Achieving Six Sigma Objectives for Variability Reduction in Coating Formulation and Processing
"Six sigma" is the new rallying cry for quality improvement in the chemical process industry. For example, Dow aims to generate an extra $1.5 billion per year in profits after training 50,000 of its employees on the methods of six sigma.3 Statistical tools play a key role in achieving savings of this magnitude. In fact, "sigma" is a Greek letter that statisticians use as a symbol for standard deviation -- a measure of variability. If a manufacturer achieves a six-sigma buffer from its nearest specification, they will experience only 3.4 off-grades per million lots. This translates to better than 99.99966% of product being in specification. To illustrate what this level of performance entails, imagine playing 100 rounds of golf a year: At six sigma you'd miss only 1 putt every 163 years!4
Of all the statistical tools used within six sigma, design of experiments (DOE) offers the most power for making breakthroughs. By way of a case-study example, this article demonstrates how DOE can be applied to development of a coatings system to achieve optimal performance with minimum variability, thus meeting the objectives of six sigma programs.