Digital Design Quality Management: The Theory of Faults

Built environment and infrastructure designs are produced in complex information systems. Managing this complexity poses a significant challenge; data scarcity and bias are substantial obstacles. This paper addresses the gap in data availability by mining building information modeling (BIM) meta-databases. Two case study databases are studied and assessed through various analytical tools, including network modeling, statistics, entropy, fast Fourier transform (fft), and information constraint (IC). Through analytical and empirical investigation, insights into the morphology, characteristics, failures, causes, and trajectories of design information systems are derived, showcasing that complex systems can be retroactively deciphered and predicted to a certain extent. This study acknowledges design errors as social and psychological phenomena and proposes behavioristic and systemic remedies for addressing design faults. Applying design quality-control management tools, risk assessment, and responsibility allocation becomes feasible, enabling proactive and real-time corrective actions. This research contributes a theoretical framework and practical methodologies as well as the application of data analysis tools to design quality control management, addressing both the information gap and the complexity challenge.