  | Colantonio, L., Moroncini, G., Sénéchal, O., Dehombreux, P., Ducobu, F., & Equeter, L. (2026). Joint Cost and Environmental Assessment of Tool Replacement Strategies Under Imperfect Wear Monitoring in Milling. In L. Equeter (Ed.), Proceedings of the Collaborative Research and Education for Asset Management 5.0 International Conference. Éditions universitaires de l'UMONS.  Peer reviewed |
 | Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (17 March 2026). Cutting Tool Condition Monitoring with Artificial Intelligence [Poster presentation]. Researchers Tuesday. |
 | Colantonio, L. (2026). Cutting Tool Condition Monitoring and Forecasting with Artificial Intelligence Approaches [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/55577 |
Dehombreux, P., El Hiki, L., Bendjelloul, N., Stassin, S., Colantonio, L., & Domgue Kamwa, L. I. (12 December 2025). L’Institut Risques de l’UMONS : recherches, formations et perspectives en prévention [Paper presentation]. FestIA, Mons, Belgium. |
 | Colantonio, L., Moroncini, G., Sénéchal, O., Dehombreux, P., Ducobu, F., & Equeter, L. (11 November 2025). Cost and Environmental Assessment of Tool Replacement Strategies Under Imperfect Wear Monitoring in Ti6Al4V Milling. International Journal of Prognostics and Health Management, 16 (4). doi:10.36001/ijphm.2025.v16i4.4269 Peer Reviewed verified by ORBi |
 | EQUETER, L., Do, P., COLANTONIO, L., TIBERI, L., DEHOMBREUX, P., & Iung, B. (14 October 2025). Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review. Machines, 13 (10), 947. doi:10.3390/machines13100947 Peer Reviewed verified by ORBi |
Colantonio, L., Equeter, L., Giovannelli, H., Dehombreux, P., Mahmoudi, S., & Ducobu, F. (October 2025). Image processing with deep-learning and transfer learning for cutting tool degradation monitoring [Paper presentation]. 13th CIRP Global Web Conference, CIRPe 2025, Hong-Kong, Hong Kong SAR China. |
 | Colantonio, L., Moroncini, G., Sénéchal, O., Dehombreux, P., Ducobu, F., & Equeter, L. (09 July 2025). Joint environmental and economic assessment of cutting tool replacement policies in Ti6Al4V milling under uncertain condition estimate [Paper presentation]. 13th IMA International Conference on Modelling in Industrial Maintenance and Reliability MIMAR2025, Nancy, France. Peer reviewed |
Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (23 May 2025). Explainable AI for tool condition monitoring using Explainable Boosting Machine [Paper presentation]. 20th CIRP Conference on Modeling of Machining Operations, CIRP CMMO, Mons, Belgium. |
 | 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 verified by ORBi |
 | 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 |
