Springer Handbook of Engineering Statistics

In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. Many organisations have shown that the first step to continuous improvement is to integrate the widespread use of statistics and basic data analysis into the manufacturing development process as well as into the day-to-day business decisions taken in regard to engineering processes.

The "Springer Handbook of Engineering Statistics" gathers together the full range of statistical techniques required by engineers from all fields to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved.

From the reviews:

"The book provides a concise compilation of approved keys and up to date information on statistical methods for engineering sciences. A detailed list of references for every topic is appreciable." (Daniela Jarušková, Zentrablatt MATH, Vol. 1096 (22), 2006)

"The Springer Handbook of Engineering Statistics is a recent entry in the Springer Press’ line of technical reference books. … The text is aimed at practicing engineers and researchers as a compilation of the core fundamentals of engineering statistics, along with current and cutting-edge research and theory. … This text will be a welcome addition to the reference library of experienced users of traditional engineering statistics … . Current research is well summarised, clearly presented, and strikingly illustrated." (Dave Jones, International Journal of Acoustics and Vibration, Vol. 12 (2), 2007)

"This book enlisted 100 authors in various field of expertise, the reader can expect wide variations in the style of writing and depth of coverage. … a book for those for those interested in learning what one can do with statistics to develop data, models, or methods to discover information for improving processes, making engineering decisions, or just to understand processes. For those applying statistics for process improvement, this book would serve as a good source to go beyond the traditional Six Sigma tool kits." (Shin Ta Liu, Technometrics, Vol. 49 (4), 2007)

"[T]he Springer Handbook on Engineering Statistics is going to be useful to engineers at large, particularly to engineers engaged in manufacturing, design, testing and operations." (Krisnha B. Misra, International Journal of Performability Engineering, Vol. 3, (3), 2007)

Dr. Hoang Pham Pham is Professor and Director of the Undergraduate Program in the Department of Industrial and Systems Engineering at Rutgers University, Piscataway, NJ. Before joining Rutgers, he was a senior engineering specialist at the Boeing Company, Seattle, and the Idaho National Engineering Laboratory, Idaho Falls. His research interests include software reliability, system reliability modeling, maintenance, and environmental risk assessment.

He is the author of Software Reliability (Springer-Verlag, 2000) and a forthcoming book System Software Reliability (Springer, 2005). He is the editor of the Handbook of Reliability Engineering (Springer-Verlag, 2003) and Springer Handbook of Engineering Statistics (Springer, 2005). He is also the editor of Springer Series in Reliability. He has published more than 80 journal articles, 20 book chapters, and the editor of ten volumes.

He is editor-in-chief of the International Journal of Reliability, Quality and Safety Engineering (www.worldscinet.com/ijrqse), associate editor of the IEEE Trans. on Systems, Man and Cybernetics (Part A), and guest editor of IIE Transactions and IEEE Trans. on Systems, Man and Cybernetics (Part A). He has been conference chair and program chair of over 20 international conferences and workshops and is currently the Conference Chair of the Eleventh International Conference on Reliability and Quality in Design will be held in St. Louis , August 2005.

He received the B.S. degree in mathematics, B.S. degree in computer science, both with high honors, from Northeastern Illinois University , Chicago , the M.S. degree in statistics from the University of Illinois , Urbana-Champaign, and the M.S. and Ph.D. degrees in industrial engineering from the State University of New York at Buffalo .