Advanced Quantitative Risk
Introduction
<Advanced Quantitative Risk Assessment Method for Mechanical System in the Petroleum and Petrochemical Industry> introduces the process of implementing a quantitative risk assessment on the complex mechanical system of the petrochemical plant, the petroleum equipment, and the offshore platform equipment and facilities. The entire book explains the various links and related knowledge of studying and implementing some quanititative risk assessment mathematical models and methods. The main contents of this book include the following aspects. The historical development and current status of quantitative risk assessment worldwide are introduced. Basic concepts, purpose, results, risk acceptance criteria, basic process, classical method of the quantitative risk assessment are summed up. A streamline Failure Mode Effects and Criticality Analysis (SFMECA) was presented to achieve risk identification and quantitative evaluation based on the traditional FMECA and Borda scoring method. A practical framework for the quantitative risk analysis of the high hazard mechanical system (HHMS) is presented in the petroleum and petrochemical industry. A quantitative assessment method was proposed for the criticality analysis in the FMECA based on Fuzzy Set Theory (FST), Fuzzy Borda method (FBM) and Grey Relational Analysis (GRA). An innovative quantitative assessment method should be presented to achieve a quantitative evaluation of multi-level complex structure hierarchical system by established an multi-level Borda model (MLBM). A framework for identification of Maintenance Significant Items (MSI) through combination of quantitative analysis with qualitative analysis is proposed for Reliability Centered Maintenance (RCM). A framework for making maintenance decisions was presented based on a quantitative assessment method and a decision-making model. A delay time model (DTM), including failure renewal model, inspection renewal model and no failure renewal model of the wearing parts was established respectively in the ideal inspection and non-ideal inspection case. Consequently, these advanced quantitative assessment method for mechanical system can help to popularize the applications of prognostics and health management (PHM), reliability centered maintenance (RCM) and asset integrity management (AIM) in high-risk industries.
This book is mainly for failure risk identification method, quantitative risk evaluation mathematical model and method, and case analysis of complex machinery and equipment in petrochemical station, oil field station and offshore platform. So far, this is the first book for quantitative risk assessment of complex structural mechanical system in the petroleum and petrochemical industry.
<Advanced Quantitative Risk Assessment Method for Mechanical System in the Petroleum and Petrochemical Industry> can be used as a reference for risk assessment researchers, high-risk machinery operators and managers, safety appraisers, managers, safety technicians, safety engineering teachers and graduate students, machinery failure diagnosis and maintenance decision-making professionals.
978-981-14-4744-0
1 History and Current Status of International Quantitative Risk Assessment
1.1 Introduction
1.2 History and current status of foreign quantitative risk assessment
1.3 History and current status of quantitative risk assessment in China
2 Introduction to Quantitative Risk Assessment
2.1 Purpose of quantitative risk assessment
2.2 Results of quantitative risk assessment
2.2.1 Related terminology
2.2.2 Individual acceptable risk criteria
2.2.3 Criteria for socially acceptable risk
2.3 Quantitative risk assessment risk acceptance criteria
2.4 The basic process of quantitative risk assessment
2.5 Risk Assesment Methods
2.5.1 Qualitative Methods
2.5.2 Quantitative Methods
3 Risk Identification and Quantitative Evaluation Method
3.1 Introduction
3.2 Problem Statement
3.3 FMEA and FMECA
3.4 Establishment of streamline Failure Mode Effects and Criticality Analysis
3.5 Quantitative evaluation method of comprehensive risk based on Borda scoring method
3.6 Case study
3.7 Conclusion
Reference
4 Quantitative Risk Analysis Method Based on Bow-tie
