Life Cycle Assessment of 3D-Printed Building Materials Towards Sustainability-Driven Optimization and Environmental Impact Analysis Using Computational Intelligence Techniques (2025-09)¶

The rising demand for sustainable solutions in 3D-printed construction necessitates advanced methods for evaluating and optimizing material performance across environmental, economic, and functional dimensions in the process. Most of the conventional material selection methods and LCAs are transparent, scalable, lack functionality for handling uncertainty, and are ineffective in fast-changing fields like 3D-printed construction. It contributes to this effort by designing an AI-based multi-criteria decision-making framework that is integrated with life cycle sustainability assessment tools for the optimization of 3D-printed building materials. Sustainable construction materials are increasingly critical due to the accelerated adoption of 3D printing, which introduces complex trade-offs among emissions, energy use, durability, and recyclability that conventional assessment tools are ill-equipped to handle in the process.