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 and...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Goos, Peter
Άλλοι συγγραφείς: Jones, Bradley
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Chichester : Wiley, [2011]
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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049 |a MAIN 
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 Chichester :  |b Wiley,  |c [2011] 
264 4 |c ©2011 
300 |a 1 online resource (xv, 287 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
505 0 |a A Simple Comparative Experiment -- An Optimal Screening Experiment -- Adding Runs to a Screening Experiment -- A Response Surface Design with a Categorical Factor -- A Response Surface Design in an Irregularly Shaped Design Region -- A 'Mixture' Experiment with Process Variables -- A Response Surface Design in Blocks -- A Screening Experiment in Blocks -- Experimental Design in the Presence of Covariates -- A Split-Plot Design -- A Two-Way Split-Plot Design. 
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. 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
650 0 |a Experimental design  |v Case studies. 
650 0 |a Industrial engineering  |x Experiments  |x Computer-aided design  |v Case studies. 
655 4 |a Electronic books. 
700 1 |a Jones, Bradley. 
776 0 8 |i Print version:  |a Goos, Peter.  |t Optimal design of experiments.  |d Hoboken, N.J. : Wiley, 2011  |z 9780470744611  |w (DLC) 2011008381  |w (OCoLC)707247960 
856 4 0 |u https://doi.org/10.1002/9781119974017  |z Full Text via HEAL-Link 
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