iAssist – Explainable AI-Based Eco-Design Support

Engineers determine around 80 % of a product’s future costs and emissions during the design phase, such as material efficiency, production waste, manufacturing effort and assembly. The problem is that existing support in design engineering lacks systematic integration of quantifiable sustainability metrics into the design of sheet metal products. This research addresses the gap by evaluating iAssist, an explainable AI-based eco-design support that integrates sustainability metrics directly into the design of sheet metal products, such as material thickness, laser cutting waste, weld seams and part count. iAssist combines CAD-based model analysis, automated detection of eco-design optimization potential, and tailored feedback using a structured design knowledge base. It thereby enables real-time, explainable design support. In three empirical studies involving 510 sheet metal designs, the rate of eco-design alternatives increased from 5% without support to 51% with the use of iAssist. Results indicate that combining predictive assessment with real-time, explainable feedback enables engineers to make more informed and sustainable design decisions. ... mehriAssist contributes a scalable approach for embedding sustainability into early-phase engineering workflows.