摘要
高溫工作測試是用來測定高溫及高電壓對固態元件隨著時間變化的影響, 它是以加速的方式來模擬元件的工作條件, 而且主要是用來評估元件的可靠度。在此篇論文提出了一種模擬退火的演算法用來對於高溫工作測試的條件做最佳化, 我們的目標是要減少在硬體部份或是測試時間上面, 於高溫工作測試時所花的成本。並且我們也會對於可靠度的統計理論, 模擬退火演算法的由來及應用做一系列的探討。在我們的最佳化演算法裡, 必須計算較為精準的偏壓必v, 因為當最佳化過程中, 偏壓一旦改變, 不僅會影響到電壓加速因子, 同時也會影響到熱加速因子。因此我們利用曲線迴歸的方式來得到較為合理的加速因子及可靠度的計算, 並且, 對於曲線迴歸的模型選擇以及對不同模型所產生的適合度資料的統計分析會有詳盡的探討。在此篇論文, 我們也會介紹在不同的使用者設定的優先條件下程式執行的結果來驗證我們所提出方法的有效性。
並列摘要
HTOL (High Temperature Operation Life) test is used to determine the effects of bias and temperature stress conditions on solid-state devices over time. It simulates the devices’ operating condition in an accelerated manner, and is primarily for device reliability evaluation. This paper addresses an SA (Simulated Annealing) method used for the HTOL test stress condition decision-making that is an optimization problem. The goal is to reduce the resources for the HTOL test, hardware or time, under reliability constraints. The theory of reliability statistic model and the SA algorithm are presented. In our optimization algorithm, we need to calculate the accurate HTOL stressed power for the next optimization loop since the Vs (Stressed Voltage) that is optimized will affect not only Afv (Voltage Acceleration Factor) but also Aft (Thermal Acceleration Factor). A curve-fitting algorithm is applied to get reasonable accelerated factors and reliability calculations. The model selection process and statistical analysis of fitted data by different models are also presented. Experimental results with different stress condition priorities and different user settings are given to demonstrate the effectiveness of our approach.
參考文獻
延伸閱讀
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