a domain expert. They take the form of if-then rules that associate certain forms of abnormal system behavior with faults that could have caused this behavior.