logo Insalogo Insa

Reliability and Lifetime analysis



Censored or truncated data,  instantaneous hazard rate, ageing models, parametric and nonparametric (Kaplan-Meier and Nelson-Aalen) estimation, models with covariates (regression models of Cox and of Aalen), bayesian approach.


System structure and Reliability:

reliability diagram, series system, parallel system, k/n or mixed system, structure function.


Reliability of repairable systems:

Reliability and Availability, Markov models, failure intensity process, homogenous and non homogeneous Poisson process models, renewal process, corrective and préventive maintenance, imperfect maintenance models, dégradation models and maintenance policy.


At the end of this module, the student will be able to drive the following process and to explain the obtained conclusions :

  • Using the Reliability database in order to estimate the functions of interest
  • Analyzing and exploiting the  structure of a system to derive its reliability from the characteristics of its components
  • Modeling the recursive occurrences of the failures on a system. Modeling the évolution of the system-state with time.
  • Modeling the effect of maintenance and its planning according to the observations made on the system (dégradation process in particular)

Needed prerequisite

  • Markov chains and applications (MIC3)
  • Inferential Statistics (I3MIMT41)
  • Statistical Modelling (I4MMMS71)
  • Poisson processes, applications in Insurance and Reliability (I4MMSP81)

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...