
- 176 pages
- English
- PDF
- Available on iOS & Android
Fault Detection, Diagnosis and Prognosis
About this book
This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.
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Information
Table of contents
- Fault Detection, Diagnosis and Prognosis
- Contents
- Preface
- Chapter1 Introductory Chapter: Prognostics - An Overview
- Chapter2 Prognostics 102: Efficient Bayesian-Based Prognostics Algorithm in MATLAB
- Chapter3 Predicting Sets of Automata: Architecture, Evolution, Examples of Prognosis, and Applications
- Chapter4 Fault DiagnosisTechniques for aWind Turbine System
- Chapter5 Analytic Prognostic in the Linear Damage Case Applied to Buried Petrochemical Pipelines and the Complex Probability Paradigm
- Chapter6 Fault Detection of Single and Interval Valued Data Using Statistical Process Monitoring Techniques
- Chapter7 Real-Time Fault Detection and Diagnosis Using Intelligent Monitoring and Supervision Systems
- Chapter8 An Approach to Optimize the Management of Information Security in Public Organizations of Ecuador