Production adjusting method based on the predicted distribution of production and inventory using a dynamic Bayesian network

In general, production quantities and goods delivered are changed randomly, and then the total stock is also changed randomly. This article deals with the production and inventory control of an automobile production parts line using a dynamic Bayesian network. A Bayesian network indicates the quantitative relations between individual variables by conditional probability. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the network. Moreover, an adjusting rule for the production quantities to maintain the probability of the lower and upper bound values of the total stock at certain values is shown.