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MPXM2102AS 数据表(PDF) 32 Page - Motorola, Inc |
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MPXM2102AS 数据表(HTML) 32 Page - Motorola, Inc |
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32 / 670 page ![]() 1–26 Motorola Sensor Device Data www.motorola.com/semiconductors Figure 13. Photograph of the aqueous alkaline solution test system and the data acquisition system for in situ monitoring of the MEMS devices. LIFETIME MODELING Reliability techniques provide a means to analyze media test results and equate the performance to a lifetime [23–24]. The primary reliability techniques involve an understanding of the failure rate, life distributions, and acceleration modeling. The failure rate for a product’s lifetime follows the bathtub curve. This curve, as shown in Figure 14, has an early life period with a decreasing failure rate. Manufacturing defects would be an example of failures during this portion of the curve. The second portion of the curve, often described as the useful life region has a constant failure rate. The last section has an increasing failure rate and is referred to as the wearout region. This wearout region would include failure mechanisms such as corrosion or fatigue. Figure 14. Bathtub curve showing various failure rate regions. Product Failure Rate INFANT MORTALITY OR EARLY LIFE FAILURE RATE END OF LIFE OR WEAR OUT FAILURE RATE Time STEADY STATE FAILURE RATE Lifetime distributions provide a theoretical model to describe device lifetimes. Common lifetime distributions include the exponential, Weibull, lognormal, and extreme value. The exponential distribution models a lifetime with a constant failure rate An example of the exponential distribution is a glass which has an equal probability of failing the moment after it is manufactured, or when its ten years old. The Weibull and lognormal distribution are all right, or Freescale Semiconductor, Inc. For More Information On This Product, Go to: www.freescale.com |
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