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Design of experiments (DOE) refers to the planned, structured, and organized observation of two or more independent variables and their effect on the output variable(s) being studies. In most cases DOE is done using statistics to analyze and predict the changes to the results of the experiment in question, most of which is highly mathematical and theoretical. This book provides an applications oriented introduction to the principles of DOE aimed at solving the day-to-day problems encountered in business.
Over the last decade, Design of Experiments (DOE) has become established as a prime
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Produktbeschreibung
Design of experiments (DOE) refers to the planned, structured, and organized observation of two or more independent variables and their effect on the output variable(s) being studies. In most cases DOE is done using statistics to analyze and predict the changes to the results of the experiment in question, most of which is highly mathematical and theoretical. This book provides an applications oriented introduction to the principles of DOE aimed at solving the day-to-day problems encountered in business.
Over the last decade, Design of Experiments (DOE) has become established as a prime analytical and forecasting method with a vital role to play in product and process improvement. Now Practical Guide to Experimental Design lets you put this high-level statistical technique to work in your field, whether you are in the manufacturing or services sector.

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.
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Autorenporträt
NORMAND L. FRIGON is a partner in the business consulting firm of Delta Performance Group. His firm provides cutting-edge consulting services and training throughout industry in all aspects of product, process, and services optimization and management. He is the coauthor of Management 2000, From Concept to Customer, Achieving the Competitive Edge, and The Leader. 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.