Performance Evaluation of Closed Tree-Structured Assembly Systems

Abstract

Assembly systems are very common in manufacturing environments. In such systems, certain machines require more than one part type before they can start processing. Our paper presents a practical stochastic model for evaluating the performance of closed-loop assembly systems. This evaluation is difficult because of synchronization delays and the large state space required to capture the interaction of the flow of parts among the various subassemblies. We present an approximate, but computationally efficient, aggregation/disaggregation algorithm to compute the system throughput and mean queue lengths for both the matched and unmatched WIP inventory components. The aggregation computes the conditional system throughput as a function of the number of jobs in the system, whereas the mean queue lengths are obtained by disaggregation. Application of our algorithm reveals several salient operational insights, such as the increase in queue length towards the downstream machines or the concavity of the assembly system throughput with respect to the total number of kanbans.

Additional information

Notes on contributors

Jishnu Hazra

Jishnu Hazra is a Professor of Operations Management at the Indian Institute of Management in Bangalore, India. He received a B.Tech. in Mechanical Engineering from the Indian Institute of Technology and a Ph.D. from the William E. Simon Graduate School of Business Administration of the University of Rochester. His main research interest is in modeling manufacturing systems and operations management.

Abraham Seidmann

Abraham Seidmann is the Xerox Professor and Areas Coordinator of Computers and Information Systems, Management Science and Operations Management at the William E. Simon Graduate School of Business Administration at the University of Rochester, Rochester, NY. Professor Seidmann is the author of numerous research articles and is a Department Editor on Interdisciplinary Management Research and Applications in Management Science. He is also an Associate or Area Editor for IIE Transactions, International Journal of Flexible Manufacturing Systems, Production Planning and Controls, Journal of Intelligent Manufacturing, and Production and Operations Management. His current research and consulting activities include Strategic Manufacturing Systems, Business Process Reengineering, Information Economics, Stochastic and Performance Modelling. Professor Seidmann has consulted with many leading industrial corporations and presented research or executive seminars on four continents.