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Accelerated life testing of products, components and materials is to get information quickly on specific lives, life distributions, failure rates, mean lives, and reliabilities. Accelerated testing is achieved by subjecting the test units to application and operation stress levels that are more severe than the stress levels applied during normal use in order to shorten their lives or their times to failure. If the results can be extrapolated to the stress levels encountered during normal use, they yield estimates of the lives and reliabilities under use stresses. Such tests provide savings in time and expense, since for many products, components, and materials, life under use conditions is so long that testing under those conditions is not timely or economically feasible.Accelerated test conditions are typically produced by testing units at higher levels of temperature, voltage, wattage, pressure, vibration amplitude, frequency, cycling rate, loads, humidity, etc. (or some combination thereof) that are encountered under use conditions. Life data obtained from units tested at different elevated stresses are analyzed and extrapolated to obtain an estimate of the life and reliability at stress levels of typical use. The use of such accelerating variables for a specific product or material is dictated by experienced engineering practice. For example, when choosing the stress level at which a test will be performed, one must be cautious not to exceed the material limitations under the specific stress and to avoid introducing failure modes that would not be observed under use conditions.The following accelerated test models were covered by Kececioglu [1]: (1) Arrhenius; (2) Eyring; (3) inverse power law; (4) combination, when two or more accelerated stresses are applied, such as combinations of temperature and voltage; (5) generalized Eyring; (6) Bazovsky; and (7) Weibull stress life. This chapter covers the following additional accelerated testing models and their practical applications:1. Log-log stress-life 2. Overload-stress 3. Combined-stress percent-life 4. Deterioration monitoring 5.Step-stressThe log-log stress-life model uses a log-log plot of stress-life data to develop curves for specific reliabilities at various functional stress levels. The overload-stress model presents a unique equation for reliability, which combines the Weibull and the log-log stress-life models' results to determine the reliability of units at their use-stress level, having determined their reliability at a higher stress level.The combined-stress percent-life model analyzes the results when one unit is tested to failure at an elevated stress, and another unit is tested -first for a fraction of its life at the use-stress level, and subsequently at the high stress level used for the first unit -until this second unit fails. A first-approximation straight line is drawn to relate stress level and associated life, from which the use-stress life is determined. The deterioration-monitoring model involves monitoring, at both use and accelerat...

Early life failures are usually attributed to problems in the manufacturing, packaging, and assembling phases. After making improvements to the greatest possible extent in these phases, the only way to improve the product's reliability is to eliminate defective units before they reach customers. A common approach used to weed out defective and weak parts before shipping the products to customers is burn‐in testing. Burn‐in testing has become a frequently used procedure in many industries, especially the semiconductor industry. In this article, an overview of burn‐in testing is presented and its applications are explained. Burn‐in methods are related to a variety of failure mechanisms and the conditions under which the tests are run are specified. Finally, the burn‐in time is determined through a reliability bathtub curve model to be the time after which the failure rate remains constant.