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In order to guarantee high operational availability, the modular industrial equipment requires frequent maintenance, which oftentimes is carried out by the manufacturer. Reports about service technician's activities are stored in maintenance histories. Manufacturers of such equipment would benefit significantly from analysis of recorded maintenance and fault histories for planning of maintenance activities, offering scalable service contracts and finding reasons for product faults. This paper introduces a methodology that supports the interpretation of the maintenance histories to allow the manufacturers the analysis and optimization of maintenance operations. The methodology interprets the maintenance histories as sequences of events, containing meaningful patterns. Tailored data mining algorithms are applied, that provide causality details going beyond the results of standard techniques. The paper uses the example of maintenance reports of gas analytic equipment.
Date of Conference: 26-29 July 2011