The application of Additive Manufacturing in Construction (AMC) requires thorough iterative planning to ensure the manufacturability and quality of the printed outputs. Often in the early design stages, designers encounter incomplete data or knowledge gaps, presenting challenges in overcoming the complexity of AMC methods. The study proposed by (Li et al., 2022) introduces a Design Decision Support System (DDSS) integrated with Additive Manufacturing (AM) ontology, facilitating informed decision-making on AM methods. This research thereby integrates the AMC knowledge base and the Fabrication Information Modelling (FIM) framework (Slepicka et al., 2021) to develop a knowledge-driven planning method. This approach aims to minimize fabrication trial and error, and refine the design methodologies. This specifically involves retrieving appropriate process parameters through considering rheological behaviors of 3D concrete printing (3DCP) materials and providing a systematic assessment of reachability of the robot printer to estimate appropriate design scale; thus support the design decision in the early phase.     «

The application of Additive Manufacturing in Construction (AMC) requires thorough iterative planning to ensure the manufacturability and quality of the printed outputs. Often in the early design stages, designers encounter incomplete data or knowledge gaps, presenting challenges in overcoming the complexity of AMC methods. The study proposed by (Li et al., 2022) introduces a Design Decision Support System (DDSS) integrated with Additive Manufacturing (AM) ontology, facilitating informed decision...     »