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The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers.Design of Experiments for Engineers and Scientists overcomes the
Experimental design. --- Research, Industrial. --- Contract research --- Industrial research --- Design of experiments --- Statistical design --- Research --- Engineering experiment stations --- Inventions --- Technological innovations --- Mathematical optimization --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Experiments --- Methodology --- 519.87 --- 519.87 Mathematical models for operational research --- Mathematical models for operational research --- Statistiek.
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The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation. Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists
Experimental design. --- Research, Industrial. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Contract research --- Industrial research --- Research --- Engineering experiment stations --- Inventions --- Technological innovations --- Design of experiments --- Statistical design --- Mathematical optimization --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Experiments --- Methodology
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This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic.
Experimental design. --- Research, Industrial. --- Plan d'expérience. --- Recherche industrielle. --- Experimental design --- Research, Industrial --- Scientific research. --- Research.
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The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation. Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand. This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry.
Science --- Mathematical statistics --- Engineering sciences. Technology --- industrial design --- engineering --- experimentation
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The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of stat.
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This book illustrates the integration of both Lean and Six Sigma as a process excellence methodology which can be utilized in Higher Education environments for achieving and sustaining world class efficiency and effectiveness. It showcases various studies carried out by leading research scholars, academics and practitioners.
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Considers strategic aspects of quality management and self-assessment frameworks, and provides an in-depth examination of a number of the main quality improvement tools and techniques.
Total quality management. --- Business. --- Management --- kvalitetsstyring --- management --- kvalitetssikring --- Management.
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