<scp>MCDM</scp> approaches in <scp>BIM</scp> ‐driven decision‐making models in enhancing energy efficiency for sustainable <scp>3D</scp> ‐printed infrastructure in the construction industry

Abstract Selecting optimal materials and construction methods is vital for sustainable infrastructure. This review explores how integrating Multi‐Criteria Decision‐Making (MCDM) methods Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Fuzzy Logic with Building Information Modeling (BIM) enhances decision‐making in Fused Deposition Modeling (FDM)‐based additive manufacturing. Unlike earlier reviews that treat BIM, Additive Manufacturing (AM), or MCDM separately, this work uniquely examines AI‐augmented MCDM models driven by real‐time BIM data, improving lifecycle assessment and sustainability. Recent case studies report material waste reductions of 30%–40%, surface quality improvements of 10%–30%, and labor cost savings of 15%–25% using these integrated approaches. We also discuss interoperability solutions like IFC‐AM extensions and middleware that bridge BIM and AM tools. By comparing MCDM methods and highlighting empirical benefits, this review provides practical insights and outlines future research directions to advance digital, resource‐efficient, and low‐carbon construction.