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lower stresses. This issue can be approached by more tests at a greater range of stresses however the cause of failure must remain unchanged. A possible pre-experiment approach to minimize this is to estimate what data you expect from testing, fit a model to the data, and determine if one would be able to make reliable conclusions if everything went as expected.
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stress and how many test subjects have failed so far. Step stress ALT can increment low to high, high to low, or through a mix of levels. A step stress ALT test that is interested in extrapolating a life distribution to constant operating conditions must be able to relate the life distribution observed under changing stresses to one of constant stresses.
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As a simplified example, consider a test object with a life distribution that roughly matches a normal distribution. Tests at various stress levels would yield different values for the mean and standard deviation of the distribution. (its parameters) One would then use a known model or attempt to fit
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When the model is known in advance the test only needs to identify the parameters for the model, however it is necessary to ensure that the model being used has been well verified. Established models must show agreement between extrapolations from accelerated data and observed data across a range of
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A model is an equation that accurately relates a test object's performance to the levels of stress on it. This can be referred to as an acceleration model, with any constants called acceleration factors. The acceleration model is usually related to the types of materials or components tested. A few
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type relationship with respect to time and temperature (for example, creep, stress relaxation, and tensile properties). If one conducts short tests at elevated temperatures, that data can be used to extrapolate the behavior of the polymer at room temperature, avoiding the need to do lengthy, and
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When the appropriate model is not known in advance, or there exist multiple accepted models, the test must estimate what model fits best based on the context of the test and results from testing. Even if two models fit data at high stresses equally well, they may differ by orders of magnitude at
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A step stress ALT is a variant of ALT that tests a component at multiple stress levels, one after the other. Components that survive one test are immediately subjected to the next. These are widely modeled under the assumption that survival life of a product depends only on the current level of
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All factors thought to influence the test object should be involved and tests should be conducted at various levels of each factor. Higher stress levels will speed up the test more however the cause of failure or other response measured must not be changed. For instance, melting components in a
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For instance, a reliability test on circuits that must last years at use conditions (high longevity) would need to yield results in a much shorter time. If the test wanted to estimate how frequently the circuits needed to be replaced, then the category of low failure would also be applicable.
27:, temperatures, voltage, vibration rate, pressure etc.) in excess of its normal service parameters in an effort to uncover faults and potential modes of failure in a short amount of time. By analyzing the product's response to such tests,
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circuit would alter why the circuit failed. Increasing the number of tests or the number of test objects in each test generally increases how precisely one can infer the test object's behavior at operating conditions.
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How one factors in the effect of time depends largely on what one is measuring. For instance, a test that is measuring lifespan may look only at the mean time to failure of the test objects, or it may try to
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Furthermore, if the circuits wore out from gradual use rather than extreme use (such as a large sudden shock), the wear out category would be involved. If a sudden shock was the primary cause of failure, a
38:, testing may be done at elevated temperatures to produce a result in a shorter amount of time than it could be produced at ambient temperatures. Many mechanical properties of polymers have an
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a model to relate how each stress factor influenced the distributions parameters. This relation would then be used to estimate the life distribution at operating conditions.
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Designing a test involves considering what factors affect the test object, what you already know about the test object's behavior, and what you want to learn from the test.
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Herrmann, W.; Bogdanski, N. (2011-06-01). "Outdoor weathering of PV modules — Effects of various climates and comparison with accelerated laboratory testing".
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Wang, Ronghua; Sha, Naijun; Gu, Beiqing; Xu, Xiaoling (2012-06-01). "Comparison
Analysis of Efficiency for Step-Down and Step-Up Stress Accelerated Life Testing".
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https://www.dfrsolutions.com/hubfs/Resources/services/Temperature-and-Humidity-Acceleration-Factors-on-MLV-Lifetime.pdf?t=1514473946162
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distributions. In any case, the parameters would be related to the test subjects and the levels of the stress factors being tested.
