Order-Reduced Dynamic Decoupling Approach for Performance Evaluation of Multitype and Small-Batch-Based Serial Lines With Adjustments and Resets

In the existing literature, extensive investigations focus on evaluating the performance of production systems that typically assumed to be operating under rigid production mode. Mass production as well as single type of products is the representative characteristics of this production mode. However, by applying prompt equipment adjustments and resets, modern production lines are capable of making different products in small batches with varying processing requirements. This is referred to as flexible manufacturing mode. With the flexible manufacturing mode, which has been widely used in recent years, real-time performance evaluation and prediction, small-batch-based real-time scheduling, and management of such systems, etc., are having important research significance. In this article, by considering adjustments and resets on serial production lines with multitype and small-batch-based production, the transient performance evaluation problem is studied. Specifically, for the system with machines having the Bernoulli reliability model and buffers having finite capacities, the mathematical model is formulated first. Then, we develop a Markovian model and a computational procedure for evaluating various system real-time performance indicators, such as production rates and completion times of different batch-based production tasks, etc. In addition, an order-reduced dynamic decoupling approach is proposed to approximate system real-time performance with high accuracy and computational efficiency. Finally, theoretic properties of the system under the flexible manufacturing mode are discussed.