Given the dynamics of the competitive market and changing customer needs, quality plays a key role in meeting customer requirements, and delivering high-quality products is essential for the survival and growth of manufacturing organizations. In this paper, process planning and advanced scheduling are considered, where scheduling is performed based on the orders received by the system. The production system has flexible machines and operators, and orders must be scheduled according to the current status of the machines and available operators so that, by assigning appropriate machines and operators, quality-related costs are minimized. To achieve the desired quality, the Taguchi quality loss function is developed by linking the quality characteristics of operations to the assigned operator and machine. Since the orders have precedence-required operations and, in one aspect, are similar to multiple traveling salesman problems, providing an exact mathematical model for these problems is often complex. Moreover, when dealing with flexible machines and operators, this complexity increases. In most works related to integrated process planning and scheduling, the mathematical models presented (because they define, for operations, a set of binary ordered pairs indicating precedence or non-precedence between operations) lack efficiency for solving with optimization software. Therefore, in this study, the problem is modeled with a new approach, and the problem is solved using GAMS software. For larger-scale problems, given the existing complexities, a genetic algorithm is used.