Modeling remaining useful life dynamics in reliability engineering

Modeling remaining useful life dynamics in reliability engineering

"Modeling Remaining Useful Life Dynamics in Reliability Engineering applies traditional reliability engineering methods to Prognostics and Health Management (PHM), looking at Remaining Useful Life (RUL) and predictive maintenance to enable engineers to effectively and safely predict machinery l...

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Detalles Bibliográficos
Otros Autores: Dersin, Pierre, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Boca Raton, Florida : CRC Press 2023.
Edición:First edition
Materias:
Reliability (Engineering) > Statistical methods.
Service life (Engineering) > Mathematical models.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009785407406719
Tabla de Contenidos:
  • Cover
  • Half Title
  • Title Page
  • Copyright Page
  • Dedication
  • Table of Contents
  • Preface
  • Acknowledgments
  • Author
  • 1 Introduction
  • Bibliography
  • 2 Reminder of Reliability Engineering Fundamentals
  • 2.1 Reliability, Failure Rate, RUL, MRL, and RUL Loss Rate
  • 2.1.1 Reliability, Failure, and Failure Rate
  • 2.1.2 RUL, MRL, MTTF, and RUL Loss Rate
  • 2.2 Fundamental Relation Between MRL, Reliability Function and Failure Rate
  • 2.3 Confidence Interval for RUL. Illustrations On Special Cases
  • 2.4 Exercises
  • Bibliography
  • 3 The RUL Loss Rate for a Special Class of Time-To-Failure Distributions*: MRL Linear Function of Time
  • 3.1 Characterizing the Special Family of Distributions
  • 3.2 Limiting Cases
  • 3.2.1 Exponential Distribution
  • 3.2.2 Dirac Distribution
  • 3.2.3 Uniform Distribution
  • 3.3 Synopsis
  • 3.4 RUL Distribution, Coefficient of Variation of TTF and RUL
  • 3.4.1 Coefficient of Variation of the Time to Failure
  • 3.4.2 Coefficient of Variation of the RUL
  • 3.5 Confidence Interval for RUL and Relation to RUL Loss Rate
  • 3.6 Higher-Order Moments and Moment-Generating Function
  • 3.6.1 Moment-Generating Function
  • 3.6.2 Moment-Generating Function for Special TTF Family
  • 3.7 Cumulative Hazard Function
  • 3.8 Exercises
  • Bibliography
  • 4 Generalization to an MRL Piecewise-Linear Function of Time
  • 4.1 Reliability Function, MRL, and Failure Rate
  • 4.2 Exercises
  • Bibliography
  • 5 Generalization to a Wide Class of Lifetime Distributions
  • 5.1 Introduction: Generalization Method
  • 5.2 Nonlinear Time Transformation
  • 5.3 Confidence Interval for RUL
  • 5.4 Application to Weibull Distribution
  • 5.4.1 Derivation of the Nonlinear Transformation
  • 5.4.2 Derivation of Confidence Intervals for the RUL
  • 5.5 Application to Gamma Distribution
  • 5.6 Application to the Lognormal Distribution.
  • 5.7 Application to the Pareto Distribution
  • 5.8 Application to Continuous Degradation Processes
  • 5.8.1 Problem Statement
  • 5.8.2 RUL for Wiener Process With Drift
  • 5.8.3 RUL for Gamma Process
  • 5.9 Exercises
  • Bibliography
  • 6 Properties of the Dg Metric
  • 6.1 Introduction
  • 6.2 Derivative of G(t)
  • 6.3 Differential Equation for MRL
  • 6.3.1 Example: The Rayleigh Distribution
  • 6.3.2 Other Example: The Gamma Distribution
  • 6.4 Second Derivative of G(t)
  • 6.4.1 Weibull Distribution
  • 6.4.2 Gamma Distribution
  • 6.5 Upper Bound for the Average RUL Loss Rate
  • 6.6 Exercises
  • Bibliography
  • 7 Multiple Failure Or Degradation Modes
  • 7.1 Introduction
  • 7.2 General Formulation
  • 7.3 Illustration in Special Case
  • 7.4 Exercises
  • Bibliography
  • 8 Statistical Estimation Aspects
  • 8.1 Introduction
  • 8.2 Nonparametric Estimation
  • 8.3 Parametric Estimation-Illustration On Two Case Studies
  • 8.3.1 Parametric Estimation: The Maximum Likelihood Estimation Method
  • 8.3.1.1 Maximum Likelihood Estimator
  • 8.3.1.2 Desirable Properties of the Maximum Likelihood Estimator
  • 8.3.1.3 Derivation of a Confidence Interval
  • 8.3.2 First Case Study: Light-Emitting Diodes (LEDs)
  • 8.3.3 Second Case Study: Redundant System
  • 8.4 Surrogate Model for the G(t) Transformation
  • 8.5 Bayesian Estimation
  • 8.6 Exercises
  • Bibliography
  • 9 Implications for Maintenance Optimization
  • 9.1 Introduction
  • 9.2 Maintenance Decisions: Balancing Costs and Risks
  • 9.3 Quantifying Costs and Risks
  • 9.3.1 Rejuvenation and Maintenance Efficiency
  • 9.3.2 Minimal Maintenance (ABAO)
  • 9.3.3 Perfect Maintenance (AGAN)
  • 9.4 Predictive Maintenance
  • 9.5 Exercises
  • Bibliography
  • 10 Advanced Topics and Further Research
  • 10.1 The Gini Index
  • 10.2 Entropy and the K Parameter
  • 10.2.1 Entropy
  • 10.2.2 Differential Entropy.
  • 10.2.2.1 Differential Entropy as a Function of K and . Parameters
  • 10.3 Perspectives for Future Research
  • 10.3.1 Complex Systems
  • 10.3.2 Dynamic Maintenance Policy
  • 10.3.3 Signal Processing
  • 10.3.4 Physics and Machine Learning
  • Bibliography
  • Index.

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