Gispert, D E; Yitmen, I; Sadri, H and Taheri, A (2025) Development of an ontology-based asset information model for predictive maintenance in building facilities. Smart and Sustainable Built Environment, 14(3), pp. 740-757. ISSN 2046-6099
Abstract
Purpose: The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process. Design/methodology/approach: A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights. Findings: The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector. Practical implications: The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry. Originality/value: The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | asset information model; building facility management; digital twins; ontology; operation and maintenance; predictive maintenance |
| Index terms: | building industry, investigation, energy efficiency, platform, methodology, validation, digital twin, data-driven decision-making, interview, operation and maintenance, predictive maintenance, literature review, ontology |
| Subjects: | digital engineering, digital design, research methods, maintenance engineering, data collection methods, data analysis and analytics, sustainability and energy, professional development, education and knowledge transfer, industry analysis, decision analysis |
| Topics: | Risk Management, Sustainability, Digital Applications, Business Strategy, Information Management, Research Practice |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here