Purpose This study aims to develop and evaluate a Scan-to-BIM (S2B) workflow that integrates building information modelling (BIM) to address facility management (FM) challenges caused by outdated and fragmented documentation, with an emphasis on improving spatial accuracy, semantic data quality and interoperability. Design/methodology/approach A five-phase workflow, comprising capture planning, field capture, point-cloud preparation, BIM modelling and validation and FM deliverables, was applied to an occupied undergraduate laboratory using structured-light scanning. The resulting BIM model was assessed for geometric accuracy, semantic enrichment and Industry Foundation Classes (IFC) compatibility to determine FM readiness. Findings The model achieved geometric deviations within approximately 3% for major architectural elements, with a root mean square error (RMSE) of 2.8 cm. Key FM parameters, including room identifiers, spatial hierarchies and asset groupings, were embedded and preserved during IFC export. The workflow improved documentation reliability, enhanced asset visibility and demonstrated feasibility under operational conditions. Research limitations/implications The study was limited to one scanning method and a single case site. Concealed services were only represented schematically. Broader testing and integration of automation tools are recommended. Practical implications The workflow supports FM tasks such as space auditing and maintenance planning, offering a potentially scalable, low-disruption pathway for digitalising university facilities. Originality/value This study contributes by repositioning S2B as an FM-oriented information workflow for educational buildings, rather than a purely geometric modelling exercise. The value lies in aligning established processes with FM information needs to support campus digital transformation.
Ng et al. (Sat,) studied this question.