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A Framework for Continuous Inspection Plans Using Multivariate Mathematical Methods
The aim of this study was to propose and apply a sampling procedure using mathematical models and multivariate statistics for continuous processes in manufacturing companies. The research presented in this paper can be classified as a descriptive and empirical quantitative study in which the basic i...
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Published in: | Quality and reliability engineering international 2013-11, Vol.29 (7), p.937-949 |
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creator | Oprime, Pedro Ganga, Gilberto Miller Devós |
description | The aim of this study was to propose and apply a sampling procedure using mathematical models and multivariate statistics for continuous processes in manufacturing companies. The research presented in this paper can be classified as a descriptive and empirical quantitative study in which the basic interest was in creating a model that describes and analyzes the causal relationships between the quality characteristics (in this case, multivariate) of a process, in order to select the best continuous inspection plan. This framework was applied in a company that supplies the main component producers for the worldwide car industry. The results obtained from applying the multivariate procedures made it possible to select the best continuous inspection plan based on inspection frequency, resultant mean quality, and proportion of the units inspected. This procedure should be tested on new problems and real situations in order to validate the methods used. Copyright © 2012 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/qre.1446 |
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subjects | continuous sampling plans Empirical analysis engineering process control Inspection Mathematical models process monitoring quality improvement Reliability engineering Resultants Sampling Statistics |
title | A Framework for Continuous Inspection Plans Using Multivariate Mathematical Methods |
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