Abstract #301031

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JSM 2003 Abstract #301031
Activity Number: 98
Type: Contributed
Date/Time: Monday, August 4, 2003 : 9:00 AM to 10:50 AM
Sponsor: Section on Quality & Productivity
Abstract - #301031
Title: On the Optimal Variance of a Parameter Design
Author(s): Fassil Nebebe*+
Companies: Concordia University
Address: GM-209-3, Montreal, Quebec, H3G 1M8, Canada
Keywords: off-line quality control ; optimal variance
Abstract:

In off-line quality control, parameter designs are widely employed to find settings of design variables that would minimize the variance of deviation from a targeted value. Much of the attention in the literature, however, has been focused on the modeling and the associated estimation problem in the analysis of data collected from parameter designs. Less is said about the expected inflation in the attained variance from the actual unknown optimal solution. This issue is of practical interest, as it permits the practitioner to evaluate the component of the estimated variance attributable to the random variation resulting from sampling. A large value in the inflated variance would prompt the practitioner to either redesign the parameter design or increase the sample size used. A related issue is the construction of a confidence interval for the unknown optimal variance, based on which the practitioner can determine if the optimal variance exceeds an acceptable level. In the latter case, a new product or process design may be needed to achieve a smaller value of variances. These issues are addressed in detail and their applications are demonstrated.

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