Offsite construction (OSC) is attracting increasing attention from both industry and academia due to its benefits, such as improved productivity and quality, as well as reduced waste. However, the current building panelization design in OSC is a time-consuming and experience-based manual process, and the generated panelization design may result in unbalanced manufacturing processes. One reason is that the prefabrication of building components involves a highly variable product mix and there is a lack of a computational framework to evaluate panelization design. The objective of this research is, thus, to propose a BIM-based generative framework that automatically generates the design of production components with the aim of improving production productivity. This framework consists of a building information extraction module, a generative design algorithm, and a simulation-based performance evaluation model. The building information extraction module is designed to extract building component information from a BIM model and classify building components into different production groups in accordance with functionalities and materials. The generative design algorithm is then developed to formulate panelization design alternatives in consideration of the structural, production, and logistics constraints. On this basis, the generated panelization designs are quantitatively assessed by a simulation-based evaluation model in terms of productivity. A case study was used to verify and validate the framework. This research contributes to the body of knowledge by a computational framework of building panelization design, which leverages the generative design algorithm and BIM-simulation integration for optimized panelization design.
Exploiting Generative Design for Multi-Material Inkjet 3D Printed Cell Instructive, Bacterial Biofilm Resistant Composites
