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Production Availability and Reliability : Use in the Oil and Gas Industry.

By: Material type: TextTextPublisher: Newark : John Wiley & Sons, Incorporated, 2018Copyright date: ©2018Edition: 1st edDescription: 1 online resource (358 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119522423
Subject(s): Genre/Form: Additional physical formats: Print version:: Production Availability and ReliabilityLOC classification:
  • TA169 .L476 2018
Online resources:
Contents:
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.
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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.

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