CPD courses Computational Mechanics and Reliability Group

Design for Engineering Reliability

Tutor: Stoyan Stoyanov
Duration: 8 hours


Engineering reliability is a term used to characterise the ability of a product or process to function properly for a certain period of time under stated conditions and the chance of a failure. Numerical methodologies are now enabling designers to predict the reliability (i.e. how long will a product last) using failure data or by adopting physics of failure modelling and simulation approach. Understanding the reliability of a product over time is a key factor in mitigating the risk of building products that have a high probability of failure in the field. Nowadays, reliability prediction theory is used in all industrial sectors to characterise the performance and maintainability of various engineering designs.

Course aims

  • Provide an introduction to the principles of failure analysis and reliability engineering
  • Introduce the concepts behind the common causes for failure such as overstress, variation, wear-out, etc. Introduce failure models associated with fatigue, fracture, etc.
  • Introduce the statistical theory behind reliability prediction tools.
  • Introduce data analysis techniques for assessing distributions of failures over time and make reliability predictions
  • Provide details on the concepts behind risk analysis and Six-Sigma in design.
  • Demonstrate how design for reliability can be realised through modelling (or experiment) and probabilistic optimisation techniques.

Indicative content

The following topics will be covered:

  • Fundamentals of reliability engineering and risk assessment.
  • Typical causes for failure in engineering products.
  • The role of designers in failure prevention.
  • Why statistics and probability is used in reliability assessment.
  • Failure modes and mechanisms. Examples of failure models.
  • Weibull analysis and failure statistics.
  • Reliability prediction techniques. Historical data based and physics-of-failure reliability prediction approaches. reliability standards (such as MIL-STD-785, IEEE 1332, IEEE STD-1413.1, MIL-HDBK-217F2).
  • Design of experiments approach for developing reliability models.
  • Design for reliability problems as design optimisation tasks.
  • Robust design, Six-Sigma and zero-defect manufacturing concepts.
  • Monte Carlo simulations for variation analysis and risk assessment.

Computational Mechanics and Reliability Group is part of the Faculty of Liberal Arts and Sciences, University of Greenwich.