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Tests d'adéquation aux processus de dégradation sans ou avec maintenance imparfaite // Goodness-of- t tests for degradation modelling without or with imperfect maintenance

The management of industrial assets and the extension of their service life-through monitoring of their operational condition and effective maintenance-represent a major industrial challenge. In this context, the level of degradation of critical industrial assets is regularly measured using sensors. The evolution of this degradation level is modeled using stochastic processes, the most common of which are Wiener processes and Gamma processes. Using appropriate statistical methods, it is possible to estimate the parameters of these models, which allows for the calculation of reliability indicators, such as remaining useful life, and the implementation of an optimal maintenance policy. The objective of this thesis is to propose tests of goodness-of-fit for degradation processes with or without maintenance, ranging from theoretical developments to practical implementation., Etudiant.e titulaire ou en cours d'obtention d'un Master 2 ou de dernière année d'école d'ingénieur en probabilités appliquées, statistique, science des données. Compétence en programmation en R, Python ou Julia. Première expérience souhaitée en fiabilité et modélisation de la dégradation.Students who have earned or are in the process of earning a Master's or engineering degree in applied probability, statistics, or data science. Programming skills in R, Python, or Julia. Initial experience in reliability and degradation modeling is preferred.

ANR Financement d'Agences de financement de la recherche