reliability engineering

Failure rates, in the simplest form, are S(time in use)/S(number of failures) or the reciprocal of mean times to/between failure.

A measure of use duration applicable to an item. For example, the life units may be starts-stops, run hours, hot-cold cycles, distances traveled, emergency starts or starts, shelf life, and other measurements which motivate failures.

A series of screens are conducted under environmental stresses to disclose weak parts and workmanship defects which require corrections and this requires and understanding of burn-in testing and ESS of which both techniques identify weak points and eliminate them by motivating early failures. Burn-in is usually a long process of operating under load(s) and at fixed temperature (in short, this is a special case of ESS) or it can be operated at varying loads and accelerated temperatures to achieve a shorter burin-in period, whereas ESS is a scientifically planned and conducted test which is usually conducted under accelerated loads to produce the same test/use results in a shorter period of time by increasing the stress on the components or assemblies. The objective of these screens is to produce a failure free product when released into operations. ESS is not intended as a test to validate compliance to a design, however it is intended to force latent defects into becoming defects before the end user finds them in day-to-day usage.

Vilfredo Pareto, and Italian economist in the late 1800s, who described the unequal distribution of wealth in the world.

Failure is the loss of function when you needed the function to occur.

Data is the informational energy which runs the reliability improvement machine. Data is acquired at great cost. Data needs to be retained and used to prevent future failure events. Proper use of data provides an understanding of failure mechanisms and prevents reoccurrence of bad events which cause safety or high cost failures to occur. Reliability data requires definition of a failure. Failures can be catastrophic failures or slow degradation-you decide by defining the failures. The units of the measure for the data must be in units of the degradation-sometimes it is hours, some times it is miles, and so forth-in short, what ever motivates the failure. Reliability always ceases with a failure or a removal from service in some aged condition which then generates a category of data called a suspension or censored data. Data is information in the form of facts, figures, or engineering databases which is obtained from engineering tests, experiments, or actual operating conditions. Reliability data is often incomplete as the exact times to failure are rarely known or recorded with much precision so that only partial information is available for analysis. Reliability data comes in two forms: 1) age-to-failure data, and 2) censored/suspended data such as occurs when unfailed items are removed from service or when they fail due to a different failure mode than we are studying-this is useful information and part of the data set. Some data is better than no data for resolving reliability issues.

Quality Function Deployment or QFD is a bad translation of a good reliability technique for getting the voice of the customer into the design process so the product delivered is the product the customer desires.

Total productive maintenance (TPM) is a corporate-wide effort involving all employees to fully use equipment to the maximum limit employing an equipment-oriented management concept to reduce failures and increase utilization of equipment and processes in a productive manner. TPM programs are teamwork programs and require a corporate culture of teamwork devoid of us vs. them issues. All employees are expected to accept ownership of the equipment and processes to do many small things all the time to insure high levels of availability by eliminating failures in the early stages with low cost actions. The employees approach the process equipment as owners rather than renters.

Poisson distributions are discrete distributions and the simplest statistic process where Poisson events are random in time which describes a stable average rate of occurrence of counted events.

Failure reporting and corrective action systems (FRACAS) is an organized database for aiding in solving reliability problems using a common sense approach by systematically and permanently removing failure mechanism.

A density figure-of-merit metric often referred to as the average or expected value. In the simplest form it appears as arithmetic S(time)/S(events) or in complicated situations as a statistic metric. It applies to mean life (ML), mean down time (MDT), mean maintenance time (MMT), mean time between failures (MTBF for repairable items), mean time to failures (MTTF for replacement items), mean time between maintenance (MTBM), mean time between maintenance scheduled (MTBMs), mean maintenance time unscheduled (MMTu), mean maintenance time scheduled (MMTs), mean time between overhauls (MTBO), mean time between unscheduled removals(MTBRu), mean time to restore (MTR), mean time between downing events (MTBDE), and so forth. The units will be time/metric, e.g., hours/failure. The reciprocal of the metric provides an incident rate, e.g., failures/hour.