Genetic Algorithm and VR for Assessing the Level of Expertise of Maintenance Operator

FOLTYN, Axel; GUILLET, Christophe; DANGLADE, Florence; MERIENNE, Frederic

Communication avec acte

Auteur

FOLTYN, Axel

GUILLET, Christophe
300270 Université de Bourgogne [UB]
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]

DANGLADE, Florence
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]

MERIENNE, Frederic
245112 Ecole Nationale Supérieure d'Arts et Métiers [Cluny] [ENSAM | Cluny]
496957 Laboratoire Interdisciplinaire Carnot de Bourgogne [ICB]
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]

URI

http://hdl.handle.net/10985/25604

DOI

10.1007/978-3-031-71707-9_31

Date

2024-09

Résumé

The study aims to find the features for assessing the level of a maintenance operator. A genetic algorithm is used to identify the most relevant features and reduce their size. Based on 30 different features entered, we demonstrate that only three operator-level evaluation features provide a good classification. Virtual reality was used to simulate maintenance operations, collect data, and validate our method for identifying the most relevant features.

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