STABILITY AND RESPONSE SURFACE METHODOLOGY

In recent years much attention has been focused on the impact of the use of statistics, and in particular experimental design, to improve the quality of products and processes. An important component of the quality of a product is its robustness or stability in the presence of what Taguchi has called noise variables. 

These noise variables can be from a variety of sources, such as environmental conditions, deterioration of components, or variation in product components and manufacturing processes. It is possible that variation due to these sources will cause variation in the key characteristics of a product or process, resulting in a product of inferior quality. 

This chapter will examine the application of statistical experimental design to designing a product or process that is robust to variation from environmental variables. It should be understood that the phrase environmental variables is to be viewed broadly and is not just limited to variables such as temperature and humidity. In this context, variation from environmental variables is variation that is external to the product and that is outside of the control of the manufacturer during production. Thus, it might also include variation in the conditions in which the customer uses the product, or in the conditions in which the product is stored, or in how the product is maintained and serviced. 

It should be noted that experiments with this objective of robust design have been run for many years in agricultural research. For example, a paper by Yates and Cochran [1] describes experiments on crop varieties in different regions over several years the objective being to determine a variety that consistently will produce a good yield over a range of climate 

The experiments conducted to perform ruggedness tests of measurement procedures can also be viewed as experiments to investigate robust design see, for example, Wemimont [2], and Youden [3,4]. The objective of ruggedness tests is to determine a robust measurement procedure that is a procedure that will give a consistent (and correct) result under a range of measurement conditions. 

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