An ontology model for maintenance strategy selection and assessment

Jimenez, Juan José Montero; Vingerhoeds, Rob A.; Grabot, Bernard; Schwartz, Sébastien

doi:10.1007/s10845-021-01855-3

Cited by 25 publications

(29 citation statements)

References 37 publications

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“…(2023) initiated the development and dissemination of a set of coherent reference ontologies to advance software and data interoperability, focusing on the potential of ZDM to transform manufacturing systems and their socio-technological interactions. Montero Jiménez et al. (2023) introduced an ontology model for Maintenance Strategy Selection and Assessment (OMSSA) in the industrial domain, facilitating reuse and integration with other ontologies.…”

Section: Literature Reviewmentioning

confidence: 99%

An ontology-driven model for hospital equipment maintenance management: a case study

Titah,

Bouchaala

2024

JQME

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Purpose This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.Design/methodology/approach The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.Findings Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.Originality/value An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

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Section: Literature Reviewmentioning

confidence: 99%

An ontology-driven model for hospital equipment maintenance management: a case study

Titah,

Bouchaala

2024

JQME

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“…However, ontologies can be also used to enhance maintainability in a system. In [19], an ontology model is proposed to facilitate maintenance strategies selection and assessment. And in [20], ontologies are used for data accessing in order to enhance system maintainability.…”

Section: Maintainability Ontologiesmentioning

confidence: 99%

Ontology-Based Solution for Handling Safety and Cybersecurity Interdependency in Safety-Critical Systems

Varvarigou¹,

Espes²,

Bersano³

2023

Latest Advances and New Visions of Ontology in Information Science

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In case, safety-critical systems face an anomaly (either intentional or not), safety and cybersecurity impact humans and environment. Thus, they affect each other and so they are considered as interdependent. An ontology-based solution for safety is needed to handle this interdependency. We propose a new safety ontology for Network Function Virtualization (NFV) framework which is able to cover reliability, availability, maintainability, and integrity-related breakdown types, since they interact and influence safety according to ENISA. Our ontology allows us to have a uniformized representation of the potential anomalies that a system and its elements can face. Based on this representation, a decision-making process takes place to avoid potential conflicts between safety and cybersecurity in order to best handle their interdependency. The results of our implementation show that our ontology handles the safety and cybersecurity interdependency and has little impact on decision-making time, which makes it an effective methodology for NFV framework.

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“…Therefore, a careful consideration should be kept in order to assure the homogeneity of criticality analysis and asset-related decisionmaking. In this regard, ontologies are showing potentialities to identify the most suitable maintenance strategies by selecting and assessing machine criticality [26,27]. In particular, ontologies, models related to symbolic AI, are used in the scientific literature and industry to set up common and agreed-upon terminologies between stakeholders.…”

Section: Basics Of Multi-attribute Criticality Analysismentioning

confidence: 99%

An ontological modelling of multi-attribute criticality analysis to guide Prognostics and Health Management program development

Polenghi

Roda

Macchi

et al. 2022

Auton. Intell. Syst.

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Digital technologies are becoming more pervasive and industrial companies are exploiting them to enhance the potentialities related to Prognostics and Health Management (PHM). Indeed, PHM allows to evaluate the health state of the physical assets as well as to predict their future behaviour. To be effective in developing PHM programs, the most critical assets should be identified so to direct modelling efforts. Several techniques could be adopted to evaluate asset criticality; in industrial practice, criticality analysis is amongst the most utilised. Despite the advancement of artificial intelligence for data analysis and predictions, the criticality analysis, which is built upon both quantitative and qualitative data, has not been improved accordingly. It is the goal of this work to propose an ontological formalisation of a multi-attribute criticality analysis in order to i) fix the semantics behind the terms involved in the analysis, ii) standardize and uniform the way criticality analysis is performed, and iii) take advantage of the reasoning capabilities to automatically evaluate asset criticality and associate a suitable maintenance strategy. The developed ontology, called MOCA, is tested in a food company featuring a global footprint. The application shows that MOCA can accomplish the prefixed goals; specifically, high priority assets towards which direct PHM programs are identified. In the long run, ontologies could serve as a unique knowledge base that integrate multiple data and information across facilities in a consistent way. As such, they will enable advanced analytics to take place, allowing to move towards cognitive Cyber Physical Systems that enhance business performance for companies spread worldwide.

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An ontology model for maintenance strategy selection and assessment

Cited by 25 publications

References 37 publications

An ontology-driven model for hospital equipment maintenance management: a case study

An ontology-driven model for hospital equipment maintenance management: a case study

Ontology-Based Solution for Handling Safety and Cybersecurity Interdependency in Safety-Critical Systems

An ontological modelling of multi-attribute criticality analysis to guide Prognostics and Health Management program development

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