4.1 Introduction
4.2 Problem Statement
4.3 Conventional Risk Analysis Methods for Mechanical Systems
4.3.1 FMECA
4.3.2 Fault Tree Analysis
4.3.3 Event Tree Analysis
4.3.4 Bow-Tie Model
4.4 Study on a Quantitative Risk Analysis Method for HHMS
4.4.1 Establishing a Hierarchical Structure Tree
4.5 Study on a Data Processing Method for Hybrid Data
4.5.1 Triangular Fuzzy Number
4.5.2 Method for Fuzzification and Defuzzification
4.5.3 Fuzzy Method for a Crisp Number
4.6 Study on a Fuzzy Fault Tree Analysis
4.7 Study on a Fuzzy Event Tree Analysis
4.8 Study of a Fuzzy Bow-Tie Model
4.9 Case Study
4.10 Conclusions
References
5 Quantitative Assessment Method for Comprehensive Criticality Analysis
5.1 Introduction
5.2 Problem Statement
5.3 Analysis on the existing QRA of the CA
5.4 A new QRA method of the CA
5.5 Case Study
5.6 Discussions and Conclusions
References
6 Quantitative Risk Evaluation Model of the Multi-level Complex Structure Hierarchical System
6.1 Introduction
6.2 Problem Statement
6.3 Risk hierarchy analysis on the complex structural system
6.4 Establishment of Mathematical Model of MLBM
6.4.1 Modeling parameter setting
6.4.2 Algorithm and process
6.5 Case study
6.6 Conclusion
References
7 Identification Method of the Significant Items
7.1 Introduction
7.2 Problem Statement
7.3 Method for screening out the non-MSI
7.3.1 Definition system and the first screening
7.3.2 Failure Mode and Effects Analysis and Risk Analysis
7.3.3 The second screening based on risk matrix
7.4 Method for determining level of the MSI
7.4.1 Establish evaluation indexes and scoring standard
7.4.2 Scoring analysis based on the APH method
7.4.3 Importance ranking based on Fuzzy Borda Count method
7.5 Case study
7.6 Conclusion
References
8 Importance Level Evaluation Method for Making Maintenance Decisions
8.1 Introduction:
8.2 Problem Statement
8.3 Definition of the evaluation indexes and scoring criteria
8.4 Evaluation model for the importance level of the DPE
8.4.1 Quantitative evaluation based on the AHP method
8.4.2 Analysis of eliminating the subjective factors based on the MCS
8.5 Decisions on maintenance based on the importance level of equipment
8.6 Case study
8.7 Conclusion
References
9 Parameter Quantitative Estimation Method of Delay Time Model
9.1 Introduction
9.2 Problem Statement
9.3 The delay time concept
9.3.1 Function Inspection
9.3.2 Delay Time Concept
9.4 The DTM of wearing parts
9.4.1 Assumptions and Notation
9.4.2 The Ideal Inspection Model
9.4.3 The Non-Ideal Inspection Model
9.5 Delay time model algorithm
9.5.1 Establishing the Likelihood Function
9.5.2 Method of Solving Maximum Likelihood Function
9.6 Numerical example
9.6.1 The Ideal Inspection Model Numerical Example
9.6.2 The Non-Ideal Inspection Model Numerical Example
9.7 Conclusion
References
Author(s) Information
Yang Tang received his B.E. degree in Process Equipment and Control Engineering from Southwest Petroleum University, China, 2010. He received his M.E. degree in Fluid machinery and Engineering from Southwest Petroleum University，China，2013. He received his Ph.D. degree in Mechanical Engineering from Southwest Petroleum University，China， 2016. He was a Visiting Scholar in the IMS Center of the University of Cincinnati, USA, 2017-2018. He was awarded the Chinese Postdoctoral Innovative Talents Program in 2019. He once served as executive director and secretary of the Sichuan Mechanical Association Graduate Branch. Now he is Associate Research Fellow and Master Tutor in mechanical engineering at the Southwest Petroleum University, China.
Guorong Wang received his B.E. degree in mechanical engineering from Southwest Petroleum University，China，1998. He received his M.E. degree in mechanical engineering from Southwest Petroleum University, China, 2001. He received his Ph.D. degree in mechanical engineering from Southwest Petroleum University, China, 2004. He is the head of national key R & D technology projects. He has won the China Youth Science and Technology Award, selected by the National Ten Thousand Million Talent Project, the State Council Special Subsidy for Government Affairs Expert, Tianfu Ten Thousand People Plan Innovation Leading Talent, Sichuan Academy Technology leader, etc.
