Diagnostics and Prognostics of Engineering Systems: Methods and Techniques

Diagnostics and Prognostics of Engineering Systems: Methods and Techniques

Seifedine Kadry (American University of the Middle East, Kuwait)
Indexed In: SCOPUS View 1 More Indices
Release Date: September, 2012|Copyright: © 2013 |Pages: 461
ISBN13: 9781466620957|ISBN10: 1466620951|EISBN13: 9781466620964|DOI: 10.4018/978-1-4666-2095-7


Industrial Prognostics predicts an industrial system’s lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to increase the system’s performance and reliability.

Diagnostics and Prognostics of Engineering Systems: Methods and Techniques provides widespread coverage and discussions on the methods and techniques of diagnosis and prognosis systems. Including practical examples to display the method’s effectiveness in real-world applications as well as the latest trends and research, this reference source aims to introduce fundamental theory and practice for system diagnosis and prognosis.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Empirical Methods for Process and Equipment Prognostics
  • Examples and Case Studies of Prognostics and Health Management
  • In-Situ Monitoring Techniques
  • Life Cycle Cost and Return on Investment for Prognostics and Health Management
  • Making Predictions
  • Monitoring Environmental and Usage Conditions
  • Physics of Failure Based Prognostics
  • Prognostics for Electronic Products
  • Reliability and Prognostics
  • Self Cognitive Capability for Anomaly Detection, Fault Analysis and Prognosis
  • Sensors for Prognostics
  • Time Series Analysis

Reviews and Testimonials

Structural health monitoring (SHM) assesses the current ability of a structural component or system to perform its intended design function successfully, and prognostics extends the assessment to forecast remaining useful life. The 19 chapters in this volume describe techniques for diagnosing fault levels, modeling equipment degradation, monitoring systems intelligently, and scheduling maintenance according to condition rather than preset time intervals. The last two chapters approach structure reliability and response prognostics with Bayesian analysis and analytical approximation, and predict fatigue damage through indirect sensor measurements. The book will mainly be of interest to mechanical and industrial engineers. 

– Book News Inc. Portland, OR

Table of Contents and List of Contributors

Search this Book:

Author(s)/Editor(s) Biography

Seifedine Kadry is an associate professor of Applied Mathematics in the American University of the Middle East Kuwait. He received his masters' degree in Modelling and Intensive Computing (2001) from the Lebanese University – EPFL -INRIA. He did his doctoral research (2003-2007) in applied mathematics from Blaise Pascal University-Clermont Ferrand II, France. He worked as Head of Software Support and Analysis Unit of First National Bank where he designed and implement the data warehouse and business intelligence; he has published one book and more than 50 papers on Applied Math, computer science and stochastic systems in peer-reviewed journals.