Reliability and Risk Modeling of Engineering Systems (EAI/Springer Innovations in Communication and Computing)

✍ Scribed by Dilbagh Panchal (editor), Prasenjit Chatterjee (editor), Dragan Pamucar (editor), Mohit Tyagi (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 178
• Category: Library

✦ Synopsis

This book addresses reliability, maintenance, risk, and safety issues of industrial systems with applications of the latest decision-making techniques. Thus, this book presents chapters that apply advanced tools, techniques, and computing models for optimizing the performance of industrial and manufacturing systems, along with other complex engineering equipment. Computing techniques like data analytics, failure mode and effects analysis, fuzzy set theory, petri-net, multi-criteria decision-making (MCDM), and soft computing are used for solving problems of reliability, risk, and safety related issues.

✦ Table of Contents

Preface
Reliability and Risk Modelling of Engineering Systems
Organization of the Book
Acknowledgments
Contents
About the Editors
1: Behavior Analysis of Polytube Industry Using Fuzzy Set Theory and Particle Swarm Optimization
1.1 Introduction
1.2 Methodology
1.3 System Study
1.3.1 System Description
1.3.2 Notations
1.3.3 Transient State
1.3.4 Mathematical Formulation
1.4 Results and Discussion
1.5 Conclusion
References
Chapter 2: RAM Analysis of Industrial System of a Chemical Industry
2.1 Introduction
2.2 Basic Concept of Fuzzy Sets and Membership Function
2.3 Fuzzy Lambda Tau Approach
2.4 Case Study
2.5 Application of Proposed Methodology
2.6 Behavioral Analysis
2.7 Conclusion
References
Chapter 3: Signature Reliability of Consecutive k-out-of-n: F System using Universal Generating Function
3.1 Introduction
3.2 Algorithm for Evaluating the UGF of r Consecutive Elements Groups (See Levitin and Ben-Haim)
3.3 Assessment of m Consecutive Failed Groups to Consecutive SWS (See Levitin and Ben-Haim)
3.4 Algorithm of Calculating Reliability of Consecutive SWS (See Levitin and Ben-Haim)
3.4.1 Algorithm to Find the Signature of Consecutive SWS
3.4.2 Algorithm to Determine the Expected Time of the Proposed System
3.4.3 Algorithm to Find the Barlow-Proschan of Consecutive SWS
3.4.4 Algorithm for Determining the Expected X
3.4.5 Sensitivity of the Consecutive SWS
3.5 Illustrative Example
3.5.1 Signature of the System
3.5.2 Expected Lifetime of System
3.5.3 Expected Cost Rate of Consecutive SWS
3.5.4 Barlow-Proschan Index of System
3.5.5 Sensitivity of Consecutive SWS
3.6 Conclusion
References
Chapter 4: Integrating Reliability, Availability, and Maintainability Issues for Analyzing Failures in Fuel Injection Pump
4.1 Introduction
4.2 Related Work
4.3 Basic Concepts and Definitions
4.3.1 Reliability
4.3.2 Maintainability
4.3.3 Availability
4.3.4 Root Cause Analysis (RCA)
4.3.5 Failure Mode and Effects Analysis (FMEA)
4.4 Illustrative Case
4.4.1 Subsystem´s Reliability, Availability, and Maintainability (RAM) Analysis
4.4.2 Failure Rate and Repair Rate for Different Components
4.4.3 Reliability Block Diagram
4.5 RAM Analysis
4.5.1 Reliability Estimation
4.5.2 Availability Estimation
4.5.3 Maintainability Estimation
4.5.4 Root Cause Analysis (RCA)
4.5.5 Failure Mode and Effects Analysis
