This accessible book equips you with all of the basic technical and managerial skills you need to develop, execute, and evaluate designed experiments effectively. You will develop a solid grounding in the statistical underpinnings of DOE, including distributions, analysis of variance, and more. You will also gain a firm grasp of full and fractional factorial techniques, the use of DOE in fault isolation and failure analysis, and the application of individual DOE methods within an integrated system. Each procedure is clearly illustrated one step at a time with the help of simplified notation and easy–to–understand spreadsheets. The book′s real–world approach is reinforced throughout by case studies, examples, and exercises taken from a broad cross section of business applications.
Practical Guide to Experimental Design is a valuable competitive asset for engineers, scientists, and decision–makers in many industries, as well as an important resource for researchers and advanced students.
This hands–on guide offers complete, down–to–earth coverage of Design of Experiments (DOE) basics, providing you with the technical and managerial tools you need to put this powerful technique into action to help you achieve your quality improvement objectives. Using a clear, step–by–step approach, Practical Guide to Experimental Design shows you how to develop, perform, and analyze designed experiments. The book features:
∗ Accessible coverage of statistical concepts, including data acquisition, reporting of results, sampling and other distributions, and more
∗ A complete range of analytical procedures – analysis of variance, full and fractional factorial DOE, and the role of DOE in fault isolation and failure analysis
∗ In–depth case studies, examples, and exercises covering a range of different uses of DOE
∗ Broad applications across manufacturing, service, administrative, and other business sectors
No matter what your field, Practical Guide to Experimental Design provides you with the "on–the–ground" assistance necessary to transform DOE theory into practice – the ideal guide for engineers, scientists, researchers, and advanced students.
Analysis of Variance.
Full Factorial Experiments.
Fractional Factorial Experiments.
Fault Isolation and Failure Analysis.
DOE Applications to Industrial Processes.
Other DOE Applications.
DAVID MATHEWS, PhD, is the chief engineer of Delta Performance Group. He is a consultant in product design and process optimization, specializing in new applications for statistical comparison techniques. He is an instructor in seminars at major universities and a technical advisor to engineers and statisticians. He also teaches at West Coast University and is a former adjunct associate professor in both the mathematics and physics departments at the University of Alabama in Huntsville. He is a member of the Eta Kappa Nu and Sigma Xi honor societies.