Another Look at Dorian Shainin's Variable Search Technique

Abstract

An in-depth analysis of Dorian Shainin's variable search (VS) method is carried out. Conditions under which the VS approach does and does not work well in comparison with traditional designs are identified. Explicit expressions for the expected number of runs and the probability of correct screening are derived under stated assumptions. The crucial roles of process knowledge and noise variation in successful application of the VS design are established through theoretical and simulation studies.

• Design of Experiment
• Factorial Design
• Projectivity
• Quality Improvement
• Variable Screening

Additional information

Notes on contributors

Tirthankar Dasgupta

Dr. Dasgupta is an Assistant Professor in the Department of Statistics. His email address is [email protected].

Nagesh Adiga

Mr. Adiga is a Ph.D. Candidate in the School of Industrial and Systems Engineering. His email address is [email protected].

C. F. Jeff Wu

Dr. Wu is Professor of Engineering Statistics and Coca-Cola Chair in the School of Industrial and Systems Engineering. His email address is [email protected].