With the development of agriculture and animal husbandry in China, numerous small and micro feed processing enterprises have been established. These industries primarily operate on a make-to-order basis, customizing feed compositions according to customer orders. For each order, companies must clean the entire processing units—including machines and production lines for raw material input, crushing, mixing, granulation, and cooling—before processing the next order. This requirement results in significant losses of raw feed materials and increases cleaning costs and time due to inefficient setup operations. Moreover, since the operators often lack formal education and training in operations management, optimizing order-processing sequences to enhance operational efficiency and profitability is challenging. To address these issues, this study adopted a simple @ risk simulation software, which can be run in Microsoft Excel, to develop a task sequence determination model aimed at minimizing cleaning costs in feed processing plants. Using actual operational data, a comparative analysis was conducted of five feasible classification-processing sequences, suggested by the technical manager and on-site experts. This analysis took into account the actual conditions of the factory and the processing temperatures that influence order sequences. The model is implementing in a Chinese cooperative animal feeding company that typically handles a mix of customer orders, including rabbit feed, ruminant, and pig feed, both with and without additives. The empirical results will be available in June 2024.