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Inference from the results of an accelerated life test requires being able to relate the test object's response (lifespan,
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High longevity - The product must be reliable for a much longer time than can be reasonably tested at normal conditions.
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Low failure - Testing even a very large sample at normal conditions would yield few or no failures in a reasonable time.
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of which represents the proportion of products failing at a given time. Several distributions for this purpose are the
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Nelson, Wayne (1980-06-01). "Accelerated Life
Testing - Step-Stress Models and Data Analyses".
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542:"8.1.6. What are the basic lifetime distribution models used for non-repairable populations?"
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ALT is primarily used to speed up tests. This is particularly useful in several cases:
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Nelson, W. (1980). "Accelerated Life
Testing - Step-Stress Models and Data Analyses".
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High wear-out - The primary cause of failure occurs over an extended amount of time.
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can make predictions about the service life and maintenance intervals of a product.
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Donahoe, D.; Zhao, K.; Murray, S.; Ray, R. M. (2008). "Accelerated Life
Testing".
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Srivastava, P.W.; Shukla, R. (2008-09-01). "A Log-Logistic Step-Stress Model".
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Temperature and
Humidity Acceleration Factors on MLV Lifetime, G. Caswell,
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Spencer, F. W. (1991). "Statistical
Methods in Accelerated Life Testing".
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https://www.dfrsolutions.com/resources/test-plan-development-how-to-do-it
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to the data. This is usually referred to as a life distribution, the
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is the process of testing a product by subjecting it to conditions (
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Test Plan
Development: How To Do It, G. Sharon, November 19, 2015,
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347:Elsayed, E. A. (2003). "Accelerated Life Testing".
406:2011 37th IEEE Photovoltaic Specialists Conference
96:equations used for acceleration models are the
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104:for temperature and humidity, and the
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349:Handbook of Reliability Engineering
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475:"8.3.1.4. Accelerated life tests"
167:Step-Stress Accelerated Life Test
610:IEEE Transactions on Reliability
567:IEEE Transactions on Reliability
500:IEEE Transactions on Reliability
248:IEEE Transactions on Reliability
445:Sorensen, Rob (May 28, 2010).
316:10.1002/9780470061596.risk0452
293:10.1080/00401706.1991.10484846
100:for high temperature fatigue,
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454:Sandia National Laboratories
202:Highly Accelerated Life Test
142:probability density function
68:Highly Accelerated Life Test
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447:"Accelerated Life Testing"
408:. pp. 002305–002311.
414:10.1109/PVSC.2011.6186415
197:Reliability (engineering)
108:for temperature cycling.
70:may be more appropriate.
357:10.1007/1-85233-841-5_22
182:Research and development
138:statistical distribution
17:Accelerated life testing
622:10.1109/TR.1980.5220742
579:10.1109/TR.2012.2182816
256:10.1109/TR.1980.5220742
43:hence expensive tests.
512:10.1109/TR.2008.928182
658:Environmental testing
351:. pp. 415–428.
120:Acceleration Factors
187:Product management
423:978-1-4244-9965-6
366:978-1-85233-453-6
207:Accelerated aging
74:Setting up a test
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459:October 20,
146:exponential
551:2015-10-20
484:2015-10-20
250:(2): 103.
233:References
630:0018-9529
587:0018-9529
520:0018-9529
217:Cox model
212:AFT model
126:corrosion
98:Arrhenius
40:Arrhenius
29:engineers
652:Category
638:35734439
528:20244594
432:20511202
334:86534403
264:35734439
176:See also
36:polymers
595:5903153
150:Weibull
47:Purpose
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155:, and
102:Eyring
25:strain
21:stress
634:S2CID
591:S2CID
524:S2CID
450:(PDF)
428:S2CID
330:S2CID
260:S2CID
157:gamma
626:ISSN
614:R-29
583:ISSN
516:ISSN
461:2015
418:ISBN
361:ISBN
320:ISBN
618:doi
575:doi
508:doi
410:doi
353:doi
312:doi
289:doi
252:doi
134:fit
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