Failure Prediction

Failure Prediction

 

the determination of the probability of failure for an object during a given time period, based on test data.

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KT will continue to take steps to enhance tasks regarding network operations such as the analysis of root causes of network failure, failure prediction and network design, based on its Neuroflow.
This work was applied to machine tool operations, drone imaging and video capture, as well as jet engine failure prediction.
Although one can expect that the independent auditors or other decision-makers are able to make correct assessment of a company's financial conditions, but studies have shown that, in practice, the assessments by auditors and decision makers do not perform well as compared to failure prediction models in making classification of failed company (Altman and Saunders, 1998).
Digital Field Service: Showcases intelligent remote monitoring, failure prediction, over-the-air repair, and dynamic technician dispatch.
Parameter analysis on Brake master cylinder failure prediction
In the next section (Section 1) we present a review of the literature in terms of bankruptcy risk where the "failure" concept is presented, we present the importance given to financial rates in bankruptcy risk studies highlighting the main methods used in bankruptcy's risk analysis and Anally we emphasize the time and space limits of failure prediction models that exist in the literature.
As an innovative approach to further enhance system dependability and availability, failure prediction anticipates failures before occurring, and performs preventive strategies or reduces time-to-repair by preparation for imminent failures [8].
Since 2004, the range and resolution of commercial laser scanners have improved significantly, which offers an opportunity to improve the failure prediction in the SiteMonitor software.
2015, A potential stress indicator for failure prediction of laboratory-scale rock samples.
There are various financial failure prediction models in the related literature.
NASA will receive verification of its FAD methodology for failure prediction of structural brazed joints on real industrial applications.
Designed to support both conventional and emerging battery chemistries for automotive and industrial applications, the MM9Z1J638 battery sensor measures key battery parameters for monitoring state of health (SOH), state of charge (SOC) and state of function (SOF) for early failure prediction.
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