在壽命檢測試驗中，當我們因故或基於實驗上的方便無法連續觀察檢驗產品時，可以採用區間設限方式進行試驗，此外，對於許多長壽命的零件與產品，我們很難在試驗結束之前觀測到足夠的試驗單位死亡個數，此時可以採用加速壽命試驗的方式進行試驗，此種試驗方法可使受測的試驗單位提早故障，以有效地減少試驗所需的時間，並達到縮減成本的目的。本論文結合逐步應力加速試驗、型一設限以及區間設限，探討當產品壽命服從Rayleigh分配時，如何建立壽命檢驗計畫，在給定生產者風險與消費者風險下，求出壽命檢驗計畫所需的最小樣本數，以及判定貨批是否接受的壽命檢定臨界值，並將以上結果編製成表，以利實務界使用。 / In life test experiment we use interval censoring to complete it when we can not inspect the experiment units continuously due to some accidents or for convenience. Furthermore, it is difficult to obtain enough units of breakdown products for many long life components and products. At this moment we can adopt step-stress life test to proceed the experiment. Using this method we can make the test units breakdown early for reducing the time test needed effectively and save prime cost. In this thesis, acceptance sampling plans are established for Rayleigh lifetime data under step-stress and type I interval censoring scheme. The minimum sample sizes and the corresponding critical values of lifetime needed for test plans are found. Some tables are provided for the use of the proposed test plans.

本文所探討的中心為貝氏模型運用於加速壽命試驗，並且假設受測項目之壽命服從Weibull分配。加速實驗環境有三種，其中第二種環境代表正常狀態，採用加速壽命試驗的方式涵蓋了三種：固定應力、漸進之逐步應力和變量曲線之逐步應力。對於先驗參數，並不是直接給予特定的值，而是透過專家評估，給定各種環境之下的產品可靠度之中位數或百分位數，再利用這些資訊經過數值運算解出先驗參數。資料的型態分成兩種，一為區間資料，另一為型一設限資料，透過蒙地卡羅法模擬出後驗分配，並且估計正常環境狀態的可靠度。 / This article develops a Bayes inference model for accelerated life testing assuming failure times at each stress level are Weibull distributed. Using the approach, there are three stressed to be used, and the three testing scenarios to be adapted are as follows：fixed-stress, progressive step-stress and profile step-stress. Prior information is used to indirectly define a multivariate prior distribution for the scale parameters at the various stress levels. The inference procedure accommodates both the interval data sampling strategy and type I censored sampling strategy for the collection of ALT test data. The inference procedure uses the well-known Markov Chain Monte Carlo methods to derive posterior approximations.