Parameter Design for Measurement Protocols by Latent Variable Methods
Walter S. Liggett Jr
We present an approach to measurement system parameter design that does not require the values of the experimental units be known. The approach does require experimental units grouped in classes, a necessity when protocol execution alters the unit. A consequence of these classes is that the approach admits replication. This paper presents maximum likelihood estimates with a comparison to similar estimates in factor analysis, strategies for noise factors including those connected with secondary properties of the experimental units, and Bayesian inference on experimental contrasts through Markov chain Monte Carlo. The approach is illustrated by solderability measurements made with a wetting balance.
experimental design, factor analysis, Markov chain and Monte Carlo, maximum likelihood, measurement system performance, quality
Liggett Jr, W.
Parameter Design for Measurement Protocols by Latent Variable Methods, Technometrics
(Accessed December 7, 2023)