Course

Unit I

Concept and Definition of reliability (reliability mathematics)-Failure distributions, hazard models – exponential, Rayleigh, Weibull, Normal and Lognormal distributions -MTTF, MTBF. Reliability of systems – series and parallel configurations – Reliability improvement, redundancy, k-out-of-n system -Reliability of complex configurations- Reliability of three-state devices – Markov analysis-Physical reliability models – random stress and random strength

Unit II

Design for reliability-Reliability allocation, derating-Maintainability-Design for maintainability-Availability- Maintenance and space provisioning. Failure data analysis-Reliability Testing-Identifying failure distributions– parameter estimation.

Approaches to intelligent control- AI approach- Concept of artificial neural network and its model, fuzzy logic and its model- Case study

Course Objective

Provide the importance of reliability, the basic methods to evaluate product and system reliability

Course Outcomes

 CO-PO Mapping

 Skills Acquired

Ability to determine reliability of a system and to identify suitable testing methods for industrial applications

1. Charles Ebeling, “An introduction to Reliability and Maintainability Engineering”, Tata McGraw Hill,
2. Lewis E., “Introduction to Reliability Engineering”, Second Edition, John Wiley & Sons, 1995.
3. Rao S., “Reliability Based Design”, McGraw Hill, 1992.
4. Srinath S., “Mechanical Reliability”, East-West Press,2002.
5. Simon Haykins, “Neural network : A comprehensive foundation”, Pearson Edition, 2003
6. J. Ross, “Fuzzy logic with fuzzy application”,McGrawHill, 1997.