BIM-enabled parametric framework for multi-criteria decision-making in energy and life cycle cost analysis of 3D-printed buildings

The rapid growth of 3D-printed construction offers significant potential to accelerate delivery and reduce material waste. However, quantitative evidence linking envelope design decisions to long-term energy and economic performance remains limited. This study addresses the limited understanding of how envelope design influences energy and economic performance in fully and partially 3D-printed residential buildings. It aims to develop a Building Information modelling parametric framework to evaluate and optimize building envelope configurations based on integrated energy and life cycle cost performance. The methodology combines parametric modeling in Autodesk Revit, energy simulation using Autodesk Insight, and Life Cycle Cost Analysis in accordance with ISO 15686-5. A full factorial design is applied to assess variations in wall systems, roof systems, and window-to-wall ratios, with results synthesized using the Simple Additive Weighting method. Applied to a single-family case study in Rio de Janeiro, results show that Energy Use Intensity ranges from 201.8 to 257.1 kWh/m 2 yr. Matched-pair comparisons indicate that double-wall systems reduce energy demand by approximately 10.4–11.6% compared with equivalent single-wall configurations, while the combined optimization of wall system, roof system, and glazing ratio achieves an overall EUI reduction of 21.5% between the worst and best-performing configurations. The optimal design combines double walls, a wood frame insulated roof, and 40% glazing. The study provides a practical decision support framework for optimizing energy efficient and cost effective envelope designs in 3D-printed construction. The contribution of this study lies in applying a BIM based factorial workflow to evaluate envelope level design alternatives for fully and partially 3D-printed residential configurations in a hot humid Brazilian context, integrating energy simulation, LCCA, and MCDM to support early stage lifecycle oriented design decisions.