05463nam 2200685Ia 450 991082510660332120240410080530.01-136-37911-81-281-00953-997866110095331-4237-2341-40-08-047954-5(CKB)1000000000350228(EBL)234969(OCoLC)171114296(SSID)ssj0000198814(PQKBManifestationID)11172776(PQKBTitleCode)TC0000198814(PQKBWorkID)10183624(PQKB)11163890(Au-PeEL)EBL234969(CaPaEBR)ebr10127973(CaONFJC)MIL100953(OCoLC)936903579(MiAaPQ)EBC234969(EXLCZ)99100000000035022820041116d2005 uy 0engur|n#---|||||txtccrMastering statistical process control a handbook for performance improvement using cases /Tim Stapenhurst1st ed.Amsterdam ;London Elsevier Butterworth-Heinemann20051 online resource (497 p.)Description based upon print version of record.9781138173262 9780750665292 Includes bibliographical references and index.Cover; Mastering Statistical Process Control: A Handbook for Performance Improvement Using Cases; Copyright; Contents; List of Figures; List of Charts; List of Case Studies and Examples; Reference of Charts; Preface; Acknowledgements; Introduction; The aim of the book; The structure of the book; How to use this book; PART 1 An Introduction to the Theory of SPC; 1 Statistical process control; A word on processes ...; ... And a word on variation; Some statistical measures; Why is understanding variation important to management?; Summary of the implications of process variationTampering (over-control) and its effect on performanceControl charts: the tool for understanding process performance; Dispelling some myths of SPC; Are there situations where SPC is not appropriate?; The relationship between SPC and Six Sigma; Summary; PART 2 Exploding Data Analysis Myths; 2 Problems with monthly report tables, goals and quartiles; Introduction; Comparing pairs of numbers: a trap for the unwary; Death by numbers: the Saga of the monthly report; Who wins the prize? How not to compare regional performance statisticsFalsifying the data (and how to spot it): one result of setting targetsQuerying the top quartile: Does it mean anything?; Summary; 3 Exploring the mis-information in moving average charts: How they fail to respond to process changes, out-of-control points, trends and seasonality; Introduction; Analysis; Coping with seasonality and trends; What moving averages actually monitor; Summary; 4 The problems with year-to-date figures; Introduction; Analysing YTD against plan; Analysing this year's YTD against last year's YTD; Why YTD charts do not workComparing YTD and YTD average charts with control chartsSummary; PART 3 Putting SPC into Practice - The Cases; The sources of the case studies; Control charts in the real worlds are not always so clear; A word on chart formats; Layout of and information in the case studies; How to use the case studies?; 5 Investigating variation in chemical concentration: How control charts were used to identify, investigate and prove the cause of fluctuations in results; 6 Improving examination results by analysing past performance and changing teaching methods7 Demonstration that moving averages are poor indicators of true process performance: Monitoring the frequency of incidents8 Monitoring rare events: How a sudden but uncertain change in safety record was shown to be significant; 9 Comparing surgical complication rates between hospitals; 10 Comparing the frequency of rare medical errors between medical centres; 11 Metrics proposal for a training administration process; 12 Reducing problems during borehole drilling: An example of monitoring two metrics on one chart; 13 Applying control charts to benchmarking in the drilling industry14 Comparing the results of using different charts to analyse a set of data: An application to a batch production processMastering Statistical Process Control shows how to understand business or process performance more clearly and more effectively. This practical book is based on a rich and varied selection of case studies from across industry and commerce, including material from the manufacturing, extractive and service sectors. It will enable readers to understand how SPC can be used to maximum effect, and will deliver more effective monitoring, control and improvement in systems, processes and management. The common obstacle to successful use of SPC is getting bogged down witQuality controlStatistical methodsProcess controlStatistical methodsQuality controlStatistical methods.Process controlStatistical methods.658.562015195Stapenhurst Tim1624520MiAaPQMiAaPQMiAaPQBOOK9910825106603321Mastering statistical process control3959528UNINA