Assessing the Economic Performance of Continuous Sampling Plans

Abstract

In manufacturing operations, items can be produced in lots or on a continuous (item-by-item) basis. Most sampling plans used in statistical quality control are designed for lot-by-lot production and inspection. In the case of item-by-item inspection, continuous sampling plans are widely used. The CSP-1 is the most widely recognized and used continuous sampling plan. Several authors have addressed the selection process for the two CSP-1 parameters, i and f. Previous research used an economic model to demonstrate that CSP-1 parameter selection is irrelevant for in-control manufacturing processes, i.e., if the process proportion nonconforming is constant, then either no inspection or 100% inspection is optimal. In this paper, a stochastic process that provides a realistic model for process changes over time is considered. An economic model of CSP-1 performance for such a process is defined and evaluated using a simulation model. Despite choosing experiments to give the CSP-1 a great chance of performing better than no inspection or 100% inspection, the experimental results show only occasional and minor improvement over no inspection and 100% inspection. These results question the validity of the CSP-1 as a sampling approach.

Key Words:

• Continuous sampling plans
• economic model
• simulation

Additional information

Notes on contributors

Amit Kumar Shee

Amit Kumar Shee received his M.S. degree in industrial engineering from the University of Arkansas. He is currently employed as a replenishment manager for Wal-Mart Stores, Inc. in Bentonville, Arkansas.

C. Richard Cassady

Richard Cassady is an Associate Professor in the Department of Industrial Engineering at the University of Arkansas. Prior to joining the faculty at UofA, he was on the faculty at Mississippi State University. He received his Ph.D., M.S. and B.S. all in industrial and systems engineering from Virginia Tech. His primary research interests are in repairable systems modeling, reliability engineering, statistical quality control and sports applications of operations research. He is a Senior Member of IIE, and a member of ASEE, ASQ, INFORMS and SRE. He is also a member of the RAMS Management Committee.