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As a mean life or mean time between failure, MTBF. As a probability of survival for a specified period of time, t. As a probability of success, independent of time. As a failure rate over a specified period of time.
Train plant employees. Use high-quality lubricants. Invest in equipment redundancy. Conduct consistent cleaning and maintenance.
Reliability is an attribute of any computer-related component (software, or hardware, or a network, for example) that consistently performs according to its specifications. It has long been considered one of three related attributes that must be considered when making, buying, or using a computer product or component.
You can increase the validity of an experiment by controlling more variables, improving measurement technique, increasing randomization to reduce sample bias, blinding the experiment, and adding control or placebo groups.
Instead, we can measure reliability as a combination of two important measurements: Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR). Mean Time Between Failures (MTBF) is the measurement of time between system breakdowns, but it only includes the time the system is working (and not being worked on).
If failure of any component does not depend on any other component, the reliability of the system is obtained simply as the product of the reliabilities of individual elements, R=R1×R2×R3×
Product Metrics. Product metrics are those which are used to build the artifacts, i.e., requirement specification documents, system design documents, etc. Project Management Metrics. Process Metrics. Fault and Failure Metrics.
Reliability (R) is the measure of the amount of the total variance attributable to true differences and can be expressed as the ratio of true score variance (T) to total variance or: R = T/T + E. This ratio gives a value known as a reliability coefficient.
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