Statistics for Engineers
An Introduction
Published on 17. June 2009
192 pages
978-0-470-74643-1 (ISBN)
Description
This practical text is an essential source of information for thosewanting to know how to deal with the variability that exists inevery engineering situation. Using typical engineering data,it presents the basic statistical methods that are relevant, insimple numerical terms. In addition, statistical terminology istranslated into basic English.
In the past, a lack of communication between engineers andstatisticians, coupled with poor practical skills in qualitymanagement and statistical engineering, was damaging to productsand to the economy. The disastrous consequence of setting tighttolerances without regard to the statistical aspect of process datais demonstrated.
This book offers a solution, bridging the gap betweenstatistical science and engineering technology to ensure that theengineers of today are better equipped to serve the manufacturingindustry.
Inside, you will find coverage on:
* the nature of variability, describing the use of formulae topin down sources of variation;
* engineering design, research and development, demonstrating themethods that help prevent costly mistakes in the early stages of anew product;
* production, discussing the use of control charts, and;
* management and training, including directing and controllingthe quality function.
The Engineering section of the index identifies the role ofengineering technology in the service of industrial qualitymanagement. The Statistics section identifies points in the textwhere statistical terminology is used in an explanatorycontext.
Engineers working on the design and manufacturing of newproducts find this book invaluable as it develops a statisticalmethod by which they can anticipate and resolve quality problemsbefore launching into production. This book appeals tostudents in all areas of engineering and also managers concernedwith the quality of manufactured products.
Academic engineers can use this text to teach their studentsbasic practical skills in quality management and statisticalengineering, without getting involved in the complex mathematicaltheory of probability on which statistical science isdependent.
Reviews / Votes
"This book appeals to students in all areas of engineering andalso managers concerned with the quality of manufactured products.Academic engineers can use this text to teach their students basicpractical skills in quality management and statistical engineering,without getting involved in the complex mathematical theory ofprobability on which statistical science is dependent." (Zentralblatt MATH, 1 August 2013)"This is a timely text that helps to support the development ofthese important skills. Its no-nonsense and useful approach gives aflavour of the main statistical tools and techniques in basiclanguage." (Quality World, December 2009) "It deserves to become a standard text to encourage the best inindustrial practice." (Engineering & Technology,November 2009)More details
Other editions
Additional editions
Book
06/2009
Wiley
€67.90
Shipment within 10-20 days
Person
S.J. Morrison, retired, Department of Operational Research, University of Hull
Mr. Samuel Jim Morrision has been retired for 20 years now, his last post being as Head of the Department of Operational Research at the University of Hull. He contributed a great deal to the pioneering of statistics in industry and operational research, and set up the first postgraduate management course at Hull. He is a Fellow of the Institution of Mechanical Engineers, the Royal Statistical Institute and the Chartered Mangagement Institute. He is also a senior member of the American Society for Quality.
Jim has been a speaker at conferences and meetings (including the IMS meeting of 1999 'Statistics in the Education of Engineers') where he has encouraged the use of simple statistics within the engineering industry. He has written many articals and papers on statistical engineering as the key to quality, writing often for the IET.
Content
About the Author.
Foreword.
Preface.
Acknowledgements.
1 Nature of Variability.
2 Basic Statistical Methods.
2.1 Variance.
2.2 Divisor 'n' or 'n_1'?
2.3 Covariance and Correlation.
2.4 Normal Distribution.
2.5 Cumulative Frequency Distributions.
2.6 Binomial Distribution.
2.7 Poisson Distribution.
2.8 Chi-squared Distribution.
Bibliography.
3 Production.
3.1 Sampling Inspection.
3.2 Control Charts.
3.3 Cusum Charts.
3.4 Significance Tests.
3.5 Analysis of Variance.
3.6 Linear Regression.
Bibliography.
4 Engineering Design.
4.1 Variance Synthesis.
4.2 Factors of Safety.
4.3 Tolerances.
4.4 The Future.
Bibliography.
5 Research and Development.
5.1 Design of Experiments.
5.2 Evolutionary Operation.
5.3 Multiple Regression.
5.4 More Statistical Methods.
Bibliography.
6 Background.
6.1 Measurement.
6.2 Statistical Computing.
Bibliography.
7 Quality Management.
7.1 Quality Planning.
7.2 Quality Organisation.
7.3 Directing the Quality Function.
7.4 Controlling the Quality Function.
7.5 Statistical Engineering.
Bibliography.
8 Conclusion.
Appendix A: Guidelines.
Appendix B: Recommended Books.
Appendix C: Periodicals.
Appendix D: Supplementary Bibliography.
Appendix E: Statistical Tables.
Index.
