An iterative methodology for reliability prediction

While much research has focused on the development of reliability prediction methodologies for the electronics industry, far less work addresses the evaluation of mechanical rotating equipment. Structured prediction methodologies that consider and attempt to reduce the resource requirements of reliability prediction do not exist in this realm. Various prediction techniques to ascertain the failure rates of mechanical equipment are widely accepted and applied, each having different resource requirements and each inducing different degrees of uncertainty. A methodology is reported herein to assist the engineer in performing reliability prediction. This iterative framework utilizes simulation to evaluate the uncertainty of reliability prediction, and, in each iteration, identifies the critical components that have the greatest impact on the uncertainty of predicted reliability for the entire system. Non-critical components are not included in the more rigorous, and costly, �ubsequent iterations. Thus, the engineer is presented with a tool by which the resources consumed in reliability prediction may be reduced.