| Predictive maintenance: A novel framework for a data-driven, semi-supervised, and partially online prognostic health management application in industries F Calabrese, A Regattieri, M Bortolini, M Gamberi, F Pilati Applied Sciences 11 (8), 3380, 2021 | 50 | 2021 |
| Unsupervised fault detection and prediction of remaining useful life for online prognostic health management of mechanical systems F Calabrese, A Regattieri, L Botti, C Mora, FG Galizia Applied sciences 10 (12), 4120, 2020 | 32 | 2020 |
| Prognostic health management of production systems. New proposed approach and experimental evidences F Calabrese, A Regattieri, L Botti, FG Galizia Procedia Manufacturing 39, 260-269, 2019 | 22 | 2019 |
| A three-objective optimization model for mid-term sustainable supply chain network design M Bortolini, F Calabrese, FG Galizia, C Mora Computers & Industrial Engineering 168, 108131, 2022 | 21 | 2022 |
| Novelty detection with autoencoders for system health monitoring in industrial environments F Del Buono, F Calabrese, A Baraldi, M Paganelli, F Guerra Applied Sciences 12 (10), 4931, 2022 | 15 | 2022 |
| Feature-based multi-class classification and novelty detection for fault diagnosis of industrial machinery F Calabrese, A Regattieri, M Bortolini, FG Galizia, L Visentini Applied Sciences 11 (20), 9580, 2021 | 14 | 2021 |
| Data-driven predictive maintenance in evolving environments: A comparison between machine learning and deep learning for novelty detection F Del Buono, F Calabrese, A Baraldi, M Paganelli, A Regattieri Proceedings of the International Conference on Sustainable Design and …, 2021 | 8 | 2021 |
| Components monitoring and intelligent diagnosis tools for Prognostic Health Management approach F Calabrese, C Andrea, A Regattieri, F Piana Proceedings of the 23rd Summer School" Francesco Turco"-Industrial Systems …, 2018 | 8 | 2018 |
| Industry 4.0 technologies: A cross-sector industry-based analysis M Bortolini, F Calabrese, FG Galizia, C Mora, V Ventura Sustainable Design and Manufacturing: Proceedings of the 8th International …, 2022 | 7 | 2022 |
| A two-step methodology for product platform design and assessment in high-variety manufacturing M Bortolini, F Calabrese, FG Galizia, A Regattieri The International Journal of Advanced Manufacturing Technology 126 (9), 3923 …, 2023 | 6 | 2023 |
| Data-Driven Fault Detection and Diagnosis: Challenges and Opportunities in Real-World Scenarios F Calabrese, A Regattieri, M Bortolini, FG Galizia Applied Sciences 12 (18), 9212, 2022 | 6 | 2022 |
| Fault diagnosis in industries: How to improve the health assessment of rotating machinery F Calabrese, A Regattieri, M Bortolini, FG Galizia Proceedings of the International Conference on Sustainable Design and …, 2021 | 5 | 2021 |
| A cross‐sectorial review of industrial best practices and case histories on Industry 4.0 technologies FG Galizia, M Bortolini, F Calabrese Systems Engineering 26 (6), 908-924, 2023 | 4 | 2023 |
| Crowd logistics: a survey of successful applications and implementation potential in northern Italy M Bortolini, F Calabrese, FG Galizia Sustainability 14 (24), 16881, 2022 | 3 | 2022 |
| Genetic Programming-Based Feature Construction for System Setting Recognition and Component-Level Prognostics F Calabrese, A Regattieri, R Piscitelli, M Bortolini, FG Galizia Applied Sciences 12 (9), 4749, 2022 | 3 | 2022 |
| A Data-Driven Approach to Predict Supply Chain Risk Due to Suppliers’ Partial Shipments M Gabellini, F Calabrese, L Civolani, A Regattieri, C Mora International Conference on Sustainable Design and Manufacturing, 227-237, 2023 | 2 | 2023 |
| A Data Model for Predictive Supply Chain Risk Management M Gabellini, L Civolani, A Regattieri, F Calabrese Proceedings of the Changeable, Agile, Reconfigurable and Virtual Production …, 2023 | 2 | 2023 |
| Data-driven prognostics: from an offline and supervised analysis to an innovative, online and unsupervised methodology F Calabrese, M Gamberi, S Margelli, F Pilati, A Regattieri ... SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS 2019, 74-80, 2019 | 2 | 2019 |
| Optimizing Makespan in Single-Model Assembly Lines with Human-Robot Collaboration A Caporale, FG Galizia, F Calabrese, M Bortolini, C Mora, E Ferrari Proceedings of the Changeable, Agile, Reconfigurable and Virtual Production …, 2023 | 1 | 2023 |
| Rapporto con gli studi sviluppati circa estrazione features, apprendimento supervisionato e non, algoritmi on-line per la diagnostica, algoritmi per la stima della RUL … A Regattieri, F Calabrese | 1 | 2020 |
