Failure forecasting of aircraft air-conditioning/cooling pack with field data

This paper presents methods for modeling the failure of air-conditioning/cooling packs for a particular type of aircraft with field data. In many regards, field data are highly desirable for more accurate failure prediction by aircraft operators, because the data implicitly account for all actual usage and environmental stresses. It is not always possible to accurately anticipate or simulate these stresses in a laboratory or even in a field test. Field data, in a larger extent, are also important to the manufacturer, because the data identify product deficiencies and areas of improvement. In this study, the failure of the aircraft air-conditioning/cooling pack under a customer-use environment is first modeled at the component level by using the Weibull distribution and its extensions. These include the two-parameter Weibull model, three-parameter Weibull model, mixture model, and phased bi-Weibull model. The number of failures over time is estimated by a renewal process. The failure of the air-conditioning/cooling pack at the system level is then modeled by using the power law process model. The failure trend is tested by the Laplace test. The results give an insight into the reliability and quality of the air-conditioning/cooling pack under actual operating conditions. The models presented here can be used by aircraft operators for assessing system and component failures and customizing the maintenance programs recommended by the manufacturer.