
Definition of Reliability
The concept of Reliability is often misused, misunderstood, and misinterpreted. Reliability in its academic root, is defined as the probability that a system will perform its intended function in a specified mission time and within specific process conditions. So, it is in essence a probability.
The ageing variable is crucial in calculating the reliability of a system. Reliability is the Probability of Success. And 1 minus the Probability of Failure. In the equation below , the ageing variable is time (t).
$$ \displaystyle \large R\left(t\right) = 1 – F\left(t\right) \:\:\:\: (where \: F = Failure \: Probability) $$
Reliability engineering is based on building data models to predict future system performance accurately. Based on past performance records. The model is more or less precise depending on how many past records we have. The more data, the more precise the model. At the end of the day, a well defined model, even with a little data, is better than no model. At least we can proceed in the right direction. That is, make the best possible decision for our assets.
This article looks at a non exhaustive list of models in the Reliability Engineering realm.
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