A Quality Cost Model to Determine Optimal Policies for Purchased Components

Abstract

This study develops a technique for predicting purchasing quality costs and studying their behavior as random variables. The resulting model extends prior research that treats purchasing costs deterministically or not at all, thereby providing a valuable decision and planning tool for companies that are placing an increasing reliance on purchased components. The model was tested in the field at a small defense contractor. Test results suggest that purchasing costs can be reduced by using the model to select the lowest cost policy from a set of three alternatives.

• purchasing quality costs
• random variables
• simulation

Additional information

Notes on contributors

Edward D. Arnheiter

Edward D. Arnheiter is an assistant professor in the Lally School of Management and Technology at Rensselaer Polytechnic Institute. Prior to beginning his academic career, Arnheiter spent 11 years in industry as an operations management practitioner, in both the defense sector and in consumer products manufacturing. He held managerial positions with several major companies including General Electric Defense Systems, Spalding Sports Worldwide, and Titleist and Foot-Joy Worldwide.

Arnheiter has taught numerous courses in advanced quality management, managerial statistics, and manufacturing systems management. He received a doctorate in industrial engineering and operations research from the University of Massachusetts at Amherst. He may be contacted at the Lally School of Management and Technology, Rensselaer at Hartford, 275 Windsor Street, Hartford, CT 06120-2991; 860-548-2430; Fax: [phone]; E-mail: [email protected].

Richard J. Giglio

Richard J. Giglio is a professor in the department of mechanical and industrial engineering at the University of Massachusetts at Amherst. His research interests include economic analysis, costing, process analysis, and quality. Giglio has extensive industrial experience in those fields, including full-time employment as a project manager and consultancies with 25 companies.

Giglio has been the principal investigator of 20 major funded research projects. His publications include one book, more than 30 journal articles, and numerous conference proceedings. He founded the first video-based master of science program in engineering management to serve working engineers and managers, and directed that program for 15 years.

Giglio earned a Ph.D. in industrial engineering from Stanford University. He may be contacted as follows: Mechanical and Industrial Engineering Department, University of Massachusetts at Amherst, Amherst, MA 01002; 413-545-0646; Fax: [phone]; E-mail: [email protected].