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Optimal design of experiments : a case study approach /

"This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability an...

Deskribapen osoa

Gorde:
Egile nagusia: Goos, Peter
Beste egile batzuk: Jones, Bradley
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Hoboken, N.J. : Wiley, 2011.
Gaiak:
Industrial engineering > Experiments > Computer-aided design.
Experimental design > Data processing.
Industrial engineering > Case studies.
Electronic books.
Sarrera elektronikoa:https://biblioteca.ues.edu.sv/acceso/elibro/?url=https%3A%2F%2Felibro.net%2Fereader%2Fbiblioues/188888
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050 4 |a T57.5  |b .G66 2011 
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100 1 |a Goos, Peter. 
245 1 0 |a Optimal design of experiments :  |b a case study approach /  |c Peter Goos, Bradley Jones. 
264 1 |a Hoboken, N.J. :  |b Wiley,  |c 2011. 
300 |a xiv, 287 p. :  |b ill. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a data file  |2 rda 
504 |a Includes bibliographical references and index. 
520 |a "This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities?While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain. The structure of the book is organized around the following chapters: 1) Introduction explaining the concept of tailored DOE. 2) Basics of optimal design. 3) Nine case studies dealing with the above questions using the flow: description → design → analysis → optimization or engineering interpretation. 4) Summary. 5) Technical appendices for the mathematically curious"--  |c Provided by publisher. 
520 |a "This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples"--  |c Provided by publisher. 
588 |a Description based on metadata supplied by the publisher and other sources. 
590 |a Electronic resource. Santa Fe, Argentina: elibro, 2025. Available via the World Wide Web. Access may be limited to libraries affiliated with elibro. 
650 0 |a Industrial engineering  |x Experiments  |x Computer-aided design. 
650 0 |a Experimental design  |x Data processing. 
650 0 |a Industrial engineering  |v Case studies. 
655 4 |a Electronic books. 
700 1 |a Jones, Bradley. 
797 2 |a elibro, Corp. 
856 4 0 |u https://biblioteca.ues.edu.sv/acceso/elibro/?url=https%3A%2F%2Felibro.net%2Fereader%2Fbiblioues/188888 

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