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Applying Answer Set Optimization to Preventive Maintenance Scheduling for Rotating Machinery

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Rules and Reasoning (RuleML+RR 2022)

Abstract

Preventive maintenance (PM) of manufacturing units aims at maintaining the operable condition of the production line while optimizing the maintenance timing and the loss of productivity during maintenance operations. The lesser studied type of preventive maintenance understands a production line as a single machine with multiple components of different maintenance needs. This is relevant when rotating machinery is deployed, e.g., in the paper and steel industries, in the mass production of raw materials consumed by other businesses. A failure in any stage of the production line has the potential of making the entire machine inoperable and enforcing a shutdown and corrective maintenance costs. This work gives an abstract formalization of PM scheduling for multi-component machines as an optimization problem. To provide a lower bound for the complexity of the optimization problem, we prove that the underlying decision problem is NP-complete for varying-size multi-component machines and scheduling timelines. Besides the formalization, the second main contribution of the paper is due to the practical need to solve the problem in industrial applications: the work gives the first encoding of the PM scheduling problem using Answer Set Optimization (ASO). Some preliminary experiments are conducted and reported to set the scene for further algorithm development.

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Acknowledgment

The support from the Academy of Finland within the project AI-ROT (#335718) is gratefully acknowledged.

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Correspondence to Anssi Yli-Jyrä .

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Yli-Jyrä, A., Janhunen, T. (2022). Applying Answer Set Optimization to Preventive Maintenance Scheduling for Rotating Machinery. In: Governatori, G., Turhan, AY. (eds) Rules and Reasoning. RuleML+RR 2022. Lecture Notes in Computer Science, vol 13752. Springer, Cham. https://doi.org/10.1007/978-3-031-21541-4_1

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  • DOI: https://doi.org/10.1007/978-3-031-21541-4_1

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