Process planning has a guiding role in the construction of intelligent manufacturing systems. However, in the current research on process planning, most of the studies only consider the processing time, ignoring the fact that choosing different processing machines and processing routes will change the qualified rate of products, which in turn affects the expected return. In this chapter, a mixed-integer linear programming model based on a process network diagram is constructed to solve the processing scheme with the highest expected return by integrating the processing time and the qualified rate of products. For processing time, the model considers the impact of the transfer time between two machines; for the qualified rate of products, the model considers the impact of the coupling relationship between adjacent processes. On this basis, the model’s objective function is a novel weighted value that combines processing time and product conformity to fully account for the compounded effects of processing time and product conformity on expected returns. The model provides a comprehensive view of their compound effects on expected returns. It also provides a comprehensive solution to improve the efficiency and quality of smart manufacturing systems. In the simulation experiments, compared with the mathematical model that only considers the processing time, the model can effectively calculate the processing route with higher expected returns, providing a new scheme for process planning.