Integration Of Bim for Clash Detection and Performance Optimization in Multi-Storey Building Design

Abstract

This review examines recent technological advancements in the integration of Building Information Modeling (BIM) for clash detection and performance optimization in multi-storey building design. The analysis highlights a clear shift from fragmented 2D drafting toward intelligent, data-driven coordination workflows that significantly reduce rework, enhance design accuracy, and improve interdisciplinary communication. BIM-enabled clash detection systems are shown to identify hard, soft, and workflow clashes early in the design cycle, thereby minimizing costly on-site modifications and schedule disruptions. Emerging computational enhancements, including generative design, deep learning–based collision detection, transfer learning frameworks, and multi-objective optimization algorithms, further strengthen BIM’s capability to automate conflict identification and generate performance-optimized design alternatives. Integration with artificial intelligence enhances clash prediction accuracy, reduces false positives, and improves early-stage design reliability. Additionally, sustainability-oriented BIM workflows demonstrate notable reductions in material waste, embodied carbon, and energy inefficiencies through coordinated routing and optimized spatial allocations. Decision-support matrices, clash prioritization frameworks, and structured coordination performance indicators contribute to improved transparency and consistency across design reviews. Overall, the findings confirm that BIM functions as a comprehensive digital ecosystem that enhances constructability, boosts lifecycle efficiency, and supports predictive, optimization-driven decision-making for complex multi-storey building projects.