Lifecycle Management of Complex Engineering Building Systems in the Context of Construction Industry Digitalization

Digitalization has changed how complex engineering building systems are designed, commissioned, operated, and decommissioned. These systems cover mechanical, electrical, plumbing, fire protection, security, and data network subsystems. Building Information Modeling (BIM) is now widely used at the design stage, yet the operations and maintenance phase still runs on fragmented, largely reactive practices that add cost and downtime. This paper examines how an integrated digital platform that combines BIM-linked digital twins, Internet of Things (IoT) sensor networks, and predictive analytics can support continuous lifecycle management of these systems. The study draws on a systematic literature review, a comparative analysis of maintenance strategies, and four international case studies, and it measures the effect on cost and reliability. Organizations that adopt integrated predictive approaches report 15-40% less unplanned downtime and 10-25% lower total maintenance costs than those relying on conventional preventive or reactive strategies. The paper sets out a five-layer platform architecture intended as a working framework for engineering project managers and facility operators. The findings are aimed at project engineers, facility managers, construction technology researchers, and policymakers writing digital construction standards.

lifecycle management, BIM, MEP systems, digital twin, IoT, predictive maintenance, construction digitalization, building automation, facility management, engineering systems

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