Statistical methods are applied widely in industry, particularly in manufacturing processes, to provide authoritative methods for quality control and thus improve productivity and efficiency. The various methods range from graphical approaches to generalised modelling, and from designed experiments to process control. Statistical Practice in Business and Industry presents the latest advances in the application of statistical and optimisation methods within modern industry, alongside more established methods. Methods are demonstrated across a wide range of real-life applications from fields including finance, e-commerce, micro-electronics, chemical and automotive engineering, component assembly, household goods and plastics manufacturing. Each topic is investigated by an expert in that field, facilitating a comprehensive understanding of how statistical methods benefit business and industry.
The book:
* Provides comprehensive coverage of the essential statistical methods applied in industry.
* Presents user-friendly practical guidance on the applications of the methods.
* Adopts a graphical approach, helping the non-statistician to fully understand the methods.
* Features problem solving strategies for all aspects of business, from product and process design, through to packaging and delivery, dealing with single and multivariate problems.
* Includes a review of available software and references to further reading.
The lucid style of Statistical Practice in Business and Industry makes this an invaluable text for anyone working in industry and employing statistical methods in their work. It also makes ideal supplementary reading for students of engineering and statistics.
Rezensionen / Stimmen
"The book can be recommended to any interested in the application of statistical methods in business." (Statistical Papers, 6 July 2011)
Produkt-Info
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Maße
Höhe: 231 mm
Breite: 161 mm
Dicke: 29 mm
Gewicht
ISBN-13
978-0-470-01497-4 (9780470014974)
Schweitzer Klassifikation
The Editors, Shirley Coleman, Tony Greenfield, Dave Stewardson, and Douglas C. Montgomery, are section leaders in ENBIS - European Network for Business and Industrial Statistics - an organisation for the encouragement of exchange of ideas and methods of best practice between academia and industry across different countries.
Herausgeber*in
University of Newcastle
Greenfield Research
University of Newcastle
Arizona State University
Contents
Contributors
Preface
1 Introduction
Shirley Coleman, Tony Fouweather and Dave Stewardson
2 A History of Industrial Statistics
Jeroen de Mast
3 Statistical Consultancy
3.I A Statistician in Industry
Ronald J.M.M. Does and Albert Trip
3.II Black Belt Types
Roland Caulcutt
3.III Statistical Consulstancy Units at Universities
Ronald J.M.M. Does and András Zempléni
3.IV Consultancy? . . . What's in It for Me?
Roland Caulcutt
4 The Statistical Efficiency Conjecture
Ron S. Kenett, Anne De Frenne, Xavier Tort-Martorell and Chris McCollin
5 Management Statistics
Irena Ograjenaek and Ron S. Kenett
6 Service Quality
Irena Ograjenaek
7 Design and Analysis of Industrial Experiments
Timothy J. Robinson
8 Data Mining
Paola Cerchiello, Silvia Figini and Paolo Giudici
9 Using Statistical Process Control for Continual Improvement
Donald J. Wheeler and Øystein Evandt
10 Advanced Statistical Process Control
Murat Kulahci and Connie Borror
11 Measurement System Analysis
Giulio Barbato, Grazia Vicario and Raffaello Levi
12 Safety and Reliability
12.I Reliability Engineering: The State of the Art
Chris McCollin
12.II Stochastics for the Quality Movement: An Integrated Approach to Reliability and Safety
M. F. Ramalhoto
13 Multivariate and Multiscale Data Analysis
Marco P. Seabra dos Reis and Pedro M. Saraiva
14 Simulation in Industrial Statistics
David R´1os Insua, Jorge Muruzabal, Jes´us Palomo, Fabrizio Ruggeri, Julio Holgado and Ra´ul Moreno
15 Communication
Tony Greenfield and John Logsdon Index