Engineers and practitioners contribute to society through their ability to apply basic scientific principles to real problems in an effective and efficient manner. They must collect data to test their products every day as part of the design and testing process and also after the product or process has been rolled out to monitor its effectiveness. Model building, data collection, data analysis and data interpretation form the core of sound engineering practice.
After the data has been gathered the engineer must be able to sift them and interpret them correctly so that meaning can be exposed from a mass of undifferentiated numbers or facts. To do this he or she must be familiar with the fundamental concepts of correlation, uncertainty, variability and risk in the face of uncertainty.
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.
Featuring:
- Contributions from leading experts in statistics and their application to engineering from industrial control to academic medicine and financial risk management giving all-round authoritative coverage.
- Wide-ranging selection of statistical techniques showing the proper way to use each to enable the reader to choose the method most appropriate for his or her purposes.
- Extensive and easy-to-use subject index making information quickly available to the reader.
The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
About the Author: 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 .
