Binary decision diagrams and extensions for system reliability analysis / Liudong Xing, Suprasad V. Amari.

Binary decision diagrams and extensions for system reliability analysis /

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"Recent advances in science and technology have made modern computing and engineering systems more powerful and sophisticated than ever. The increasing complexity and scale imply that system reliability problems not only continue to be a challenge but also require more efficient models and solu...

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Bibliographic Details
Main Author: Xing, Liudong
Other Authors: Amari, Suprasad V.
Format: Electronic eBook
Language:English
Published: Hoboken, New Jersey : John Wiley and Sons, Inc., 2015.
Series:Performability engineering series.
Subjects:
Reliability (Engineering) > Graphic methods.
System analysis > Graphic methods.
Decision trees.
Decision Trees
Online Access: Full text (Wentworth users only)
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Preface
  • Nomenclature
  • 1 Introduction
  • 1.1 Historical Developments
  • 1.2 Reliability and Safety Applications
  • 2 Basic Reliability Theory and Models
  • 2.1 Probabiltiy Concepts
  • 2.1.1 Axioms of Probability
  • 2.1.2 Total Probability Law
  • 2.1.3 Random Variables
  • 2.1.4 Parameters of Random Variables
  • 2.1.5 Lifetime Distributions
  • 2.2 Reliability Measures
  • 2.2.1 Time-to-Failure and Failure Function
  • 2.2.2 Reliability Function
  • 2.2.3 Failure Rate Function
  • 2.2.4 Mean Time to Failure
  • 2.2.5 Mean Residual Life
  • 2.3 Fault Tree Analysis
  • 2.3.1 Overview
  • 2.3.2 Fault Tree Construction
  • 2.3.3 Different Forms of Fault Trees
  • 2.3.3.1 Static Fault Trees
  • 2.3.3.2 Dynamic Fault Trees (DFTs)
  • 2.3.3.3 Noncoherent Fault Trees
  • 2.3.4 Types of Fault Tree Analysis
  • 2.3.4.1 Qualitative Analysis
  • 2.3.4.2 Quantitative Analysis
  • 2.3.5 Fault Tree Analysis Techniques
  • 2.3.5.1 Inclusion-Exclusion (I-E)
  • 2.3.5.2 Sum of Disjoint Products (SDPs)
  • 3 Fundamentals of Binary Decision Diagrams
  • 3.1 Preliminaries
  • 3.2 Basic Concepts
  • 3.3 BDD Construction
  • 3.3.1 Input Variable Ordering
  • 3.3.2 OBDD Generation
  • 3.3.3 ROBDD Generation
  • 3.3.4 Example Illustrations
  • 3.4 BDD Evaluation
  • 3.5 BDD-Based Software Package
  • 4 Application of BDD to Binary-State Systems
  • 4.1 Network Reliability Analysis
  • 4.2 Event Tree Analysis
  • 4.3 Failure Frequency Analysis
  • 4.3.1 Steady-State System Failure Frequency
  • 4.3.2 Time-Dependent System Failure and Success Frequencies
  • 4.4 Importance Measures and Analysis
  • 4.4.1 Deterministic Importance Measures
  • 4.4.2 Probabilistic Importance Measures
  • 4.4.2.1 Birnbaum's Measure
  • 4.4.2.2 Criticality Importance Factor
  • 4.4.2.3 Fussell-Vesely Measure
  • 4.5 Modularization Methods
  • 4.6 Non-Coherent Systems.
  • 4.6.1 Prime Implicants Based Method
  • 4.6.2 BDD Based Method
  • 4.7 Disjoint Failures
  • 4.8 Dependent Failures
  • 4.8.1 Common-Cause Failures (CCFs)
  • 4.8.2 Functional Dependent Failures
