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Quality management and quality practice: Perspectives on their history and their future

dc.contributor.authorFisher, N. I.en_US
dc.contributor.authorNair, Vijayan N.en_US
dc.date.accessioned2009-03-03T20:08:36Z
dc.date.available2010-03-01T21:10:28Zen_US
dc.date.issued2009-01en_US
dc.identifier.citationFisher, N. I.; Nair, V. N. (2009). "Quality management and quality practice: Perspectives on their history and their future." Applied Stochastic Models in Business and Industry 25(1): 1-28. <http://hdl.handle.net/2027.42/61868>en_US
dc.identifier.issn1524-1904en_US
dc.identifier.issn1526-4025en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/61868
dc.description.abstractThe purpose of this article and a companion article is to explore a number of topics in Statistics in Business and Industry. This article sketches the history of Quality Management, from its emergence in the late 19th and early 20th centuries through to the present day. Particular emphasis is placed on activities in Japan immediately following the end of the Second World War, and subsequent developments elsewhere in the world. We draw a careful distinction between Quality Management and various methodologies that aid in its implementation, such as Six Sigma. In the words of one management practitioner, Norbert Vogel, ‘TQM in its broadest sense examines all aspects of management and the alternative methodologies being promoted are merely sub-sets of what should be an integrated management system.’ The article concludes with some speculative thoughts about the future of Quality Management from a statistician's point of view. Copyright © 2009 John Wiley & Sons, Ltd.en_US
dc.format.extent232601 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherJohn Wiley & Sons, Ltd.en_US
dc.subject.otherMathematics and Statisticsen_US
dc.titleQuality management and quality practice: Perspectives on their history and their futureen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartments of Statistics and Industrial Operations and Engineering, University of Michigan, 453 West Hall, Ann Arbor, MI 48109-1092, U.S.A.en_US
dc.contributor.affiliationotherSchool of Mathematics and Statistics, University of Sydney, F07, NSW 2006, Australia ; ValueMetrics Australia, Australia ; School of Mathematics and Statistics, F07, University of Sydney, NSW 2006, Australiaen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/61868/1/756_ftp.pdf
dc.identifier.doi10.1002/asmb.756en_US
dc.identifier.sourceApplied Stochastic Models in Business and Industryen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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