Production Availability and Reliability

Name: Production Availability and Reliability | Use in the Oil and Gas industry
Brand: Wiley
Price: 139.99 EUR
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Use in the Oil and Gas industry

Alain Leroy(Author)

Wiley (Publisher)

1st Edition

Published on 16. April 2018

368 pages

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System requirements

978-1-119-52242-3 (ISBN)

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System requirements

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Content

Cover
Half-Title Page
Title Page
Copyright Page
Contents
Preface
1. Basic Concepts
1.1. Introduction
1.2. Definition of terms
1.2.1. Risk
1.2.2. Time definitions
1.2.3. Failures and repairs
1.2.4. IEC 61508 terms
1.3. Definition of parameters
1.3.1. Reliability
1.3.2. Maintainability
1.3.3. Availability and production availability
1.3.4. Dependability
1.3.5. Definitions used by maintenance engineers
1.3.6. Definitions used in the refinery industry
1.4. The exponential law/the constant failure rate
1.4.1. Reliability
1.4.2. Validity
1.4.3. Oil and gas industry
1.5. The bathtub curve
1.5.1. Meaning
1.5.2. Useful life and mission life
1.5.3. Validity
1.5.4. Oil and gas industry
2. Mathematics for Reliability
2.1. Introduction
2.2. Basis of probability and statistics
2.2.1. Boolean algebra
2.2.2. Probability relations
2.2.3. Probability distributions
2.2.4. Characteristics of probability distributions
2.2.5. Families and conjugates
2.3. Formulae and theorems
2.3.1. Combinatorial analysis
2.3.2. Central limit theorem
2.3.3. Chebyshev's inequality
2.3.4. Laws of large numbers
2.3.5. Supporting functions and distributions
2.3.6. Bayes' theorem
2.4. Useful discrete probability distributions
2.4.1. Binomial distribution
2.4.2. Poisson distribution
2.5. Useful continuous probability distributions
2.5.1. Exponential distribution
2.5.2. Uniform distribution
2.5.3. Triangular distribution
2.5.4. Normal distribution
2.5.5. Log-normal distribution
2.5.6. Weibull distribution
2.5.7. Gamma distribution
2.5.8. Beta distribution
2.5.9. Chi-squared distribution
2.5.10. Fisher-Snedecor distribution
2.6. Statistical estimates
2.6.1. Estimates
2.6.2. Calculation of point estimate
2.6.3. Calculation of confidence interval
2.6.4. Heterogeneous samples
2.6.5. Implementation
2.7. Fitting of failure distribution
2.7.1. Principle
2.7.2. Median rank method
2.7.3. Implementation
2.8. Hypothesis testing
2.8.1. Principle
2.8.2. Existing tests
2.8.3. Implementation
2.9. Bayesian reliability
2.9.1. Definition
2.9.2. Use of Bayes' theorem
2.9.3. Bayesian inference
2.9.4. Selection of the prior probability distribution
2.9.5. Determination of the posterior probability distribution
2.9.6. Bayesian credibility interval
2.10. Extreme value probability distributions
2.10.1. Meaning
2.10.2. The three extreme value probability distributions
2.10.3. Use in the industry
3. Assessment of Standard Systems
3.1. Introduction
3.2. Single item
3.2.1. Availability
3.2.2. Number of failures
3.3. System reliability
3.3.1. Series systems
3.3.2. Parallel systems
3.4. Specific architectures
3.4.1. Method of analysis
3.4.2. Redundant item system
3.5. On-guard items
3.5.1. Unrevealed failures
3.5.2. Full formula
3.5.3. Optimum proof test duration
4. Classic Methods
4.1. Introduction
4.2. Failure Mode and Effects Analysis
4.2.1. Conventional Failure Mode and Effects Analysis/Failure Mode, Effects and Criticality Analysis
4.2.2. Functional/hardware FMEA
4.2.3. Case study
4.3. Fault trees
4.3.1. Conventional fault trees
4.3.2. Fault tree extensions
4.3.3. Facilities provided by software packages
