Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study

Abstract

In this paper, we propose a study of the decision horizon duration for rolling stock mission assignment and maintenance planning in a prognostics and health management (PHM) context. The aim is to determine the best decision horizon duration that allows the construction of a suitable schedule that assigns railways vehicles to missions and integrates required maintenance operations according to the current and future health of the vehicles. A genetic algorithm is used to minimize the overall cost of the joint schedule as a function of the decision horizon. The results are compared to three proposed heuristics to study the influence of the resolution method on the decision horizon duration. The best decision horizon duration is given for each used method for an illustration case.

Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach

“…For these reasons, prognostics and health monitoring (PHM) for actuators are gaining interest among researchers 3,5,6 . Among them, a particular focus is related to the determination of the actuators' healthy status in order to estimate their time‐to‐failure or remaining‐useful‐lifetime (RUL) 7 .…”

“…For these reasons, prognostics and health monitoring (PHM) for actuators are gaining interest among researchers. 3,5,6 Among them, a particular focus is related to the determination of the actuators' healthy status in order to estimate their time-to-failure or remaining-useful-lifetime (RUL). 7 The latter quantity can be exploited in a maintenance plan to schedule future interventions to prevent undesired monitored device crash.…”