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Reliability Engineering and Services

Reliability Engineering and Services

Tongdan Jin

ISBN: 978-1-119-16701-3

Jan 2019

500 pages




Offers a holistic approach to guiding product design, manufacturing, and after-sales support as the manufacturing industry transitions from a product-oriented model to service-oriented paradigm 

This book provides fundamental knowledge and best industry practices in reliability modelling, maintenance optimization, and service parts logistics planning. It aims to develop an integrated product-service system (IPSS) synthesizing design for reliability, performance-based maintenance, and spare parts inventory. It also presents a lifecycle reliability-inventory optimization framework where reliability, redundancy, maintenance, and service parts are jointly coordinated. Additionally, the book aims to report the latest advances in reliability growth planning, maintenance contracting and spares inventory logistics under non-stationary demand condition.

Reliability Engineering and Service provides in-depth chapter coverage of topics such as: Reliability Concepts and Models; Mean and Variance of Reliability Estimates; Design for Reliability; Reliability Growth Planning; Accelerated Life Testing and Its Economics; Renewal Theory and Superimposed Renewals; Maintenance and Performance-Based Logistics; Warranty Service Models; Basic Spare Parts Inventory Models; Repairable Inventory Systems; Integrated Product-Service Systems (IPPS), and Resilience Modeling and Planning

  • Guides engineers to design reliable products at a low cost
  • Assists service engineers in providing superior after-sales support
  • Enables managers to respond to the changing market and customer needs
  • Uses end-of-chapter case studies to illustrate industry best practice
  • Lifecycle approach to reliability, maintenance and spares provisioning

Reliability Engineering and Service is an important book for graduate engineering students, researchers, and industry-based reliability practitioners and consultants.




