Environmental Assessment and Improvement of Factory Building Designs based on Generative Artificial Intelligence

The paper explores an innovative approach to evaluate the environmental impact of factory buildings at early design stages. Generative design, a cutting-edge computational technique, is employed to generate multiple factory building design alternatives based on user and case specific boundary conditions, e.g. related to material flow and space restrictions. This paper aims to integrate generative design principles with environmental assessment metrics to improve factory buildings for minimal environmental footprint, e.g. driven through energy demand. Thus, a framework that combines the generative factory design approach with key environmental assessment parameters is introduced. The effectiveness of generative design in enhancing the environmental performance of factory buildings is demonstrated with a case study. A comparative analysis of different designs highlights main influencing factors, as well as trade-offs and synergies between different manufacturing system performances and environmental oriented objectives. With that, the paper underlines the value of generative design as a transformative tool in sustainable factory design and provides actionable insights for architects, engineers, and policymakers aiming to develop greener industrial facilities.