Queuing approximations for capacity planning under common setup rules

Abstract

We consider the problem of estimating the resulting utilization and cycle times in manufacturing settings that are subject to significant capacity losses due to setups when switching between different product or part types. In particular, we develop queuing approximations for a multi-item server with sequence-dependent setups operating under four distinct setup rules that we have determined to be common in such settings: first-in-first-out, setup avoidance, setup minimization and type priority. We first derive expressions for the setup utilization and overall utilization, and use Kingman’s well-known approximation to estimate the average cycle time at the station under each setup rule. We test the accuracy of the approximations using a simulation experiment, and provide insights on the use of different setup rules under various conditions.

Keywords:

• Queuing approximations
• capacity planning
• setup rules

Additional information

Notes on contributors

Esma S. Gel

Esma S. Gel is an associate professor of industrial engineering in the School of Computing, Informatics and Decision Systems Engineering (CIDSE) at Arizona State University. Dr. Gel holds a BS degree in industrial engineering from Middle East Technical University, Turkey, and MS and PhD degrees in industrial engineering from Northwestern University, obtained in 1995 and 1999, respectively. Her research focuses on the use of stochastic modeling and control techniques for the design, control and management of operations in various settings, with emphasis on manufacturing and service systems, business and logistics processes, and health care systems. Dr. Gel’s work has been funded by the National Science Foundation as well as several industrial partners such as Intel and Mayo Clinic. She is a former INFORMS Vice President and served on the INFORMS Board of Directors.

John W. Fowler

John W. Fowler is the Motorola Professor of Supply Chain Management in the W.P. Carey School of Business at Arizona State University. His research interests include discrete event simulation, deterministic scheduling, multi-criteria decision making, and applied operations research with applications in semiconductor manufacturing and healthcare. He has published over 130 journal articles and over 100 conference papers. He was the Program Chair for the 2002 and 2008 Industrial Engineering Research Conferences, Program Chair for the 2008 Winter Simulation Conference (WSC), and Program Co-Chair for the 2012 INFORMS National Meeting. He was the founding Editor-in-Chief of IIE Transactions on Healthcare Systems Engineering and currently serves as a Healthcare Operations Management Departmental Editor. He is also an editor of the Journal of Simulation and Associate Editor of IEEE Transactions on Semiconductor Manufacturing and the Journal of Scheduling. He is a Fellow of the Institute of Industrial and Systems Engineers (IISE), served as the IIE Vice President for Continuing Education, is a former INFORMS Vice President, and served on the WSC Board of Directors.

Ketan Khowala

Ketan Khowala received his MS and PhD degrees in industrial engineering from Arizona State University in 2003 and 2012, respectively. Since obtaining his graduate degrees, Ketan has been working at leading firms in the high-tech manufacturing sector, driving supply chain operations, implementing operational management and logistics tools, and improving critical processes for cost, quality, and resource effectiveness. His projects at On Semiconductor, Apple, and more recently, Google, have involved a wide range of mission critical projects in manufacturing capacity modeling, inventory optimization, demand scenario analysis, and management of new product supply chains.