Chapter 1: Reliability Concepts and Models

1.0 Introduction

1.1 Reliability Definition and Hazard Rate

1.1.1 Managing Reliability for Product Life Cycle

1.1.2 Reliability is a Probabilistic Measure

1.1.3 Failure Rate and Hazard Rate Function

1.1.4 Bathtub Hazard Rate Curve

1.1.5 Failure Intensity Rate

1.2 Mean Lifetime and Mean Residual Life

1.2.1 Mean-Time-to-Failure

1.2.2 Mean-Time-Between-Failures

1.2.3 Mean-Time-Between-Replacements

1.2.4 Mean Residual Life

1.3 System Downtime and Availability

1.3.1 Mean-Time-To-Repair

1.3.2 System Availability

1.4 Discrete Random Variable for Reliability Modeling

1.4.1 Bernoulli Distribution

1.4.2 Binomial Distribution

1.4.3 Poisson Distribution

1.5 Continuous Random Variable for Reliability Modeling

1.5.1 The Uniform Distribution

1.5.2 The Exponential Distribution

1.5.3 The Weibull Distribution

1.5.4 The Normal Distribution

1.5.5. The Lognormal Distribution

1.5.6 The Gamma Distribution

1.6 Bayesian Reliability Model

1.6.1 Concept of Bayesian Reliability Inference

1.6.2 Bayes Formula

1.7 Markov Model and Poisson Process

1.7.1 Discrete Markov Model

1.7.2 Birth-Death Model

1.7.3 Poisson Process



Chapter 2: Reliability Estimation with Uncertainty

2.0 Introduction

2.1 Reliability Block Diagram

2.2 Series Systems

2.2.1 Reliability of Series Systems

2.2.2 Mean and Variance of Reliability Estimate

2.3 Parallel Systems

2.3.1 Reliability of Parallel Systems

2.3.2 Mean and Variance of Reliability Estimate

2.4 Mixed Series and Parallel Systems

2.4.1 Series-Parallel System

2.4.2 Parallel-Series System

2.4.3 Mixed Series-Parallel System

2.5 Systems with k-out-of-n:G Redundancy

2.5.1 Reliability for Hot-Standby Redundant Systems

2.5.2 Application to Data Storage Systems

2.6 Network Systems

2.6.1. Edge Decomposition

2.6.2 Minimum Cut Set

2.6.3 Minimum Path Set

2.6.4 Linear-Quadratic Approximation to Terminal-Pair Reliability

2.6.5 Moments of Terminal-Pair Reliability Estimate

2.7 Reliability Confidence Intervals

2.7.1 Confidence Interval for Pass/Fail Tests

2.7.2 Confidence Intervals for System Reliability

2.8 Reliability of Multi-State Systems

2.8.1 Series or Parallel Systems with Three-State Components

2.8.2 Universal Generating Function

2.9 Reliability Importance Measures

2.9.1 Marginal Reliability Importance

2.9.2 Joint Reliability Importance Measure

2.9.3 Integrated Importance Measure for Multi-State System

2.9.4 Integrated Importance Measure for System Lifetimes



Chapter 3: Design and Optimization for Reliability

3.0 Introduction

3.1 Life Cycle Reliability Optimization

3.1.1 Reliability-Design Cost

3.1.2 Reliability-Manufacturing Cost

3.1.3 Minimize Product Life cycle cost

3.2 Reliability and Redundancy Allocation

3.2.1 Reliability Allocation for Cost minimization

3.2.2 Reliability Allocation under Cost Constraint

3.2.3 Redundancy Allocation for Series System

3.2.4 Redundancy Allocation for k-out-of-n Subsystems

3.3 Multi-Objective Reliability-Redundancy Allocation

3.3.1 Pareto Optimality

3.3.2 Maximize Reliability and Minimize Variance

3.3.3 Numerical Experiment

3.4 Failure-in-Time Based Design

3.4.1 Component Failure Rate Estimate

3.4.2 Component with Life Data

3.4.3 Component without Life Data

3.4.4 Non-Component Failure Rate

3.5 Failure Rate Considering Uncertainty

3.5.1 Temperature Variation

3.5.2 Electrical Derating Variation

3.6 Fault Tree Method

3.6.1 Functional Diagram

3.6.2 Fault Tree Analysis

3.7 Failure Mode, Effect and Criticality Analysis

3.7.1 Priority Risk Number

3.7.2 Criticality Analysis

3.8 Case Study: Design for Six-Sigma

3.8.1 Principle of Design for Six-Sigma

3.8.2 Design for Printed Circuit Board Reliability



Chapter 4: Reliability Growth Planning

4.0 Introduction

4.1 Classification of Failures

4.2 Failure Mode Types

4.1 Surfaced Failure Modes

4.2 Latent Failure Modes

4.3 No-Fault Found (NFF) Failures

4.3.1 The Cause of NFF

4.3.2 The Impact of NFF

4.4 Corrective Action Effectiveness

4.4.1 Engineering Change Order versus Retrofit

4.4.2 Corrective Action Effectiveness

4.5 Reliability Growth Model

4.5.1 Duane Postulate

4.5.2 Power Law Model

4.5.3 Trend Test Statistics

4.5.4 Bounded Failure Intensity Model

4.5.5 Bayesian Projection Model

4.6 Reliability Growth and Demonstration Test

4.6.1 Optimal Reliability Growth Test

4.6.2 Reliability Demonstration Test

4.7 Lifecycle Reliability Growth Planning

4.7.1 Reliability Growth of Field Systems

4.7.2 Prediction of Latent Failure Modes

4.7.3 Allocation of Corrective Action Resource

4.8 Case Study

4.8.1 Optimizing Reliability Growth Test of Diesel Engine

4.8.2 Multi-Phase Reliability Growth Strategy



Chapter 5: Accelerated Stress Testing and Economics

5.0 Introduction

