Reliability, Availability, and Maintainability in .NET

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System Production Phase System Production Phase System Operations & Support (O&S) Phase System Operations & Support (O&S) Phase 1 System Fielding System Disposal Phase System Disposal Phase 2 3 System Disposal Period of Stabilized Failure System/Component Failure Rate Remains Relatively Constant Period of Increasing Failure System/Component Failure Rate Increases Due to Effects of Aging & Maintenance 4
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Hazard Rate h(t)
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Period of Decreasing Failure Field Elimination of System/Component Defects Reduces Failure Rate
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Bathtub Paradigm
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Figure 50.2 Bathtub Curve Paradigm Equipment Failure Pro le
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tronic components lead to the formulation of the Bathtub Curve. Examples of these components included vacuum tube and early semiconductor technologies that exhibited high failure rates. Many subject matter experts (SMEs) question the validity of the Bathtub Curve in today s world. Due to the higher component reliabilities available today, most systems become obsolete and are replaced or disposed of long before their useful service life pro le reaches the Period of Increasing Failure. Most computers will last for many years or decades. Yet, newer technologies drive the need to upgrade or replace computers every 2 3 years. Smith [1992] observes that the Bathtub Curve may provide an appropriate pro le for a few components. However, the Bathtub Curve has been ASSUMED to be applicable to more components than is supported by actual eld data measurements. Large, statistically valid sample sizes are required to establish age-reliability characteristics of components. Often, large populations of data are dif cult to obtain due to their proprietary nature, assuming they exist. Nelson [1990] also notes that the Bathtub Curve only represents a small percentage of his experiences. Anecdotal evidence suggests that most reliability work in the US is based on the Period of Stabilized Failure, primarily due to the simplicity of dealing with the constant hazard rate from negative exponential distributions. Although any decreasing or increasing exponential distribution can be used to model the three failure rate regions, the Weibull distribution typically provides more exibility in accurately shaping the characteristic pro le. Based on these observations, the validity of the Bathtub Curve may better serve as an instructional tool for describing curve tting than as one size ts all paradigm for every type of electronic equipment. Low Rate and Mass Production Systems. The discussion of the decreasing failure period of the Bathtub Curve does provide some key insights, especially in terms of systems planned for production. Figure 50.3 might represent the initial failure rate period for a rst article system and set of OPERATING ENVIRONMENT conditions. For example, assume the instantaneous failure rate or hazard rate at POWER ON is f0, which represents the mean of a statistically valid sample of rst article systems. During the System Design Segment, f0 is strictly an analytical estimate.
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50.3 System Reliability
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Failure Rate ( )
Initial Failure Rate Mean for a Given System and OPERATING ENVIIRONMENT Conditions
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Decreasing Failure Period (DFP) Decreasing Failure Period (DFP)
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Figure 50.3 Electronic Equipment Failure Pro le
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Once we have a statistically valid sampling of rst article systems, we can validate the distribution with actual eld data. By correcting latent defects such as design errors and aws, component material defects, and workmanship process and method problems for a speci c serial number system, its failure rate should decrease thereby improving its reliability. The strategy is to posture the system design and manufacturing processes for a Low Rate Initial Production (LRIP) failure rate near f2, not f0. From an infant mortality perspective, Figure 50.3 also illustrates the effects of a diminishing failure rate resulting from a component burn-in. Based on this premise, some organizations establish a burn-in strategy to speci c components for a prescribed number of hours prior to assembly to reduce infant mortality.
System/Component Mortality
Traditionally, complex systems were viewed as having a failure rate that decreased with time based on the frequency distribution of initial failures. These failures were referred to as infant mortality due to weak components. Therefore, the Decreasing Failure Period (DFP) was viewed as a burnin period to eliminate these failures. If the failure rate diminishes initially during the defect elimination phase, why not subject the system/component to an operational burn-in period at the factory Some System Developer or Production organizations do this. They know that mission critical components must achieve a speci ed level of reliability and perform a burn-in. Some organizations driven by pro tability may tend to rebuff this extra burn-in as follows: 1. Unnecessary due to the higher reliability of today s components. 2. Consumes investment resources with no immediate return.