Springer Handbook of Engineering Statistics (eBook)

In today's global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them 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. 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.

Hoang Pham is a distinguished professor and former chairman (2007-2013) of the Department of Industrial and Systems Engineering at Rutgers University. Before joining Rutgers in 1993, he was a senior engineering specialist with the Idaho National Engineering Laboratory, Idaho Falls, Idaho, and Boeing Company in Seattle, Washington. His research areas include reliability modeling and prediction, software reliability, and statistical inference. He is editor-in-chief of the International Journal of Reliability, Quality and Safety Engineering and editor of Springer Series in Reliability Engineering and has been conference chair and program chair of over 40 international conferences and workshops. Dr. Pham is the author or coauthor of 7 books and has published over 200 journal articles, 100 conference papers, and edited 20 books including Springer Handbook of Engineering Statistics and Handbook of Reliability Engineering. He has delivered over 40 invited keynote and plenary speeches at many international conferences and institutions. His numerous awards include the 2009 IEEE Reliability Society Engineer of the Year Award. He is a fellow of the IEEE, AAIA, and IISE.

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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.