A MODEL FOR DETERMINING OPTIMAL BATCH SIZES OF MULTI-FEATURED PRODUCTS WITH RANDOM PROCESSING ACCURACIES UNDER QUALITY AND COST CONSTRAINTS

Abstract

Determining optimal batch sizes in a production system has been a primary focus in the manufacturing sector. From the volume of research, it is well known that the batch size of a manufacturing process is significantly affected by several cost factors such as setup cost, order cost, and defective cost. In this paper, a model for determining the batch size for a multi-featured products production system is developed with consideration of quality and cost constraints under stochastically changing process accuracies. In determining the batch size of products, we consider tool capability and feature-based set-up accuracy. A mathematical structure of the model is presented and its applicability is demonstrated through illustrative examples.