Reliable Quantity Pdf For Free

HANDOUT ON RELIABILITY A test is said to be reliable if it yields similar results in repeated administrations when the attribute being measured is believed not to have changed in the interval between measurements, even though the test may be administered by different people and alternative forms of the test are used.

Reliability is complementary to probability of failure, i.e. R(t) = 1 ?F(t) , orR(t) = 1 ??[1 ?Rj(t)] . For example, if two components are arranged in parallel, each with reliability R 1 = R 2 = 0.9, that is, F 1 = F 2 = 0.1, the resultant probability of failure is F = 0.1 × 0.1 = 0.01.

To perform a reliability prediction, you begin by listing all the components in your system design. You then compute the estimated failure rates of your components using the equations from the standard you choose to use. The summation of all the components' failure rates is the predicted failure rate of your system.

Reliability is typically defined by a metric known as mean time between failure (MTBF) expressed in minutes, hours, or days; in contrast, availability is represented by a percentage such as 99.9%. Measuring availability to define the state of a simple website is sufficient and commonplace.

Once you know the failure rate of each component part of an asset, you can use that to calculate the overall reliability of the entire system. The formula looks like this: R = (1-F1) * (1-F2) * (1-F3) * (1-F4) ? R refers to the overall reliability of the system, or asset.

Reliability is the probability of a product successfully functioning as expected for a specific duration within a specified environment. Figure 1 shows the four key elements to reliability: function, probability of success, duration and environment.

MTBF is a basic measure of an asset's reliability. It is calculated by dividing the total operating time of the asset by the number of failures over a given period of time. Taking the example of the AHU above, the calculation to determine MTBF is: 3,600 hours divided by 12 failures. The result is 300 operating hours.