Typically the operating policy for the inventory control system for a commodity is developed independent of the operating policy for the quality control system for that commodity and vice versa. In many circumstances, these systems are dependent on one another. A cost model that combines a fixed order quantity inventory control system with a Bayesian quality control system for a lot-by-lot attribute acceptance sampling plan is presented along with an algorithm to obtain the operating parameters for the combined systems. Behavior of the combined systems is investigated, and the costs and operating policy determined using this model are compared with the costs and operating policy determined when there is no integration of the two systems and when there is partial integration of the two systems. There are significant cost savings obtained by using the operating policy developed under the combined systems over the operating policy derived from the separate systems.