The rising price of agricultural products leads to frequent change of feed recipe, which can cause a high number of reprocessing batches, elevating the overall cost of production. In this study, we proposed an artificial neural network to predict production rate. The conversion of production rate to production cost, the tips for data collection as well as tips for implementation of new feed cost estimation are also discussed. Being able to estimate production rate enables feed mills to improve their operations. In this study, we elaborate its application to feed scheduling (although the applications can be extended to other aspects such as productivity improvement, which goes beyond the scope of this particular study).
artificial neural network; feed cost estimation; feed scheduling
