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A condition-based maintenance program is proposed to reduce the device testing cost by utilizing tester's self-diagnostic data. The degradation signal is modeled as a nonstationary Gaussian process with time-varying mean and variance. Based on the degradation model, an optimization algorithm is devised to determine the best maintenance policy such that production loss due to equipment failures is minimized. Simulations and numerical examples are provided to demonstrate the performance of the method.