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Discrete Stochastic Models and Applications for Reliability Engineering and Statistical Quality Control, 9780367749842
Paperback
Harness probability for reliability: optimize systems with discrete stochastic models.

Discrete Stochastic Models and Applications for Reliability Engineering and Statistical Quality Control

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$97.01

  • Paperback

    170 pages

  • Release Date

    7 October 2024

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Summary

Title: Modeling Reliability: Discrete Stochastic Approaches for Engineering and Quality Control

Discrete stochastic models are powerful tools for understanding, controlling, and optimizing engineering systems and processes. This book bridges the gap between theory and application, providing real-life examples and illustrations of these models in reliability engineering and statistical quality control.

Explore a range of discrete stochastic models, from well-known classics to…

Book Details

ISBN-13:9780367749842
ISBN-10:036774984X
Author:Serkan Eryilmaz
Publisher:Taylor & Francis Ltd
Imprint:CRC Press
Format:Paperback
Number of Pages:170
Release Date:7 October 2024
Weight:300g
Dimensions:234mm x 156mm
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About The Author

Serkan Eryilmaz

Serkan Eryilmaz completed his Ph.D. at Ankara University (Turkey) in 2002. He is currently working as a professor at the Department of Industrial Engineering and serving as vice president for research at Atilim University, Ankara. He is the present co-chair of the System Reliability Technical Committee of the European Safety and Reliability Association. He currently serves as a member of the Editorial Board of Reliability Engineering and System Safety and an Area Editor of the IISE Transactions- Quality & Reliability Engineering. His research interests include reliability engineering, applied probability, stochastic modeling, and renewable energy systems. He is the author of more than 180 publications. He was honored by TUBITAK (Scientific and Technological Research Council of Turkey) Science Incentive Award due to his highly qualified studies on system reliability in the field of stochastic models/ processes in operations research.

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