Risk Analysis & Reliability Engineering – 3 Days
- Online course on risk and reliability engineering applications.
- Identify, analyze, and apply risk and reliability engineering concepts.
- Assess data interpretation methods for risk analysis.
- Select techniques for qualitative and quantitative risk assessment.
- Evaluate failure distributions and develop risk mitigation solutions.
Overview
The Online Risk and Reliability Training is a 3-day course covering theoretical and practical applications of risk and reliability engineering. Participants will learn about concepts such as reliability, availability, and maintainability analysis, as well as quantitative risk analysis and Monte Carlo simulations. The course aims to equip mechanical, process, and energy engineers with the knowledge and skills needed to analyze and mitigate risks in engineering projects. Topics include basic statistics, accelerated life testing, risk analysis, Monte Carlo simulation, and reliability assessment techniques.
Who should attend
Mechanical, Process, Energy Engineers
About The Course
The course duration is 3 days and will consist of both theoretical and practical applications of risk and reliability engineering. The course will introduce the fundamentals of Risk analysis and reliability engineering. Reliability, availability and maintainability (RAM) Analysis will be dealt with. Quantity riskanalysis, basic statistics, distribution of failure, reliability of failure, consequences of failure and monte-carlo simulations (MCS).
On successful completion of this course, you will be able to: 1) identify and analyse the concepts and principals of risk and reliability engineering and their potential applications to different engineering problems. 2) Assess and analyse appropriate approaches to the collection and interpretation of data in the application of risk and reliability engineering methods. 3) Evaluate and select appropriate techniques and tools for qualitative and quantitative risk analysis and reliability assessment. 4) Analyse and evaluate failure distributions, failure likelihood and potential consequences and develop solutions for control/mitigation of risks.
Who Should Attend?
This training is suitable for mechanical, process, energy engineers and professionals that want to obtain knowledge on applied aspects of risk and reliability engineering.
Day 1
PROGRAMME
07.00 – 08.30 Lecture 1: Basic Statistics
Prof Purnendu Das
08.30 – 08.45 Break
08.45 – 10.15 Lecture 2: Basic Probability
Prof Purnendu Das
10.15 – 10.30 Break
10.30 – 12.00 Lecture 3: Accelerated life
testing & Analysis of Life Data
Dr. T. V Santhosh
12.00 – 12.30 Break
12.30 – 14.00 Lecture 4: RCM Analysis
Dr. T. V Santhosh
Day 2
07.00 – 08.30 Lecture 5: Introduction to Risk
Analysis
Prof Edoardo Patelli
08.30 – 08.45 Break
08.45 – 10.15 Lecture 6: Introduction to Monte
Carlo simulation method
Prof Edoardo Patelli
10.15 – 10.30 Break
10.30 – 12.00 Lecture 7: Quantitative Risk
Assessment: FMEA, FMECA, and HAZOP
Prof Edoardo Patelli and Dr
T.V Santhosh
12.00 – 12.30 Break
12.30 – 14.00 Lecture 8: Event Tree and Fault
Tree Human reliability techniques
Dr T.V Santhosh
Day 3
07.00 – 08.30 Lecture 9: Efficient Monte Carlo Simulation methods
Prof Edoardo Patelli
08.30 – 08.45 Break
08.45 – 10.15 Lecture 10: Reliability analysis
and Uncertainty quantification with COSSAN Software
Prof Edoardo Patelli
10.15 – 10.30 Break
10.30 – 12.00 Lecture 11: Reliability &
Maintainability and Reliability testing
Dr T.V Santhosh
12.00 – 12.30 Break
12.30 – 14.00 Lecture 12: System Reliability
Techniques
Prof Edoardo Patelli and Dr T.V Santhosh
Lecture Content
Lecture 1
Introduction to statistics and basic statistical terms (e.g. correlation, covariance,etc.)
Lecture 2
Introduction to Probability with a focus on understanding and being apple to apply basic concepts (e.g. mean, variance, etc.)
Lecture 3
Objectives of life tests Types of tests
Qualitative and quantitative accelerated life testing
Acceleration factor Selection of life distributions Life-stress models
Case study
Lecture 4
Concepts of maintenance Principles of RCM Categories of RCM RCM program
Case study
Lecture 5
Introduction to Risk Analysis
Basic concept of Safety and Risk Analysis. Definition of Reliability and Availability and Resilience
Qualitative and Quantitative Risk Assessment
Lecture 6
Basics of simulation, Monte Carlo simulation
Advantages and limitation of Monte Carlo methods
Lecture 7
Quantitative Risk Assessment: FMEA, FMECA and HAZOP.
Introduction to the Failure mode, effects, and criticality analysis (FMECA) Hazard and operability study analysis (HAZOP)
Lecture 8
Definitions, Fault tree and Event tree modelling, Basic component data models, Risk quantification, Importance measures, Common cause failures, Human reliability modelling
Industrial case study
Lecture 9
Advanced Monte Carlo methods for reliability analysis Important sampling, Line Sampling and Subset Simulation.
Lecture 10
Demonstrations by reliability software COSSAN Software Models and their capabilities
Lecture 11
(RAM) Introduction to maintenance strategies and reliability-based maintenance.
MTTF calculations, Time & Failure terminated reliability testing, Confidence level.
Lecture 12
Reliability block diagram, Reliability bounds method, Redundancy techniques, Electronic reliability, Software reliability, Survival signature and load-flow approach, Resilience modelling
Course Duration: 3 Days
Cost:£995 + Vat
