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  2. Product lifetime - Wikipedia

    en.wikipedia.org/wiki/Product_lifetime

    Product lifetimes can be modelled using extant data from surveys with the application of probability and other statistical concepts (e.g. distributions). [12] [22] One of the earliest attempts to estimate product lifetimes was undertaken by Pennock and Jaeger [23] who utilised actuarial methods to measure the Service life of household goods for ...

  3. Failure modes, effects, and diagnostic analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_Modes,_Effects...

    Given a component database calibrated with field failure data that is reasonably accurate, [1] the method can predict device level failure rate per failure mode, useful life, automatic diagnostic effectiveness, and latent fault test effectiveness for a given application.

  4. Failure rate - Wikipedia

    en.wikipedia.org/wiki/Failure_rate

    Government and commercial failure rate data Handbooks of failure rate data for various components are available from government and commercial sources. MIL-HDBK-217F, Reliability Prediction of Electronic Equipment, is a military standard that provides failure rate data for many military electronic components. Several failure rate data sources ...

  5. Worst-case circuit analysis - Wikipedia

    en.wikipedia.org/wiki/Worst-case_circuit_analysis

    The circuit's EVA and RSS results are determined for beginning-of-life and end-of-life states. These results are used to calculate part stresses and are applied to other analysis. In order for the WCCA to be useful throughout the product’s life cycle, it is extremely important that the analysis be documented in a clear and concise format.

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites . The datasets are ported on open data portals .

  7. Prognostics - Wikipedia

    en.wikipedia.org/wiki/Prognostics

    Data-driven prognostics usually use pattern recognition and machine learning techniques to detect changes in system states. [3] The classical data-driven methods for nonlinear system prediction include the use of stochastic models such as the autoregressive (AR) model, the threshold AR model, the bilinear model, the projection pursuit, the multivariate adaptive regression splines, and the ...

  8. Engineering statistics - Wikipedia

    en.wikipedia.org/wiki/Engineering_statistics

    Engineering statistics involves data concerning manufacturing processes such as: component dimensions, tolerances, type of material, and fabrication process control. There are many methods used in engineering analysis and they are often displayed as histograms to give a visual of the data as opposed to being just numerical.

  9. High-temperature operating life - Wikipedia

    en.wikipedia.org/.../High-temperature_operating_life

    High-temperature operating life (HTOL) is a reliability test applied to integrated circuits (ICs) to determine their intrinsic reliability. This test stresses the IC at an elevated temperature, high voltage and dynamic operation for a predefined period of time. The IC is usually monitored under stress and tested at intermediate intervals.