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2019 | OriginalPaper | Buchkapitel

Process Mining for Maintenance Decision Support

verfasst von : Adithya Thaduri, Stephen Mayowa Famurewa, Ajit Kumar Verma, Uday Kumar

Erschienen in: System Performance and Management Analytics

Verlag: Springer Singapore

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Abstract

In carrying out maintenance actions, there are several processes running simultaneously among different assets, stakeholders, and resources. Due to the complexity of maintenance process in general, there will be several bottlenecks for carrying out actions that lead to reduction in maintenance efficiency, increase in unnecessary costs and a hindrance to operations. One of the tools that is emerging to solve the above issues is the use Process Mining tools and models. Process mining is attaining significance for solving specific problems related to process such as classification, clustering, discovery of process, prediction of bottlenecks, developing of process workflow, etc. The main objective of this paper is to utilize the concept of process mining to map and comprehend a set of maintenance reports mainly repair or replacement from some lines on the Swedish railway network. To attain the above objective, the reports were processed to extract out time related maintenance parameters such as  administrative, logistic and repair times. Bottlenecks are identified in the maintenance process and this information will be useful for maintenance service providers, infrastructure managers, asset owners and other stakeholders for improvement and maintenance effectiveness.

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Metadaten
Titel
Process Mining for Maintenance Decision Support
verfasst von
Adithya Thaduri
Stephen Mayowa Famurewa
Ajit Kumar Verma
Uday Kumar
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-7323-6_23