Lean Management Framework for Healthcare Facilities Integrating BIM, BEPS and Big Data Analytics

Gökhan Demirdöğen, Zeynep Işık, Yusuf Arayici

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
15 Downloads (Pure)

Abstract

An increase in the usage of information and communication technologies (ICT) and the Internet of Things (IoT) in Facility Management (FM) induces a huge data stack. Even though these data bring opportunities such as cost savings, time savings, increase in user comfort, space optimization, energy savings, inventory management, etc., these data sources cannot be managed and manipulated effectively to increase efficiency at the FM stage. In addition to data management issues, FM practices, or developed solutions, need to be supported with the implementation of lean management philosophy to reveal organizational and managerial wastes. In the literature, some researchers performed studies about awareness about building information modeling (BIM)-FM, and FM-related data management problems in terms of lean philosophy. However, the comprehensive solution for effective FM has not been investigated with the application of lean management philosophy yet. Therefore, this study aims to develop an FM framework for healthcare facilities by considering lean management philosophy since more stable workflow, continuous improvement, and creating more value to customers will help to deliver a more acceptable solution for the FM industry. Within this context, the integration of BIM, Building Energy Performance Simulations, and Big Data Analytics are proposed as a solution. In the study, the Design Science Research (DSR) methodology was followed to develop the FM framework. Depending on the DSR methodology, two scenarios were used to investigate the issue in a real healthcare facility and develop the FM framework. The developed framework was evaluated by four experts, and the revisions of the proposed framework were realized.
Original languageEnglish
Article number7061
JournalSustainability
Volume12
Issue number17
DOIs
Publication statusPublished - 29 Aug 2020

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