MSc Reliability Engineering and Asset Management / Course details

Analysing the reliability of plant items: Within the context of Industry 4.0: Setting the scene: needs, definitions, and statistics of item failure. Decision analysis: identifying reliability problems using Pareto and trend analysis. Weibull analysis: graphical analysis of item life data, method of Median Ranks, the Cumulative Hazard plot.  

Assessing the reliability of plant systems: Reliability Block Diagrams  (RDBs): representation and assessment of the reliability of simple configurations. Assessment of larger, more complex and proof-tested systems, via System Reduction, Truth Table and Bayesian Techniques. Maintainability analysis. Estimating system repair times.

Advanced reliability and safety assessment: Fault Tree Analysis: (a) symbols and construction, (b) minimum cut sets, (c) top event quantification, (d) importance measures. Event Tree Analysis.  Simulation.  Case studies of applications in design for industrial safety.  

Human Reliability Assessment (HRA): Overview of Human Factors and methods of Assessment: (a) Alternative methods for HRA, (b) Human Error Assessment and Reduction Technique (HEART), (c) HEART Case studies of applications in industrial safety and production performance. 

This unit aims to equip the student with:

•    a working knowledge of the analytical techniques of reliability engineering;

•    an appreciation of the contribution that these techniques can make to the task of enhancing (a) the effectiveness of the maintenance function and (b) the availability, maintainability and, where relevant, the safety of the physical assets involved;

•    an understanding of the information that will be needed if such benefits are to be realised.

Analysing the reliability of plant items: Within the context of Industry 4.0: Setting the scene: needs, definitions, and statistics of item failure. Decision analysis: identifying reliability problems using Pareto and trend analysis. Weibull analysis: graphical analysis of item life data, method of Median Ranks, the Cumulative Hazard plot.  

Assessing the reliability of plant systems: Reliability Block Diagrams  (RDBs): representation and assessment of the reliability of simple configurations. Assessment of larger, more complex and proof-tested systems, via System Reduction, Truth Table and Bayesian Techniques. Maintainability analysis. Estimating system repair times.

Advanced reliability and safety assessment: Fault Tree Analysis: (a) symbols and construction, (b) minimum cut sets, (c) top event quantification, (d) importance measures. Event Tree Analysis.  Simulation.  Case studies of applications in design for industrial safety.  

Human Reliability Assessment (HRA): Overview of Human Factors and methods of Assessment: (a) Alternative methods for HRA, (b) Human Error Assessment and Reduction Technique (HEART), (c) HEART Case studies of applications in industrial safety and production performance.

The course is delivered as 5-full days of teaching on campus and subsequent discussion through the online Blackboard system.

• Explain / describe the fundamental concepts and techniques of reliability engineering and how they can be applied to improving the reliability, availability, maintainability and safety of engineering plant and systems.
• Identify the data needed in order to apply the analyses practiced during the course.
• Fully explain / describe  the various reliability-based approaches to the formulation of maintenance strategy.
• Fully explain / describe  the implications of decision making in relation to reliability, maintainability and risk based approaches and the potential consequences of system failure. 
• Explain / describe  how big data and the internet of things will better enable subsequent technical risk analysis. 
   

• Analyse statistical data on the lifetimes of engineering items in order to aid the diagnosis of the causes of their failure. Select and apply, for the purposes of system reliability assessment, the most appropriate of the available techniques.
• Analyse the internal reliability dependencies of an engineered system in order to assess its overall availability and to identify the reliability-critical or safety-critical areas of the system or of its operation.
• Explain / describe how RAM (Reliability, Availability and Maintainability) link with the broader context of operations and maintenance management. 
   

• Organise the collection of plant reliability and availability data and undertake an analysis of it which will facilitate the identification and diagnosis of reliability problems, and hence their cost-effective elimination or mitigation. Take cost-effective steps to improve the overall availability of operating equipment and plant. Design and modify plant for improved maintainability.
• Select a major accident (from the Module library) and consider how principle risk assessment methods could have been applied to avoid the pending tragedy.
• Explain / describe the benefits and limitations of industry leading reliability software.

• Convey important reliability, maintainability and risk concepts in terms of their application strengths and limitations.
• Contribute to group exercise addressing the application of risk assessment methods applied to a complex system in a high risk industry.
• Manage the creation and revision of assignment material and reliability models.
• Research supporting journal papers, reference text books and online case studies.

Provided in person or via the Blackboard system.

1. Davidson J and Hunsley C (Eds.),  The Reliability of Mechanical Systems, 2nd Ed., Mechanical Engineering Publications, IMechE, London 1994
2. O'Connor  P D T, Practical Reliability Engineering (3rd Ed), Wiley 1991
3. Andrews J D and Moss T R, Reliability and Risk Assessment, Professional Engineering Publishing (PEP) 1993
4. T.R.Moss,The Reliability Data Handbook, Professional Engineering Publishing (PEP),  London 2005