Failure rate modeling using equipment inspection data

System reliability models typically use average equipment failure rates. Even if these models are calibrated based on historical reliability indices, all-like components within a calibrated region remain homogeneous. This paper presents a new method of customizing failure rates using equipment inspection data. This allows available inspection information to be reflected in system models, and allows for calibration based on interruption distributions rather than mean values. The paper begins by presenting a method to map equipment inspection data to a normalized condition score, and suggests a formula to convert this score into failure probability. The paper concludes by applying this methodology to a test system based on an actual distribution system, and shows that the incorporation of condition data leads to richer reliability models.