4.3.4. Case study
4.4. Reliability block diagrams
4.4.1. Conventional RBDs
4.4.2. RBD extension
4.4.3. Facilities provided by software packages
4.4.4. Case study
4.5. Monte Carlo method
4.5.1. Principle
4.5.2. Use for production availability and reliability
4.5.3. How many runs are enough?
5. Petri Net Method
5.1. Introduction
5.2. Petri nets
5.2.1. Definition
5.2.2. Mathematical properties
5.2.3. Petri net construction
5.2.4. GRAFCET
5.3. IEC 62551 extensions
5.3.1. Extensions to structure
5.3.2. Modified execution rules
5.4. Additional extensions
5.4.1. Extensions to structure
5.4.2. Modified execution rules
5.5. Facilities provided by software packages
5.5.1. Additional extensions to structure
5.5.2. Modified execution rules
5.5.3. Petri net processing
5.5.4. Results
5.6. Petri net construction
5.6.1. Petri net modeling
5.6.2. Minimizing the risk of error input
5.6.3. Petri net checking
5.6.4. Petri net validation
5.7. Case study
5.7.1. System description
5.7.2. Petri net model
6. Sources of Reliability Data
6.1. Introduction
6.2. The OREDA project
6.2.1. History
6.2.2. Project management and organization
6.2.3. Description of OREDA 2015 handbooks
6.2.4. Use of the data tables
6.2.5. Use of the additional tables
6.2.6. Reliability database and data analysis software
6.2.7. Data collection software
6.3. The PDS handbook
6.3.1. History
6.3.2. Description of the handbook
6.3.3. Use of the handbook
6.4. Reliability Analysis Center/Reliability Information Analysis Center publications
6.4.1. History
6.4.2. Non-electronic Part Reliability Data handbook
6.4.3. FMD
6.4.4. NONOP
6.4.5. Use of the publications
6.5. Other publications
6.5.1. EXIDA handbooks
6.5.2. Electrical items
6.5.3. Pipelines
6.5.4. Flexibles
6.5.5. Miscellaneous
6.6. Missing information
7. Use of Reliability Test and Field Data
7.1. Introduction
7.2. Reliability test data
7.2.1. Principle
7.2.2. Test organization
7.2.3. Assessment of failure rate
7.3. Field data
7.3.1. Principle
7.3.2. Data collection organization
7.3.3. Assessment of failure rate
7.3.4. Assessment of probability to fail upon demand
7.3.5. Assessment of MRT
7.3.6. Case study
7.4. Accelerated tests
7.4.1. Principle
7.4.2. Example
7.4.3. Highly accelerated tests
7.5. Reliability growth
7.5.1. Principle
7.5.2. Main models
8. Use of Expert Judgment
8.1. Introduction
8.2. Basis
8.2.1. Definitions
8.2.2. Protocol for expert elicitation
8.2.3. Role of the facilitator
8.3. Characteristics of the experts
8.3.1. Definition
8.3.2. Selection
8.3.3. Biases
8.3.4. Expert weighting
8.3.5. Expert dependence
8.3.6. Aggregation of judgments
8.4. Use of questionnaires
8.4.1. Conditions of use
8.4.2. The Delphi method
8.4.3. Case study
8.5. Use of interactive group
8.5.1. Number of experts
8.5.2. Procedure
8.6. Use of individual interviews
8.6.1. Conditions of use
8.6.2. Case study
8.7. Bayesian aggregation of judgment
8.7.1. Form of information provided by experts
8.7.2. Assessment of failure rate (or MTBF)
8.7.3. Assessment of probability of failure upon demand
8.8. Validity of expert judgment
9. Supporting Topics
9.1. Introduction
9.2. Common cause failures
9.2.1. Introduction
9.2.2. Definition
9.2.3. Defenses against CCF
9.2.4. CCF modeling with the beta-factor method
9.2.5. CCF modeling with the shock method
9.2.6. Extension of the beta-factor model: the PDS method
9.2.7. Field data
9.2.8. Impact of CCF on system reliability
9.2.9. Impact of testing polisy on CCF
9.3. Mechanical reliability
9.3.1. Characteristics
9.3.2. Stress-strength interference
9.3.3. Empirical reliability relationships
9.3.4. Comparison with system (constant failure rate) approach
