Abstract

For many products, an underlying degradation process is the root cause of failures. Often, such degradation processes are not directly observable and all that can be learned from the test is the time of failure. In order to get useful information in a short time, accelerated degradation testing is frequently used. Most of the existing degradation analysis methods assume that the degradation process can be regularly inspected and the degradation amount can be easily and accurately measured. Unfortunately, for many products and many testing processes, this is not an easy task. In this paper, a design of experiment (DOE) method of using the degradation process together with the observed failure data to improve reliability is proposed. Unlike other degradation analysis methods, the proposed method does not require regular degradation measurements. In the use of DOE, all the factors that affect the degradation process are classified into two types. The Type I factor is called the amplification factor. Its effect on degradations is well known based on the engineering knowledge of the physical process of the degradation. This factor is used to amplify (accelerate) the degradation process. The type II factors are called control factors. Their effects are unknown and need to be studied by experiments. By combing the engineering knowledge and the observed failures, the effects of control factors are analyzed using a linear regression method. Important effects and the optimum settings of control factors are identified. The product reliability can be improved by operating under the optimum settings.

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