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In literature, lot of work has been done on optimal, robust and response surface designs. These designs are very useful for performing trial run in the industries for obtaining optimum and efficient results with lesser number of trials. More of the work in literature relates to symmetric designs, whereas practically in industries generally all the factors can not be on same number of levels. This book deals with various robust asymmetric designs under the concept of non-isomorphic interaction graphs, response surface designs, moment aberration designs, non-isomorphic hidden projection…mehr

Produktbeschreibung
In literature, lot of work has been done on optimal, robust and response surface designs. These designs are very useful for performing trial run in the industries for obtaining optimum and efficient results with lesser number of trials. More of the work in literature relates to symmetric designs, whereas practically in industries generally all the factors can not be on same number of levels. This book deals with various robust asymmetric designs under the concept of non-isomorphic interaction graphs, response surface designs, moment aberration designs, non-isomorphic hidden projection properties and optimal block designs in non-regular Hadamard matrices. This book also deals with the concept of maximum estimation capacity of three-level combined arrays. Nevertheless, this book should be useful to academics for their future research in this preview. Especially useful for automobile, pharmaceutical, agriculture, chemical industries etc. wherever large number of trial runs is required and one wants to reduce the number of runs in their trial experiments. It would save them on money and at the same time would give them efficient designs for their product manufacturing.
Autorenporträt
Dr. Neena Mital, PhD in Statistics specialized in Design of Experiments from University of Delhi. She is working as an Associate Professor at Department of Statistics, Ram Lal Anand College, University of Delhi, Delhi. Pursuing post-doctorate project, that studies the Role of Statistics in Industrial applications.