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Measurement Errors in Statistical Process Monitoring: a Literature Review

Authors :
Philippe Castagliola
Mohammadreza Maleki
Amirhossein Amiri
Laboratoire des Sciences du Numérique de Nantes (LS2N)
IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)
Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)
Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)
Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)
Source :
Computers & Industrial Engineering, Computers & Industrial Engineering, Elsevier, 2017, 103, pp.316-329. ⟨10.1016/j.cie.2016.10.026⟩
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

An overview on the effect of measurement errors on different areas of SPM.Providing a comprehensive classification of articles in this area.Presenting an analytical overview on the researches in this area.Introducing research gaps in this area to motivate future studies. In most industrial applications, the measures performed on inspected units are often strongly contaminated by either the inspector or the measuring device leading to measurement errors. It is recognized that the measurement errors affect the performance of control charts in various statistical process monitoring applications. In this paper, we present a conceptual classification scheme based on content analysis method to analyze and categorize the researches which have explored the effect of measurement errors on different aspects of statistical process monitoring (SPM). Moreover, based on 60 relevant papers in this field, the research gaps are mentioned and some directions to motivate the future studies are provided.

Details

Language :
English
ISSN :
03608352
Database :
OpenAIRE
Journal :
Computers & Industrial Engineering, Computers & Industrial Engineering, Elsevier, 2017, 103, pp.316-329. ⟨10.1016/j.cie.2016.10.026⟩
Accession number :
edsair.doi.dedup.....ae66bcca646f0027628a25afbff1e967
Full Text :
https://doi.org/10.1016/j.cie.2016.10.026⟩