Prognostic algorithm categorization with PHM Challenge application

Prognostic algorithms can be divided into three major categories. The most basic methods model the component or system reliability using failure time data and conventional models such as the Weibull. When information pertaining to the operating condition and environmental stressors are available, stress-based techniques can be used. The third type of prognostics is termed effects-based. It is truly an individual based prognostics because it uses information as to how the individual component is affected by the usage condition. This paper presents a summary of the three prognostic types and describes the ongoing development of a Matlab-based set of tools to facilitate prognostic model development. The application of models of each type is illustrated with the PHM Challenge data set. The paper shows the advantages of identifying a degradation parameter to provide for the use of effects-based prognostics.