Risk and Reliability Engineering
This course provides the basic knowledge and tools to determine the risk and reliability of equipment, a process and a system. It is designed to be 50% theoretical and 50% practical.

Agenda
Day 1
 Introduction
 Basic Concepts
 Risk
 Risk Analysis
 Reliability
 Reliability Engineering
 Uncertainty – Uncertainty Management
 Asset Life Cycle Economic Analysis
 Deterministic Model
 Probabilistic Model
 RiskBased Life Cycle Economic Analysis
 An Integrated Approach to Optimize the Economy of the Asset Life Cycle”
 Concept, Applications and Benefits
 Integrated Reliability Toolkit
 Disciplines
 Methodologies
Day 2
 Statistics for Risk and Reliability Analysis
 Basic Terms (Probability, Population, Sample, Descriptive Statistics, Random Variable)
 Descriptive Statistics
 Sample Statistics
 Histograms •
 Statistics (Sample Mean, Sample Mode, Sample Standard Deviation, Percentiles)
 Using Excel™ for sample statistics
 Population Statistics
 Probability Distribution Models
 Probability Distribution Formats (pdf, CDF, Inverse CDF)
 Statistics of probability distributions (Mean, Mode, Median,
 Probabilistic characterization of a sample or How to select a probability distribution model for a given sample.
 Goodness of fit Tests
 Use of software for goodness of fit tests. Statistics for Risk and Reliability Analysis
 Solving mathematical models (equations) random variable input parameters
 Sampling from a random variable
 Monte Carlo Simulation
 Using Excel™ for Monte Carlo Simulation
 Probabilistic Dependence
 Correlated Random Variables – Correlation Factor
 How to consider probabilistic dependence in Monte Carlo Simulation
Day 3
 Principles of Production Processes Reliability Analyisis
 Reliability, Availability and Maintainability (RAM)
 Analysis for Repairable Items
 Samples Data for RAM Analysis of repairable items
 UpTime Data (Failure Data and Censored Data)
 Down Time Data
 Probability Distribution for Up Time Samples in Repairable Items
 Probability Distribution for DownTime Samples in Repairable Items
 Methodology for Availability and Expected Number of Failures calculations for Repairable items
 Availability and Expected Number of Failures Calculations
 Sources of Data for Reliability Analysis
 Evidence, Expert Opinion, Generic Data • Combining different sources of data
 Bayes Theorem
 Combining Generic Data with Evidence
 Combining Expert Opinion with Evidence
 System Availability and Expected Number of Failures Calculations
 Forecasting failures and availability of a pumping system
 Forecasting failures and availability in an ESP Oil Well
Day 4
 Principles of Financial Analysis
 Basics Terms and Definitions
 Life time of an investment , Projected Cash Flow, Discount Rate
 Financial Indicators • Net Present Value (Deterministic Model, Probabilistic Model)
 Annualized Present Value (Deterministic Model, Probabilistic Model)
 Principles of Risk Analysis
 Basic Terms and Definition
 Undesired Events
 Basic Model
 Qualitative and SemiQuantitative Methods for Risk Analysis
 Quantitative Risk Analysis (QRA)
 An ESP Oil Well QRA Example
Day 5
 Risk Based Asset Economic Life Cycle Analysis
 General Model
 Monte Carlo calculation of NPV
 Sensitivity Analysis of Probabilistic NPV
 Determining the Risk Mitigation Actions Portfolio
 Comparing Investments Options – Risk / Profitability Matrix
 Final Exercise: Life Cycle Economic Analysis of an ESP Oil Well

Audience
Production engineers, Surface facilities Engineers, Reliability Engineers and Maintenance Engineers

Prerequisites