Prediction of obsolescence degree as a function of time: A mathematical formulation

Predicting the obsolescence risk of components is an important challenge in system life-cycle management to improve its durability. The degree measures occurrence risk. Thus, it expresses probability that entity will become obsolete within a given time horizon. Some mathematical techniques have already been proposed deal with this problem. Recent studies also shown machine learning methods can be effective way prediction capability. However, these two classes assess by scalar at observation time. This does not permit projection possible evolution over paper proposes new approach based on distribution model as function Based sales data, modeled time, and remaining time-to-obsolescence inferred. tested smartphones’ obsolescence. study's results are then analyzed while proposing future work carried out increase approach's applicability.