4.6 Results and Discussion
References
Chapter 5: Multi-State Reconfigurable Manufacturing System Configuration Design with Availability Consideration
5.1 Introduction
5.1.1 Aim of Chapter
5.2 Literature Review
5.3 Mathematical Formulation
5.3.1 Economic Objective
5.3.2 Availability Objective
5.3.2.1 Universal Generating Function (UGF) for Availability Estimation
5.3.2.2 UGF for MSMS Systems with Multiple Independent Output Performance Measures
5.3.2.3 MSMS Availability
5.3.3 Integrated Objective Modelling of Multi-Objective MSMS
5.4 Integrated Objective Model Optimisation of MSMS
5.5 Solution Methodology of the Model
5.6 An Illustrative Case
5.6.1 Manufacturing System with Two Machines in Parallel Availability Assessment
5.6.2 Manufacturing System with Two Machines in Series Availability Assessment
5.6.3 Reconfigurable Manufacturing System Configuration Selection
5.7 Conclusion
References
Chapter 6: Reliability and Availability Analysis of a Standby System of PCB Manufacturing Unit
6.1 Introduction
6.2 State Transition Diagram
6.3 Transition Probabilities and Mean Sojourn Times
6.4 Mean Time to System Failure
6.5 Availability of the System
6.6 Graphical Interpretations and Conclusions
References
Chapter 7: Risk Mitigation of SGU in Sugar Plant Using Fuzzy Digraph and Matrix Approach
7.1 Introduction
7.2 Literature Review
7.2.1 Risk Identification
7.2.2 Risk Analysis and MADM Techniques
7.2.3 Integrated Approach
7.2.4 Objective
7.3 Research Methodology
7.4 Method FDMA
7.5 Case Analysis
7.6 Result and Discussion
7.7 Conclusion
References
Chapter 8: An Integrated Fuzzy MCDM-Based FMEA Approach for Risk Prioritization of Casting Defects in Electro-Pneumatic Brake ...
8.1 Introduction
8.1.1 Background
8.1.2 Motivations
8.1.3 Contributions to the Literature
8.1.4 Overview of the Work
8.2 Preliminaries
8.2.1 Fuzzy Logic
8.2.2 Fuzzy AHP
8.2.3 Fuzzy TOPSIS
8.3 Case Study
8.3.1 Description of the Risk Factors
8.3.1.1 Severity
8.3.1.2 Occurrence
8.3.1.3 Detection
8.3.2 Description of the Casting Defects
8.3.2.1 Gas Porosity Defects
Pinholes or Porosities
Subsurface Blowholes
Open Holes
8.3.2.2 Shrinkage-Related Defects
Open Shrinkage Defects
Closed Shrinkage Defect
Warping
8.3.2.3 Mold Material Defects
Cuts and Washes
Fusion
Run Out
Swell
Drops
Rat Tails, Veins, and Buckles
Metal Penetration
8.3.2.4 Metallurgical Defects
Slag Inclusion
Hot Tear/Crack
Hot Spots
8.3.2.5 Pouring Defects
8.3.2.6 Cold Shut
8.3.2.7 Misrun
8.3.2.8 Cold Shots
8.3.3 Casting Shape Defects
8.3.3.1 Mismatch/Shifts
8.3.3.2 Flash/Fin or Burrs
8.3.4 Relative Importance of Risk Factors by Fuzzy AHP
8.3.5 Risk Ranking of Casting Defects by Fuzzy TOPSIS
8.4 Validation and Discussions
8.5 Conclusions
References
Chapter 9: Dimensions Modelling for Reliable Indian Food Supply Chains
9.1 Introduction and Background
9.2 Model Development
9.3 Research Methodology
9.3.1 Analytical Hierarchical Process (AHP)
9.3.2 TODIM Approach
9.4 Numerical Illustration
9.4.1 AHP Methodology
9.4.2 TODIM
9.5 Results and Discussions
9.6 Implications and Future Scope
References
Chapter 10: RAM Analysis for Improving Productivity in Process Industries: A Review
10.1 Introduction
10.2 Literature Review
10.3 Conclusion
References
Index