Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models - Theory and Applications (Paperback, Softcover reprint of the original 1st ed. 2019)

This book presents the latest developments and breakthroughs in fuzzy theory and performance prediction of queuing and reliability models by using the stochastic modeling and optimization theory. The main focus is on analytics that use fuzzy logic, queuing and reliability theory for the performance prediction and optimal design of real-time engineering systems including call centers, telecommunication, manufacturing, service organizations, etc. For the day-to-day as well as industrial queuing situations and reliability prediction of machining parts embedded in computer, communication and manufacturing systems, the book assesses various measures of performance and effectiveness that can provide valuable insights and help arrive at the best decisions with regard to service and engineering systems. In twenty chapters, the book presents both theoretical developments and applications of the fuzzy logic, reliability and queuing models in a diverse range of scenarios. The topics discussed will be of interest to researchers, educators and undergraduate students in the fields of Engineering, Business Management, and the Mathematical Sciences.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Asset Analytics
Release date:	February 2019
First published:	2019
Editors:	Kusum Deep • Madhu Jain • Said Salhi
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Paperback
Pages:	282
Edition:	Softcover reprint of the original 1st ed. 2019
ISBN-13:	978-981-13-4519-7
Categories:	Books > Business & Economics > Business & management > Management & management techniques > Operational research Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Professional & Technical > Mechanical engineering & materials > Production engineering > Reliability engineering Promotions
LSN:	981-13-4519-8
Barcode:	9789811345197

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