Digital-Twin-Based Lifecycle Intelligent Construction for Prefabricated Buildings: A Data-Driven Project Management Framework and Empirical Validation

With the advancement of industrialized prefabricated construction and intelligent building technologies, construction project management faces challenges including low construction efficiency, difficult cost control, uneven resource allocation, and insufficient construction risk management. This paper proposes a digital twin and data-driven full lifecycle intelligent construction optimization model that integrates BIM modeling, construction planning management, cost control, resource scheduling, and risk assessment to achieve multi-objective optimization and quantitative management of construction processes. By establishing a cost-efficiency-quality optimization model and conducting data analysis and process scheduling for key indicators, the study validates the effectiveness of the optimization model in shortening construction periods, reducing costs, improving resource utilization, and enhancing risk control. Experimental results demonstrate that the optimization model provides quantifiable and actionable decision support while ensuring construction quality, showcasing strong theoretical and practical value. Additionally, this paper conducts in-depth analysis of indicator correlations, offering scientific basis for construction parameter optimization, project management strategy formulation, and promotion of intelligent construction methods. It provides a systematic and scalable technical solution for full lifecycle management of prefabricated buildings. The research findings not only offer references for construction enterprises' intelligent construction practices but also provide methodological guidance for the digital and intelligent development of future construction project management.