Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (2025). Explainable AI for tool condition monitoring using Explainable Boosting Machine. In Procedia CIRP. ScienceDirect.  Peer reviewed |
  | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (03 April 2025). Explainable AI for tool condition monitoring using Explainable Boosting Machine. Procedia CIRP, 133, 138-143. doi:10.1016/j.procir.2025.02.025 Peer Reviewed verified by ORBi |
 | Colantonio, L., Equeter, L., Giovannelli, H., Dehombreux, P., Mahmoudi, S., & Ducobu, F. (2025). Image processing with deep-learning and transfer learning for cutting tool degradation monitoring. Procedia CIRP, 132, 50-55. doi:10.1016/j.procir.2025.01.009 Peer Reviewed verified by ORBi |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (2024). Industrial Tool Condition Monitoring: Integrated Direct And Indirect Approach For Automated Database Creation. In Krzysztof Kolowrocki & Ewa Dabrowska (Eds.), Advances in Reliability, Safety and Security - ESREL 2024 Collection of Extended Abstracts Part 1. Gdynia, Poland: Polish Safety and Reliability Association. Peer reviewed |
 | COLANTONIO, L., EQUETER, L., DEHOMBREUX, P., & DUCOBU, F. (26 May 2024). Confidence Interval Estimation for Cutting Tool Wear Prediction in Turning Using Bootstrap-Based Artificial Neural Networks. Sensors, 24 (11), 3432. doi:10.3390/s24113432 Peer Reviewed verified by ORBi |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (2024). Comparison of artificial intelligence techniques for cutting tool condition monitoring. Materials Research Proceedings. doi:10.21741/9781644903131-217 Peer reviewed |
Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (25 April 2024). Comparison of artificial intelligence techniques for cutting tool condition monitoring [Paper presentation]. 27th International ESAFORM Conference on Material Forming, ESAFORM 2024, Toulouse, France. Peer reviewed |
  | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (26 March 2024). Predicting the Health of Cutting Tool with Artificial Intelligence [Poster presentation]. Mardi des chercheurs 2024 (MdC 2024). |
Colantonio, L., Equeter, L., Giovannelli, H., Mahmoudi, S., Dehombreux, P., & Ducobu, F. (2024). Image Processing With Deep-Learning And Transfer Learning For Cutting Tool Degradation Monitoring [Paper presentation]. 12th CIRP Global Web Conference (CIRPe 2024). Peer reviewed |
Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (October 2023). Suivi de la Dégradation des Outils de Coupe avec des Méthodes d’Intelligence Artificielle [Paper presentation]. 31èmes Journées Manufacturing'21, Cluny, France. |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (2023). Cutting Tool Degradation Monitoring in Turning with Artificial Neural Network. In Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023). Singapore, Singapore: Research Publishing, Singapore. doi:10.3850/978-981-18-8071-1_P287-cd Peer reviewed |
Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (03 July 2023). Cutting Tool Health Monitoring in Turning with AI [Paper presentation]. 12th IMA International Conference on Modelling in Industrial Maintenance and Reliability (MIMAR), Nottingham, United Kingdom. Peer reviewed |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (19 April 2023). Comparison of cutting tool wear classification performance with artificial intelligence techniques. Materials Research Proceedings, 28, 1265-1274. doi:10.21741/9781644902479-137 Peer reviewed |
Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (19 April 2023). Comparison of cutting tool wear classification performance with artificial intelligence techniques [Paper presentation]. 26th International ESAFORM Conference on Material Forming, ESAFORM 2023. Peer reviewed |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (24 November 2022). Cutting Tool Health Monitoring in Turning with Artificial Intelligence Technique [Paper presentation]. 6th International Conference on System Reliability and Safety, Venise, Italy. Peer reviewed |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (06 September 2022). Predicting the Health of Cutting Tools with Artificial Intelligence [Poster presentation]. Mardi des Chercheurs 2022 (MdC2022). |
 | Dehombreux, P., Equeter, L., & Colantonio, L. (2022). OPPORTUNISTIC MAINTENANCE: A NEWER NAME TO GOOD PRACTICE. Assets Performance Magazine, p. 36-40. |
Colantonio, L. (13 May 2022). Prédiction de la dégradation des outils de coupe avec des méthodes d'intelligence artificielle [Paper presentation]. 30 èmes journée Manufacturing'21, Besançon, France. |
 | Colantonio, L., Dehombreux, P., Hajzman, M., & Verlinden, O. (2022). 3D projection of the LuGre friction model adapted to varying normal forces. Multibody System Dynamics. Peer reviewed |
 | Colantonio, L., Dehombreux, P., Hajzman, M., & Verlinden, O. (2021). 3D LuGre Model for Multibody Systems Involving Contacts with Stick-slip [Paper presentation]. ECCOMAS Thematic Conference on Multibody Dynamics, Budapest, Hungary. |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (10 December 2021). A Systematic Literature Review of Cutting Tool Wear Monitoring in Turning by Using Artificial Intelligence Techniques. Machines, 9 (351), 1-54. doi:10.3390/machines9120351 Peer Reviewed verified by ORBi |
Colantonio, L. (26 January 2021). Prédiction de la Dégradation des outils de coupe par des méthodes d'intelligence artificielle [Paper presentation]. 29èmes Journées Manufacturing'21, Online, Unknown/unspecified. |
 | Colantonio, L. (2020). Study of blade vibration damping by friction: Verlinden Olivier, Michal Hajzman [Master’s dissertation, Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/42486 |
