Analysis of Variation Transmission in Manufacturing Processes-Part II

Methods for analysing variation in multistage manufacturing processes in order to identify stages which contribute most to variation in the final product are a valuable prioritization tool in variation reduction studies. However, when the data are observed with significant measurement error, substan...

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Bibliographic Details
Published inJournal of quality technology Vol. 31; no. 2; pp. 143 - 154
Main Authors Agrawal, R., Lawless, J. F., Mackay, R. J.
Format Journal Article
LanguageEnglish
Published Milwaukee Taylor & Francis 01.04.1999
Taylor & Francis Ltd
Subjects
Autoregressive Models
Confidence intervals
Machinery
Manufacturing
Methods
Moment Estimation
Normal distribution
Product quality
Statistical analysis
Studies
Variation Reduction
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Summary:Methods for analysing variation in multistage manufacturing processes in order to identify stages which contribute most to variation in the final product are a valuable prioritization tool in variation reduction studies. However, when the data are observed with significant measurement error, substantial biases which mislead the investigator can result. In addition, methods of interval estimation and diagnostic model checking are needed for proper application of these methods. In this paper, we present methods that incorporate measurement error and discuss both maximum likelihood estimation and a simpler "naive" method that is much easier to implement. We then give methods of developing confidence intervals, either in the presence or absence of measurement error. Finally, we discuss techniques for model checking.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0022-4065
2575-6230
DOI:10.1080/00224065.1999.11979911