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Optimal Inspection Models with Their Applications (Hardcover, 1st ed. 2023) Loot Price: R4,574
Discovery Miles 45 740
Optimal Inspection Models with Their Applications (Hardcover, 1st ed. 2023): Kodo Ito, Toshio Nakagawa

Optimal Inspection Models with Their Applications (Hardcover, 1st ed. 2023)

Kodo Ito, Toshio Nakagawa

Series: Springer Series in Reliability Engineering

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Loot Price R4,574 Discovery Miles 45 740 | Repayment Terms: R429 pm x 12*

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This book surveys recent applications of inspection models, maintenance models and cumulative damage models, as well as discusses the policies involved with these models. It explains how a stochastic approach can be applied to systems using real-world examples. The book begins by introducing and summarizing standard inspection models. It dedicates chapters to random inspection models and general inspection models, before moving on to discuss inspection policies and checkpoint models. The book discusses inspection of reliability systems, such as missile maintenance systems, as well as Markov models of inspection. The book concludes with a summary of other inspection models, problems they face, and solutions to these problems. Each chapter utilizes examples to illustrate the various models, methods, and policies. This book is of interest to engineering students, researchers, and design and production engineers working in system manufacturing.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Springer Series in Reliability Engineering
Release date: February 2023
First published: 2023
Authors: Kodo Ito • Toshio Nakagawa
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 261
Edition: 1st ed. 2023
ISBN-13: 978-3-03-122020-3
Categories: Books > Computing & IT > General theory of computing > Systems analysis & design
Books > Professional & Technical > Mechanical engineering & materials > Production engineering > Reliability engineering
Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General
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LSN: 3-03-122020-X
Barcode: 9783031220203

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