This article presents prognosis implementation from an industrial perspective. From the description of a use-case (available information, data, expertise, objective, expected performance indicators, etc.), an engineer should be able to select easily, among the large variety of prognosis methods, the ones that are compatible with his objectives and means. Many classifications of prognosis methods have already been published but they focus more on the techniques that are involved (physical model, statistical model, data-based model, ...) than on the necessary inputs to build/learn the model and/or run it and the expected outputs.

This paper presents the different strategies of maintenance and the place of prognostics in these strategies. The life cycle of a prognosis function is described, which helps to define relevant, yet certainly not complete, characteristics of prognosis problems and methods. Depending on the maintenance strategy, the prognosis function will not be used at the same step and with different objectives. Two different steps of use are defined when using the prognosis function: evaluation of the current state and prediction of the prognosis output.

The paper also illustrates on one example the fact that, depending on the information at hand, the prognosis method chosen is different.