5.1 Design of Accelerated Stress Test

5.1.1 HALT, HASS and ESS

5.1.2 Types of Accelerating Stresses

5.1.3 Stress Profiling

5.2 Scale Acceleration Model and Usage Rate

5.2.1 Exponential Accelerated Failure Time Model

5.2.2 Weibull AFT Model

5.2.3 Lognormal AFT Model

5.2.4 Linear Usage Rate Acceleration Model

5.2.5 Miner’s Rule under Cyclic Loading

5.3 Arrhenius Model

5.3.1 Accelerated Life Factor

5.3.2 Other Units for Activation Energy

5.4 Eyring Model and Power Law Model

5.4.1 Eyring Model

5.4.2 Inverse Power Law Model

5.5 Semi-Parametric Acceleration Models

5.5.1 Proportional Hazard Model

5.5.2 PH Model with Weibull Hazard Rate

5.5.3 Logistic Regression Model

5.5.4 Log-Logistic Regression Model

5.6 Highly Accelerated Stress Screening Test

5.6.1 Production with HASS vs. Non-HASS

5.6.2 Financial Justification of HASS

5.7 Case Study for HASS Project

5.7.1 DMAIC in Six-Sigma Reliability Program

5.7.2 Define—Financial Analysis and Project Team

5.7.3 Measure—Infant Mortality Distribution

5.7.4 Analyze—Root Cause of Early Failures

5.7.5 Improve—Action Taken

5.7.6 Control—Monitoring and Documentation



Chapter 6: Renewal Theory and Superimposed Renewal

6.0 Introduction

6.1 Renewal Integral Equation

6.1.1 Overview of Renewal Solution Methods

6.1.2 Generic Renewal Function

6.1.3 Renewal in Laplace Transform

6.1.4 Geometric and Geometric-Type Renewal

6.1.5 Generalized Renewal Process

6.2 Exponential and Erlang Renewal

6.2.1 Exponential Renewal

6.2.2 Erlang Renewal

6.3 Generalized Exponential Renewal

6.3.1 Generalized Exponential Distribution

6.3.2 Renewal in Laplace Transform

6.3.3 Inverse Laplace Transform

6.4 Weibull Renewal with Decreasing Failure Rate

6.4.1 Approximation by Mixed Exponential Functions

6.4.2 Laplace and Inverse Laplace Transform

6.5 Weibull Renewal with Increasing Failure Rate

6.5.1 Transient Renewal Function

6.5.2 Approximation with no Oscillation

6.5.3 Approximation with Oscillation

6.6 Renewals under Deterministic Fleet Expansion

6.6.1. Superimposed Exponential Renewal

6.6.2. Superimposed Erlang Renewal

6.6.3. Lead-time Renewal

6.7 Renewal under Stochastic Fleet Expansion

6.7.1. Aggregate Exponential Renewal

6.7.2. Lead-time Renewal

6.8 Case Study

6.8.1. Installed Base of Wind Turbine

6.8.2. Spare Parts Prediction under Fleet Expansion



Chapter 7: Performance-Based Maintenance

7.0 Introduction

7.1 Corrective Maintenance

7.1.1 Classification of Maintenance Policy

7.1.2 Corrective Maintenance Management

7.2 Preventive Maintenance

7.2.1 Block Replacement

7.2.2 Age-based Replacement

7.3 Condition-Based Maintenance

7.3.1 Principle of Condition-based Maintenance

7.3.2 Proportional Hazard Model

7.3.3 Gamma Degradation Process

7.3.4 Stationary Gamma Degradation Process

7.4 Inverse Gaussian Degradation Process

7.4.1 Distribution of Inverse Gaussian process

7.4.2 Probability Density of First Passage Time

7.5 Non-Stationary Gaussian Degradation Process

7.5.1 The Degradation Concept

7.5.2 Hypothesis Testing

7.5.3 Estimation of Remaining Useful Life

7.6 Performance-Based Maintenance

7.6.1 The Rise of Performance-Based Service

7.6.2 Procedure for PBM implementation

7.6.3 Five Overarching Performance Measures

7.6.4 Reliability and MTBF Considering Usage Rate

7.6.5 Operational Availability Under Corrective Maintenance

7.6.6 Operational Availability Under Preventive Maintenance

7.7 Contracting for Performance-Based Logistics

7.7.1 Incentive Payment Schemes

7.7.2 Game-Theoretic Contracting Model

7.8 Casey study: RUL Prediction of Electronic Instrument

7.8.1 Built-in Self-Test program

7.8.2 A 4-Step process for RUL prediction



Chapter 8: Warranty Models and Service

8.0 Introduction

8.1 Warranty Concept and Its Roles

8.1.1 Overview of warranty Services

8.1.2 Classification of warranty Policy

8.2 Warranty Policy for Non-Repairable Products

8.2.1 Warranty Reserve under Pro-Rata Rebate

8.2.2 Warranty Reserve under Fixed Rebate

8.2.3 Mixed Warranty Policy

8.2.4 Optimal Preventive Maintenance under Warranty

8.3 Warranty Policy for Repairable Products

8.3.1 Warranty Cost for as-Good-as-New Repair

8.3.2 Warranty Cost for Minimum Repair Policy

8.4 Warranty Cost with Variable Sales

8.4.1 Pro Rata Rebate

8.4.2 Constant Rebate

8.5 Warranty Cost in Reliability Growth

8.5.1 Warranty Planning from Customer Perspective

8.5.2 System Availability under Different Service Modes

8.5.3 Fleet Downtime Cost to Customer

8.5.4 Minimizing the Downtime Cost

8.6 Other Warranty Models

8.6.1 Two-Dimensional Warranty

8.6.2 Extended Warranty Service

8.7 Case Study: Design for Warranty

8.7.1 Minimizing Warranty Cost

8.7.2 Application to Electronics Product Design



Chapter 9: Basic Spare Parts Inventory Models

