The construction industry’s drive toward digitalization and offsite practices has highlighted the potential of integrating Building Information Modeling (BIM) with Design for Manufacturing and Assembly (DfMA) principles. While this integration offers opportunities for addressing challenges in productivity, sustainability, and cost-effectiveness, the implementation of DfMA principles often creates complex interactions with functional requirements and other criteria. Existing studies employing Multi-Criteria Decision Making (MCDM) techniques, while valuable, typically focus on isolated criteria pairs and lack automated integration with design tools. This research develops an automated optimization framework for internal wall systems, chosen for their significant impact on project costs, sustainability, and varying performance requirements. The methodology combines expert knowledge through interviews with computational design optimization, creating a seamless workflow between decision-making and design automation. Using Rhino.Inside to integrate Grasshopper with Revit, and leveraging Tunny plugin to employ NSGA-II algorithm, the framework generates Pareto-optimal solutions balancing multiple criteria. A case study of a Melbourne townhouse demonstrates the framework’s effectiveness, showing significant improvements in decision-making efficiency and design automation. This research advances both theoretical understanding and practical implementation of BIM-DfMA integration, aligned with Construction 4.0 principles.
Keywords Design for manufacture and assembly, Building information modelling, Internal wall partitions, Optimization, Automation