Building an Ontology for Intelligent Maintenance Systems and Spare Parts Supply Chain Integration

Silva, Thiago Regal da; Pereira, Carlos Eduardo

doi:10.3182/20140824-6-za-1003.02217

Cited by 7 publications

(1 citation statement)

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“…This ontology is suitable for reliability analysis and might be reused, but no wide use or links to maintenance scheduling or any other services is considered in the actual version of the ontology. Saalmann et al proposed an integrated approach combining existing domain ontologies of various interacting systems for manufacturing systems [9,10]. Although the domain is different, the idea is similar, to some extent, to some of this paper's aims.…”

Section: Related Workmentioning

confidence: 92%

Supporting the Management of Rolling Stock Maintenance with an Ontology-Based Virtual Depot

Louadah,

Papadakis,

McCluskey

et al. 2024

Applied Sciences

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The railway industry forecasts growth in passenger and freight traffic over the next 30 years. This places additional demands on rolling stock depot facilities, many of which were designed and built before the modern age of information technology. This paper explores the potential of improving the efficiency and effectiveness of rolling stock maintenance management to meet the challenges of the near future, by utilising advanced computing techniques. The objective of the work is to create optimised maintenance plans for a fleet of trains, considering optimal use of resources. As a “glue” for joining up functions and operations, a generic Depot and Vehicle ontology (called the Virtual Depot) is introduced. The ontology captures the structures, relationships, and attributes of objects in the Depot (rolling stock, sensors, depot assets, tools, resources, and staff). The ontology is populated with example company and fleet-specific knowledge using an automated knowledge acquisition method. This paper describes the systematic method for the creation of a Virtual Depot. Two particular aspects are discussed in detail—knowledge acquisition of fleet-specific information obtained from a manufacturer’s Vehicle Maintenance Instruction manuals and the construction of a short-term scheduling process within the Virtual Depot. Our evaluation considers the integrative aspects of the method, demonstrating how the ontological structure and its acquired specific information informs and benefits the scheduling process, in particular with respect to schedule optimisation. Results from an initial case study show there is significant potential to optimise short-term maintenance schedules, and the ability to automatically consider resource availability in short-term scheduling is demonstrated.

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Section: Related Workmentioning

confidence: 92%