LGPMI - An ontology-driven model for hospital equipment maintenance

Journal article

Mawloud Titah, Mohammed Abdelghani Bouchaala
Journal of Quality in Maintenance Engineering, Emerald Publishing Limited, 2024

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Cite

APA Click to copy
Titah, M., & Bouchaala, M. A. (2024). An ontology-driven model for hospital equipment maintenance management: a case study. Journal of Quality in Maintenance Engineering.

Chicago/Turabian Click to copy
Titah, Mawloud, and Mohammed Abdelghani Bouchaala. “An Ontology-Driven Model for Hospital Equipment Maintenance Management: a Case Study.” Journal of Quality in Maintenance Engineering (2024).

MLA Click to copy
Titah, Mawloud, and Mohammed Abdelghani Bouchaala. “An Ontology-Driven Model for Hospital Equipment Maintenance Management: a Case Study.” Journal of Quality in Maintenance Engineering, Emerald Publishing Limited, 2024.

BibTeX Click to copy

@article{titah2024a,
  title = {An ontology-driven model for hospital equipment maintenance management: a case study},
  year = {2024},
  journal = {Journal of Quality in Maintenance Engineering},
  publisher = {Emerald Publishing Limited},
  author = {Titah, Mawloud and Bouchaala, Mohammed Abdelghani}
}

Abstract

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.

Keywords:

Decision-support, Healthcare, Knowledge-based system, Maintenance, Rule-based reasoning,
Semantic web technologies, Domain knowledge, Knowledge inference