Collaborative Research: Monitoring Process and Product Quality Profiles

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

This grant provides funding for the development of statistical methods for the effective monitoring of curves that represent the quality of a process or product. In most current statistical process control applications in industry it is assumed that that quality can be adequately represented by the distribution of a univariate quality characteristic or by the general multivariate distribution of a vector consisting of several correlated quality characteristics. In many practical situations, however, the quality of a process or product is better characterized and summarized by a relationship between a response variable and one or more explanatory variables. Thus, at each sampling stage one observes a collection of data points that can be represented by a curve (or profile). In some calibration applications, the profile can be represented adequately by a simple straight-line model, while in other applications more complicated models are needed. In this work control charts will be developed and evaluated to monitor such process and product quality profiles. This application will be related to functional data analysis and methods will be developed for linear profiles, nonlinear profiles, and those currently handled using splines and wavelets. The results of this research will lead to more effective use of industrial data to characterize and monitor the quality of processes and products. In particular, the methods can be used to monitor calibration relationships and avoid the over-calibration of measurement devices. This lowers costs and improves measurement accuracy. Applications exist in the pharmaceutical industry in the monitoring of non-linear dose-response curves of successive batches of drugs. Applications have been identified and data have already been obtained in semiconductor manufacturing and in the calibration of chemical and other measurement processes, including one at NASA.