  • 5 Phased-Mission Systems
  • 5.1 System Description
  • 5.2 Rules of Phase Algebra
  • 5.3 BDD-Based Method for PMS Analysis
  • 5.3.1 Input Variable Ordering
  • 5.3.2 Single-Phase BDD Generation
  • 5.3.3 PMS BDD Generation
  • 5.3.4 PMS BDD Evaluation
  • 5.4 Mission Performance Analysis
  • 6 Multi-State Systems
  • 6.1 Assumptions
  • 6.2 An Illustrative Example
  • 6.3 MSS Representation
  • 6.3.1 MSS Representation Using MFT
  • 6.3.2 MSS Representation Using MRBD
  • 6.3.3 Equivalency of MRBD and MFT Representations
  • 6.4 Multi-State BDD (MBDD)
  • 6.4.1 Step 1
  • State Variable Encoding
  • 6.4.2 Step 2
  • Generating MBDD from MFT
  • 6.4.3 Step 3
  • MBDD Evaluation
  • 6.4.4 Example Illustration
  • 6.5 Logarithmically-Encoded BDD (LBDD)
  • 6.5.1 Step 1
  • Variable Encoding
  • 6.5.2 Step 2
  • Generating LBDD from MFT
  • 6.5.3 Step 3
  • LBDD Evaluation
  • 6.5.4 Example Illustration
  • 6.6 Multi-State Multi-Valued Decision Diagrams (MMDD)
  • 6.6.1 Step 1
  • Variable Encoding
  • 6.6.2 Step 2
  • Generating MMDD from MFT
  • 6.6.3 Step 3
  • MMDD Evaluation
  • 6.6.4 Example Illustration
  • 6.7 Performance Evaluation and Benchmarks
  • 6.7.1 Example Analyses
  • 6.7.2 Benchmark Studies
  • 6.7.3 Performance Comparison and Discussions
  • 6.7.3.1 Comparing Model Size
  • 6.7.3.2 Comparing Runtime Complexity of Model Construction
  • 6.7.3.3 Comparing Runtime Complexity of Model Evaluation
  • 6.8 Summary
  • 7 Fault Tolerant Systems and Coverage Models
  • 7.1 Basic Types
  • 7.2 Imperfect Coverage Model
  • 7.3 Applications to Binary-State Systems
  • 7.3.1 BDD Expansion Method
  • 7.3.2 Simple and Efficient Algorithm
  • 7.4 Applications to Multi-State Systems.
  • 7.5 Applications to Phased-Mission Systems
  • 7.5.1 Mini-Component Concept
  • 7.5.2 Extended SEA Method for PMS
  • 7.5.3 An Illustrative Example
  • 7.6 Summary
  • 8 Shared Decision Diagrams
  • 8.1 Multi-Rooted Decision Diagrams
  • 8.2 Multi-Terminal Decision Diagrams
  • 8.3 Performance Study on Multi-State Systems
  • 8.3.1 Example Analyses
  • 8.3.2 Benchmark Studies
  • 8.4 Application to Phased-Mission Systems
  • 8.4.1 PMS Analysis Using MDDs
  • 8.4.1.1 Step 1-Variable Encoding
  • 8.4.1.2 Step 2-Input Variable Ordering
  • 8.4.1.3 Step 3-PMS MDD Generation
  • 8.4.1.4 Step 4-PMS MDD Evaluation
  • 8.4.2 An Illustrative Example
  • 8.5 Application to Multi-State k-out-of-n Systems
  • 8.5.1 Multi-State k-out-of-n System Analysis Using MDDs
  • 8.5.1.1 Step 1- BDDkl Generation
  • 8.5.1.2 Step 2- MDDkl Generation
  • 8.5.1.3 Step 3- MDDSj Generation
  • 8.5.1.4 Step 4-System MDDSj Evaluation
  • 8.5.2 An Illustrative Example
  • 8.6 Importance Measures
  • 8.6.1 Capacity Networks and Reliability Modeling
  • 8.6.2 Composite Importance Measures (Type 1)
  • 8.6.2.1 General CIMs
  • 8.6.2.2 Alternative CIMs
  • 8.6.3 Computing CIMs Using MDD
  • 8.6.4 An Illustrative Example
  • 8.7 Failure Frequency Based Measures
  • 8.8 Summary
  • Conclusions
  • References
  • Index
  • EULA.

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