A multi-objective optimization method for engineering change paths of complex products considering a multi-process complex network

This study addresses the optimization of change propagation paths in complex product engineering, where multiple disciplines and heterogeneous knowledge sources are involved. In such settings, design, production, and modification processes are often simultaneous, parallel, and collaborative, while the knowledge driving these changes is extensive, dynamic, and unstructured. To manage these challenges, a multi-objective optimization method is proposed within a multi-process complex network. A multi-stage network is constructed covering product design, process planning, and manufacturing, and an optimization model is developed considering change propagation intensity, total cost, and carbon emissions. The model is solved using the non-dominated sorting genetic algorithm III (NSGA-III) algorithm, and its feasibility and effectiveness are validated through a case study on engineering changes in a household refrigerator.