Abstract
In robust parameter design, it is often the case that the quality characteristic is nonnormal. An example in semiconductor manufacturing is resistivity, which typically follows a gamma distribution. It is also common to have models that contain, in addition to fixed polynomial effects, a random effect representing an extraneous source of variation. In this article, we demonstrate the use of generalized linear mixed models (GLMM) for situations in which the response is nonnormal and in which the noise variable is a random effect. We discuss the analysis of the random effects as well as the fixed effects in a fitted model using GLMM techniques. A numerical example from semiconductor manufacturing is provided for illustration.
Original language | English (US) |
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Pages (from-to) | 65-75 |
Number of pages | 11 |
Journal | Journal of Quality Technology |
Volume | 38 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2006 |
Keywords
- Noise variables
- Nonnormal
- Random effects
- Response surface methodology
- Robust design
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering