Optimizing sustainability performance through component commonality for multi-generational products

Increasing frequency of new product introduction reduces the potential to implement closed-loops and repurpose serviceable end-of-use resources, causing sub-optimal resource utilization. Furthermore, it hinders the transition to sustainable manufacturing and circular economy. Although careful planning of inter-generational design compatibility allows implementing sustainable closed-loops even in fast-paced multi-generation systems, designers currently lack the product sustainability performance (PSP) forecasting methods required for such planning. Thus, this paper presents a new design methodology that forecasts and maximizes the closed-loop dynamic PSP by identifying the optimal component-level commonality between successive design generations. The proposed method employs the Norton-Bass diffusion model to forecast multi-generation demand and utilizes the Non-dominated Sorting Genetic Algorithm II to identify the optimal design configurations. The representative PSP objectives used in this work are: maximization of manufacturer gross profit, minimization of total greenhouse gas emissions, and maximization of product's functional value (for customer). The optimized intergenerational component commonality significantly improved all three objectives considered. The results further demonstrate the potential PSP improvements by optimizing the market introduction timing of successive product generations to increase closed-loop resource management effectiveness.