Throughout the many years of accelerated life testing (ALT) development, colleagues have found numerous ways to take advantage of the interaction of stress and failure mechanisms.[1-14] In an ideal situation, the reliability engineer will have ample time, samples, test resources, and knowledge to conduct ALT. However, this is often not the case. Trading off the risks in conducting ALT and meeting the myriad constraints and expectations is a challenge. Understanding the basics of ALT approaches and associated assumptions permits test designers to select the ALT method that will provide meaningful results in time for technical and business decisions while meeting budgetary and risk-tolerance limits. There is no single way to design ALT for a specific set of conditions, but clearly articulating the tradeoffs involved permits the entire design team to fully understand the test results. The "best" ALT is a method that adds value to the design process. The most accurate results would involve testing all the production units in customer use until all units have failed. Although this is clearly not practical, neither is the simple-minded approach of guessing at the results. In between these two extremes lies an optimal approach: the most efficient ALT that provides meaningful results. When the results provide information to make design or program decisions, ALT adds value. Reducing ALT costs by reducing sample size or test duration is possible, but doing so may significantly increase uncertainty of the results. Running the test longer to achieve more accurate results is often constrained by the timeline to make decisions. Such tradeoffs force reliability engineers to carefully design each ALT and determine the best path forward.

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