9.0 Introduction

9.1 Overview of Inventory Model

9.1.1 Inventory Cost and Review Policy

9.1.2 Inventory Demand Patterns

9.2 Deterministic EOQ Model

9.2.1 EOQ with No Backorders

9.2.2 EOQ with Backlogging

9.3 The Newsvendor Model

9.3.1 The Single-Period Inventory Model

9.3.2 Inventory Performance Measures

9.4 The (q, r) Inventory System under Continuous Review

9.4.1 Optimal Policy with Fixed Lead Time

9.4.2 Recorder Point with Variable Lead Time

9.4.3 The Base Stock Policy

9.5 The (s, S, T) Policy under Periodic Review

9.5.1 The Inventory Control Mechanism

9.5.2 Approximation Solution to Optimal Policy

9.5.3 Variable Lead Time

9.5.4 The (S-1, S, T) Periodic-Review Policy

9.6 Basic Supply Chain Systems

9.6.1 The Concept of Echelon Inventory

9.6.2 Bullwhip Effects and Supply Resilience

9.7 Spare Parts Demand Forecasting

9.7.1 Spare Parts Demand Pattern

9.7.2 Data-Driven Method

9.7.3 Reliability Regression Model

9.7.4 Installation Based Model

9.7.5 Forecasting under Reliability Growth and Fleet Expansion



Chapter 10: Repairable Inventory System

10.0 Introduction

10.1 Characteristics of Repairable Inventory System

10.1.1 Spare Parts Supply Mode

10.1.2 Item-Level Performance Measure

10.1.3 System-Level Performance Measure

10.1.4 Item Approach versus System Approach

10.2 Single Echelon Inventory with Uncapacitated Repair

10.2.1 Operational Structure

10.2.2 Demand during Repair Turn-Around Time

10.2.3 Performance Characterization

10.2.4 Variance of Backorders

10.3 Single Echelon Inventory with Capacitated Repair

10.3.1 Operational Structure

10.3.2 Performance Characterization

10.3.3 Expected Backorders and On-hand Inventory

10.4 Repairable Inventory for a Finite Fleet Size

10.4.1 The Machine-Inventory Model

10.4.2 Performance Characterization

10.5 Single Echelon Inventory with Emergency Repair

10.5.1 Prioritizing Repair and Supply Services

10.5.2 Performance Characterization

10.6 Repairable Inventory Planning under Fleet Expansion

10.6.1 Non-Stationary Parts Demand

10.6.2 Multi-Resolution Inventory Control

10.6.3 Optimization Model and Algorithm

10.7 Multi-Echelon, Multi-Item Repairable Inventory

10.7.1 Basic Assumptions of the METRIC Model

10.7.2 Compound Poisson Demand

10.7.3 Expected Backorders for Single Item

10.7.4 Multi-Echelon, Multi-Item Optimization Model

10.8 Case Study: Teradyne’s Spare Parts Supply Chain

10.8.1 Distributed Product-Service Operation

10.8.2 Global Customer Services

10.8.3 Repair Turn-Around Time and Failure Mode



Chapter 11: Reliability and Service Integration

11.0 Introduction

11.1 The Rise of Product-Service System

11.1.1 Blurring between Product and Service

11.1.2 Technological Factors

11.1.3 The State of the Art

11.2 Reliability-Inventory Allocation under a Static Fleet

11.2.1 Life cycle cost Analysis

11.2.2 Minimizing Life cycle cost of Single-Item Fleet

11.2.3 Maximizing Service Profit of Multi-Item System Fleet

11.2.4 Optimization Algorithms

11.3 Allocation of Reliability and Inventory under Fleet Expansion

11.3.1 Multi-Resolution Inventory Policy

11.3.2 Estimating the Inventory Cost

11.3.3 Life cycle cost of a Variable-Size Fleet

11.3.4 Optimization Model and Solution Algorithms

11.4 Joint Allocation of Maintenance, Inventory and Repair Capacity

11.4.1 Inventory Demand under Preventive Maintenance

11.4.2 Estimating the Cost of Product-Service System

11.4.3 Principal-Agent Service Contracting Model

11.4.4 Moral Hazard and Asymmetric Information

11.4.5 First Best Solution

11.5 Case Study: Supporting Wind Industry Operation using PBC

11.5.1 Line Replaceable Units of Wind Turbine

11.5.2 Maximizing the Service Profitability



Chapter 12: Resilience Engineering and Management

12.0 Introduction

12.1 Resilience Concept and Measures

12.1.1 Resilience in Different Domains

12.1.2 Resilience Curves

12.1.3 Resilience Measures

12.2 Disaster Resilience Models of Power Grid

12.2.1 Reliability versus Resilience

12.2.2 Reliability Measures of Power Systems

12.2.3 Resilience Measures of Power Systems

12.2.3 Modelling Hurricane Events

12.3 Prevention, Survivability and Recovery

12.3.1 Three Aspect of Power Resilience

12.3.2 Hardening

12.3.3 Proactive Maintenance

12.3.4 Decentralized Resource Allocation

12.3.5 Recovery and Restoration

12.4 Variable Generation System Model

12.4.1 Wind Turbine System

12.4.2 Solar Photovoltaic System

12.4.3 Battery Charge and Discharge Model

12.4.4 Demand Response Model

12.5 Case Study: Design for Distribution Resilience

12.5.1 Background Data

12.5.2 Prevention via Distributed Power Allocation

12.5.3 Survivability via Microgrid Operation

12.5.4. Multi-Team Repair and Recovery




Appendix A

Appendix B

Subject Index