Model-based Diagnosis and Manufacturing

Given the increasing use of digital control systems in manufacturing plants, the theoretical potential for error monitoring and diagnosis has significantly increased. However, conventional monitoring systems often still suffer from the problems of past decades where automated error recognition is nonexistent and the monitoring system restricts itself mainly to communications and signal processing. As a result, the diagnostic load in case of malfunctions is left to the operator. We describe a model-based diagnosis system that is integrated into the control of a manufacturing plant by providing an additional layer atop the existing monitoring system. The diagnosis system provides flexible, high-level and resilient diagnosis capability and can directly use the monitoring system's reports as observations for the diagnosis process. We also discuss general principles of developing models for this domain and show a simple model used in our current diagnosis/monitoring prototype system.