Reliability Engineering: A Five Day Intensive Training Course

 


COURSE INSTRUCTORS

V. Narayan BMech, DipEE, DIM and Kenneth Lees BSc, MSc (Click on name to View Profile)


COURSE OUTLINE

The reliability of a Plant or Facility determines its performance - process safety, environmental and cost performance all depend on it.  It is thus a pivotal driver, which we can use to make significant business gains. Unfortunately it is often seen as a black art, best left to mathematicians or other specialists.

This practical training course will show you that reliability is easy to understand and explains how to use data from operating and maintenance records to improve performance.

Learning Outcomes

The links between Maintenance and Reliability, and the effect of Reliability on Process & Environmental Safety, Production Volumes and Maintenance Costs will be clearly explained in this highly interactive training seminar.

DAY ONE

Session One - Reliability Engineering Concepts

 Terminology and definitions
 Probability and Likelihood of Failure
 Understanding basic statistical concepts: Mean, Median, Mode, Standard Deviation, Normal Distribution
 Failure Histograms
 Failure distributions; simple analyses
 Probability Density Function, Hazard Rates
 Metrics - MTTF, MTBF, MTTR
 Relationship between Reliability, Availability & Maintainability
 The Bathtub Curve
 How to use reliability information for maintenance

Session Two - Reliability Engineering Applications

 Tools overview; RBDs, Reliability Modelling, FTA / ETA, FMECA, RCM, RBI, RCA
 Computing value added, performance metrics
 Making a Business Case

Session Three - Human Error & Reliability

 People, Process and Plant; Reliability Tripod
 Human Error major contributor to unreliability
 Understanding Human Error
 Physiological & Psychological Stress
 Rule, Skill and Knowledge based errors
 Error prone situations
 Managing Error

DAY TWO

Session One - Degradation Mechanisms

 Wear, Corrosion, Fatigue, Creep, Erosion ......
 Physical process - tyres & potholes, crack propagation
 What do we understand by the term Maintenance?
 Failure Patterns
 Age-related and non age-related failures
 Managing Degradation  - Appropriate Tasks

Session Two - Risk Management

 What is Risk?
 Quantitative Risk
 ALARP and Residual Risk
 Qualitative Risk
 Decision Making
 Selling ideas

Session Three - 
Introduction to Reliability Centred Maintenance (RCM)

 Maintenance in context (includes video presentation)
 Why RCM is different
 The seven RCM questions
 The Operating Context
 Failure Mode and Effect Analysis
 Simple RCM Exercise - Kettle
 Where to use RCM
 RCM in Oil & Gas and Process Industry

Session Four - Introduction to Risk Based Inspection (RBI)

 Corrosion Circuits
 Corrosion Rates; Design & Actual
 Probability of failure, Susceptibility to failure
 Consequences; HSE, Production loss, Asset damage
 Process steps, Criticality, Confidence Rating, Inspection
 Interval factor, Remnant life, Next Inspection Interval
 Non Age-Related failures
 Strategy based tasks
 Where to use RBI

Session Five - Introduction to Instrumented Protective Functions (IPF)

  Layers of Protection
  IPF vs. Process Control
  Cause-Consequence charts
  Process Demand Categories
  Consequences; HSE, Production loss, Asset damage
  Safety Integrity Levels
  Implementation
  Spurious Trips/Alarms; Safe Failures
  Testing, Coverage Factor and Maintenance
  Where to use IPF

DAY THREE

Session One Introduction to Risk Based Inspection (RBI)

 Corrosion Circuits
 Corrosion Rates; Design & Actual
 Probability of failure, Susceptibility to failure
 Consequences; HSE, Production loss, Asset damage
 Process steps, Criticality, Confidence Rating, Inspection
 Interval factor, Remnant life, Next Inspection Interval
 Non Age-Related failures
 Strategy based tasks
 Where to use RBI

Session Two - Introduction to Failure Mode, effects and Criticality Analysis (FMECA)

 Failure Mode and Effect Analysis
 Probability and its ranking
 Detectability of Failure and its ranking
 Consequence and its ranking
 Risk Priority Number - Criticality
 Where to use FMECA

Session Three - Introduction to Fault Tree and Event Tree Analysis (FTA / ETA)

 Terminology, Symbols, and Notation
 Logic Diagrams
 Assigning probabilities
 Incorporating Human Error
 Where to use FTA, ETA

Session Four - Introduction to Reliability Block Diagrams (RBDs) and Reliability Modelling

 System Reliability
 Series RBDs
 Parallel RBDs
 Complex RBDs, Nested RBDs
 Bridge RBDs
 System Analysis
 System Analysis and Modeling
 Analytical and Simulation Models

DAY FOUR

Session One - Exercises

 Histogram plotting
 Normalizing Histograms
 Probability Density Function, Computing F(t), R(t), z(t)

Session Two - Exercises - Simple Weibull Charts

 Arranging the data set
 Distribution of rank order, Benard's approximation
 Median ranks
 Plotting the data points, best-fit line
 Outputs: Shape and scale factors, B10, B1, B .1,B .01
 Computing the pdf chart values
 Forecasting failures
 Weibull Video

Session Three - Exercises - Reliability Block Diagrams

 Series RBD example
 Parallel RBD example
 Bridge RBD example
 Laboratory Ovens
 Nested RBDs

Session Four - Exercises - More Complex Weibull charts

 Suspended data points
 Censoring, Effect on ranks
 The effect of preventive maintenance
 Applying Benards approximation to get median ranks
 Plotting Weibull chart points
 Plotting the data points, best-fit line

Session Five - Data Sources

 Run length data; run meters, DCS, operating logs
 CMMS; failure data, history text
 Operators and Maintainers as sources
 Publicly available sources, OREDA, IEEE
 Errors in data sources, Independent & Identical conditions

DAY FIVE

Session One - Implementation of Reliability Improvements

When & Where to Apply - Selection of Projects
 Preparing the Ground
 Knowledge of Current performance
 Identify Critical Systems
 Identify Poor Performers
 Set Objectives
 Sponsor, Terms of Reference, Budget

Session Two - Managing Change

 Change is a process
 Models
 Bereavement Curve
 Reliability Improvement requires Change
 Socratic Method
 Communication Plan
 Need for openness
 Check data quality

Session Three - Analysis and Measurement

 Select the right tools, software
 Use the same metrics before and after study
 Follow the evidence, don't 'bend' the data!
 Apply corrections/confidence limits if data quality is suspect
 Publish ALL results, good or bad
 Communicate to Stakeholders

Session Four - SWOT the Solutions, Track Results and Review Learning

Every solution is a potential problem
 Evaluate downsides
 Plan mitigation
 Check metrics and report KPIs
 Share results and credit contributions
 Report, Present Results
Test results
 Recap
 Q & A


Tuition and Fees

 

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