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Digital Twin in Facility Management Operational Decision Making and Predictive Maintenance

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Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 (AISI 2022)

Abstract

The facility management industry is progressively influenced by digital technologies that observe data from control automation structures and sensor networks. Developments in digital technology, such as the digital twin, provide an elevated depiction of buildings and their possessions by assimilating the digital and physical worlds. This report explores gaps, trends and patterns in the property management subdivision and adds to digital and automated clarifications for building administration. The interplay between building systems, building information management, and intelligent information control of multidimensional models are only a few of the various research fields examined in this paper. More academics are absorbed in using digital twins to accomplish their data and open novel study topics in Facility Management (FM) and Building Information Modeling (BIM). Seventy-seven academic journals on the use of digital twin technology in the Facility Management industry were located and categorized using selection criteria and a thorough bibliometric search across many databases. The study included a wide range of topics, comprising digital twins in facility lifecycle managing, digital twin information integration criteria, user-centered building design, preventative maintenance, digital twin semantics for facility conservation, and digital twin-based human information. The results show that before the FM sector can deploy digital twins, information standardization needs to be addressed. To facilitate future research based on this assumption, this paper offers a theoretical framework for using digital twins in facility management.

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Correspondence to Ala’a Ahmad .

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Ahmad, A., Alshurideh, M. (2023). Digital Twin in Facility Management Operational Decision Making and Predictive Maintenance. In: Hassanien, A.E., Snášel, V., Tang, M., Sung, TW., Chang, KC. (eds) Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022. AISI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-031-20601-6_38

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