The scheduling of material requirements at a factory to maximize profits.or productivity is a difficult mathematical problem. The stochastic nature of most production setups introduces additional complications as a result of the uncertainty involved in vendor reliability and processing times. But in developing the descriptive model for a system, a true representation can only be attained if the variability of these elements is considered.

Here we present the development of a normative model based on a new type of descriptive model which considers the element of stochasticity. The arrival time of an assembly part from a vendor is considered to be a normally distributed random variable. We attempt to optimize the system with regard to work-in-process inventory using a dynamic programming algorithm in combination with a heuristic procedure. The decision variable is the prescribed assembly part delivery date. The model is particularly suitable for application in low volume assembly lines, where products are manufactured in discrete batches.