Reliability Evaluation and Demonstration

Holders: Prof. Klemenc Jernej, Prof. Nagode Marko

Subject description

  1. Lecture: Databases for analysis of product’s failures: Internal data sources; External data sources; Input-data quality and its influence to the product-failure analysis.
  2. Lecture: Modelling the bathtub curve with a weighted mixture of two-parametric Weibull’s probability density functions: Early-failures model; Constant hazard-rate model; Aging-failures model.
  3. Lecture: Temporal development of a product’s availability with- and without considering the maintainability process: Basics of a Markov-chain analysis; Operational states of composed products; Derivation of differential equations of system states with- and without considering the maintainability intensity.
  4. Lecture: Predicting the built-in probability of the system functioning: Static reliability model; Connecting the statistical approach for reliability prediction with finite-elements numerical simulations; Case study for a Weibull’s reliability model.
  5. Lecture: Introduction to design of experiments and data processing for validating the products and their components: Experimental plan as a consequence of the product’s requirements; Influential factors and a full factorial experiment; Limited plan of experiments; Data processing for full-factorial and limited-plan experiments.
  6. Lecture: Introduction to design of experiment and data processing for reliability evaluation: Functional data modelling; Empirical data modelling; Connecting influential factors and product durability with artificial-intelligence methods.
  7. Lecture: Burn-in testing: Conditional reliability as a customer’s perspective; Estimating the burn-in testing period on the basis of technical and economic criteria; Case study.
  8. Lecture: Acceptance testing: Binomial experiment; Risk for type I and type II errors; Estimating the sample size with a regard to the requested reliability objectives using a real case situation.
  9. Lecture: Accelerated testing for validation of simple and complex products by increasing the number of test samples: Experiment with- or without substitution of failed samples; Expected testing time for a given sample size; Acceleration factor as a function of the sample-set size.
  10. Lecture: Accelerated testing for validation of simple and complex products by increasing the loading frequency: Limits for increasing the loading frequency for simple and complex products; Transformation of time domains for environmental and laboratory testing; Acceleration factor as a function of the loading frequency.
  11. Lecture: Accelerated testing for validation of simple and complex products by increasing the loading levels: Accelerated test with the increased loading level; Inverse power-law model; Arrhenius model; Eyring model; Acceleration factor as a function of the increased loading level.
  12. Lecture: Accelerated testing for validation of simple and complex products by increasing the loading levels: Step-stress accelerated testing; Reliability estimation from the step-stress testing at known data trend; Estimating the confidence interval with Weibull’s analysis; Case study.
  13. Lecture: Demonstration of meeting the requirement in R&D process: Reliability growth as a consequence of repeating PDCA cycles; Ideal reliability-growth model; Duane’s reliability-growth model.
  14. Lecture: Demonstration of meeting the requirement in R&D process: Experimental proof of reliability growth with Weibull’s analysis; Saturation method with a graphical visualisation; Case study.
  15. Lecture: reliability of mechatronic systems: Software as a building block of product; Software reliability testing.

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