![\"\"](\"https:\/\/reliabilityanalytics.com\/blog\/wp-content\/uploads\/2011\/08\/bathtub_curve1.png\" "\\"bathtub_curve\\"")
<\/a><\/p>\nIt has proven to be particularly appropriate for electronic equipment and systems. Note that it displays the three failure rate patterns, a decreasing failure rate (DFR), constant failure rate (CFR), and an increasing failure rate (IFR).<\/p>\n
Zone 1 is the infant mortality period is characterized by an initially high failure rate. This is normally the result of poor design, the use of substandard components, or lack of adequate controls in the manufacturing process. When these mistakes are not caught by quality control inspections, an early failure is likely to result. Early failures can be eliminated by a “burn in” period during which time the equipment is operated at stress levels closely approximating the intended actual operating conditions. The equipment is then released for actual use only when it has successfully passed through the “burn-in” period. A 48 hour “burn-in” is usually adequate to “cull out” a large proportion of the infant mortality failures.<\/p>\n
Zone 2, the useful life period, is characterized by an essentially constant failure rate. This is the period dominated by chance failures. Chance failures are those failures that result from strictly random or chance causes. They cannot be eliminated by either lengthy burn-in periods or good preventive maintenance practices. Equipment is designed to operate under certain conditions and up to certain stress levels. When these stress levels are exceeded due to random unforeseen or unknown events, a chance failure will occur. While reliability theory and practice is concerned.with all three types of failures its primary concern is with chance failures, since they occur during the useful life period of the equipment. The figure above is somewhat deceiving, since Zone 2 is usually of much greater length than Zones 1 or 3. The time when a chance failure will occur cannot be predicted; however, the likelihood or probability that one will occur during a given period of time within the useful life can be determined by analyzing the equipment design.\u00a0 If the probability of chance failure is too great, either design changes must be introduced or the operating environment made less severe.<\/p>\n
This CFR period is the basis for application of most reliability engineering design methods. Since it is constant, the exponential distribution of time to failure is applicable and is the basis for the design and prediction procedures spelled out in documents such as MIL-HDBK-217, “Reliability Prediction of Electronic Equipment.”<\/p>\n
The simplicity of the approach utilizing the exponential distribution makes it extremely attractive. Fortunately, it is widely applicable for complex equipments and systems. If complex equipment consists of many components, each having a different mean life and variance which are randomly distributed, then the system malfunction rate becomes essentially constant as failed parts are replaced. Thus, even though the failures might be wearout failures, the mixed population causes them to occur at random time intervals with a constant failure rate and exponential behavior. The figure below indicates this concept for a population of incandescent lamps in a factory. This has been verified for many equipments from electronic systems to bus-motor overhaul rates.<\/p>\n
Zone 3, the wearout period, is characterized by an increasing failure rate as a result of equipment deterioration due to age or use. For example: mechanical components such as transmission bearings will eventually wear out and fail, regardless of how well they are made. Early failures can be postponed and the useful life of equipment extended by good design and maintenance practices. The only way to prevent failure due to wearout is to replace or repair the deteriorating component before it fails. Since modern electronic equipment is almost completely composed of semiconductor devices which really have no short-term wearout mechanism, except for perhaps electromigration, one might question whether predominantly electronic equipment will even reach Zone 3 of the bathtub curve. Different statistical distributions can be used to characterize each zone. For example, the infant mortality period might be represented by Gamma or Weibull, the useful life period by the exponential, and the wearout period by gamma or normal distributions<\/p>\n <\/p>\n References:<\/p>\n 1. MIL-HDBK-338, Electronic Reliability Design Handbook<\/a>, 15 Oct 84 Figure 1 shows a typical time versus failure rate curve for equipment. This is the well known “bathtub curve,” which, over the years, has become widely accepted by the reliability community. It has proven to be particularly appropriate for electronic … Continue reading <\/a><\/p>\n
\n2. Bazovsky, Igor, Reliability Theory and Practice<\/a>
\n3. O\u2019Connor, Patrick, D. T., Practical Reliability Engineering<\/a>
\n4. Birolini, Alessandro, Reliability Engineering: Theory and Practice<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"