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Application of MANOVA and Mahalanobis Distance in quality control

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Date Issued:
1997
Summary:
Many quality control problems are multivariate in nature since multiple process or product variables are measured and monitored in modern industry. Occasionally a multiple population, multi-variable scenario is encountered in parallel line manufacturing system. This work deals with the analysis of such system using multivariate techniques such as Canonical Analysis, MANOVA and Mahalanobis Distance. Using such techniques, the significant differences between the populations and the magnitude and directions of the variations within and between the populations were determined. Also, elimination/reduction of such variations using multivariate techniques led to a drastic improvement of the production system. A methodology for application of such multivariate techniques for the purpose of quality assurance and improvement was developed here. The application of this methodology was performed on a pager production line and the results obtained show the benefits and the feasibility of the use of multivariate techniques for on-line monitoring and quality control.
Title: Application of MANOVA and Mahalanobis Distance in quality control.
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Name(s): Seth, Mahua.
Florida Atlantic University, Degree grantor
Mazouz, Abdel Kader, Thesis advisor
College of Engineering and Computer Science
Department of Ocean and Mechanical Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1997
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 99 p.
Language(s): English
Summary: Many quality control problems are multivariate in nature since multiple process or product variables are measured and monitored in modern industry. Occasionally a multiple population, multi-variable scenario is encountered in parallel line manufacturing system. This work deals with the analysis of such system using multivariate techniques such as Canonical Analysis, MANOVA and Mahalanobis Distance. Using such techniques, the significant differences between the populations and the magnitude and directions of the variations within and between the populations were determined. Also, elimination/reduction of such variations using multivariate techniques led to a drastic improvement of the production system. A methodology for application of such multivariate techniques for the purpose of quality assurance and improvement was developed here. The application of this methodology was performed on a pager production line and the results obtained show the benefits and the feasibility of the use of multivariate techniques for on-line monitoring and quality control.
Identifier: 9780591311266 (isbn), 15381 (digitool), FADT15381 (IID), fau:12148 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1997.
Subject(s): Quality control
Beepers--Quality control
Process control
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/15381
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.