9.4. Reliability of electronic items
9.4.1. Characteristics
9.4.2. MIL-HDBK-217
9.4.3. UTE-C-80811
9.4.4. Other reliability data books
9.4.5. EPRD
9.4.6. Effect of dormancy period
9.4.7. Common cause failures
9.4.8. Comparison of previsions
9.4.9. Use in the oil and gas industry
9.5. Human reliability
9.5.1. Human factors
9.5.2. Human reliability in the nuclear industry
9.5.3. Evaluation of HRA techniques
9.5.4. Human reliability in the oil and gas industry
10. System Reliability Assessment
10.1. Introduction
10.2. Definition of reliability target
10.2.1. Absolute reliability target
10.2.2. Risk target
10.3. Methodology of system reliability study
10.3.1 Overall description
10.3.2. Step 1: system analysis
10.3.3. Step 2: qualitative analysis
10.3.4. Step 3: quantitative data selection
10.3.5. Step 4: system reliability modeling
10.3.6. Step 5: synthesis
10.4. SIL studies
10.4.1. Introduction
10.4.2. SIL assignment
10.4.3. SIL demonstration
10.5. Description of the case study
10.5.1. Origin of the risk
10.5.2. Description of the standard SIF
10.5.3. Risk assessment
10.6. System analysis
10.6.1. Description of HIPS functioning
10.7. Qualitative analysis
10.7.1. FMEA
10.7.2. CCF analysis
10.8. Quantitative data selection
10.8.1. Selection of reliability data
10.8.2. Collection of proof test data
10.8.3. CCF quantification
10.9. System reliability modeling
10.9.1. Building of system reliability model
10.9.2. System reliability calculation
10.10. Synthesis
10.10.1. Conclusions
10.10.2. Recommendations
10.11. Validity of system reliability assessments
10.11.1. Reports
10.11.2. Conclusions
11. Production Availability Assessment
11.1. Introduction
11.2. Definition of production availability target
11.2.1. Absolute production availability target
11.2.2. Economic target
11.3. Methodology
11.3.1. Events considered in production availability assessments
11.3.2. Overall description
11.3.3. Step 1: system analysis
11.3.4. Step 2: quantitative data selection
11.3.5. Step 3: production availability assessment
11.3.6. Step 4: synthesis
11.4. System analysis
11.4.1. Determination of system running modes
11.4.2. Item failure analysis
11.5. Quantitative data selection
11.5.1. Selection of reliability data
11.5.2. Collection of operational data
11.6. Production availability assessment
11.6.1. Building of production availability model
11.6.2. Production availability calculations
11.7. Synthesis
11.7.1 Main results
11.7.2. Additional economic parameters
11.7.3. Flared gas
11.7.4. Other results
11.7.5. Recommendations
11.8. Uncertainty on the reliability parameters
11.9. Validity of production availability assessments
12. Management of Production Availability and Reliability
12.1. Introduction
12.2. Principles of dependability management
12.2.1. Dependability property management
12.2.2. Phasing of the management
12.2.3. Lifecycle costing and dependability
12.3. Technical specifications
12.3.1. Contents
12.3.2. Reliability specification
12.3.3. Production availability specification
12.4. Reliability and production availability program
12.4.1. Contents
12.4.2. Reliability program
12.4.3. Production availability program
12.5. Validation of system reliability
12.5.1. Reliability data collection
12.5.2. Random failures
12.5.3. Common cause failures
12.6. Validation of production availability
12.6.1. Useful life
12.6.2. Reliability data
12.6.3. Production data
12.6.4. Use of production availability model
Appendices
Appendix 1: Notations and Abbreviations
Appendix 2: Markov Chain
Appendix 3: Comparison of Modeling Methods
Appendix 4: Solutions of Exercises
Bibliography
Index
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