From Theory to Practice: Model-Based Diagnosis in Industrial Applications



Roxane Koitz Franz Wotawa


Due to the increasing complexity of technical systems, accurate fault identification is crucial in order to reduce maintenance costs and system downtime. Model-based diagnosis has been proposed as an approach to improve fault localization. By utilizing a system model, possible causes, i.e. defects, for observable anomalies can be computed. Even though model-based diagnosis rests on solid theoretical background, it has not been widely adopted in practice. The reasons are twofold: on the one hand it requires an initial modeling effort and on the other hand a high computational complexity is associated with the diagnosis task in general. In this paper we address these issues by proposing a process for abductive model-based diagnosis in an industrial setting. Suitable models are created automatically from failure assessments available. Further, the compiled system descriptions reside within a tractable space of abductive diagnosis. In or- der to convey the feasibility of the approach we present results of an empirical evaluation based on several failure assessments.

How to Cite

Koitz, . R. ., & Wotawa, F. . (2015). From Theory to Practice: Model-Based Diagnosis in Industrial Applications. Annual Conference of the PHM Society, 7(1).
Abstract 135 | PDF Downloads 139



Model-based diagnosis, model based reasoning, Failure Modes and Effect Analysis (FMEA), Fault identification

Technical Research Papers