REGATTIERI, ALBERTO
REGATTIERI, ALBERTO
DIPARTIMENTO DI INGEGNERIA INDUSTRIALE
Docenti di ruolo di Ia fascia
A Data-Driven Approach to Predict Supply Chain Risk Due to Suppliers’ Partial Shipments
2024 Gabellini, Matteo; Calabrese, Francesca; Civolani, Lorenzo; Regattieri, Alberto; Mora, Cristina
A hybrid approach integrating genetic algorithm and machine learning to solve the order picking batch assignment problem considering learning and fatigue of pickers
2024 Gabellini M.; Calabrese F.; Regattieri A.; Loske D.; Klumpp M.
Balancing Data Acquisition Benefits and Ordering Costs for Predictive Supplier Selection and Order Allocation
2024 Regattieri A.; Gabellini M.; Calabrese F.; Civolani L.; Galizia F.G.
A Data Model for Predictive Supply Chain Risk Management
2023 Gabellini M.; Civolani L.; Regattieri A.; Calabrese F.
A predictive data-driven approach for supply chain quality risks in the automotive sector
2023 Gabellini M.; Calabrese F.; Civolani L.; Regattieri A.; Galizia F.G.
A two-step methodology for product platform design and assessment in high-variety manufacturing
2023 Bortolini M.; Calabrese F.; Galizia F.G.; Regattieri A.
Condition Monitoring of CNC machines: machining process classification through Temporal Convolutional Networks
2023 Calabrese F.; Regattieri A.; Gabellini M.; Caporale A.; Epifania P.
Interaction between Lean and Green Supply Chain Management: experiences from the automotive sector
2023 Bortolini M.; Galizia F.G.; Gamberi M.; Mora C.; Naldi L.D.; Regattieri A.; Ronchi M.
Statistical Management and Modeling for Demand Spare Parts
2023 Ferrari E.; Pareschi A.; Regattieri A.; Persona A.
Assembly line balancing and activity scheduling for customised products manufacturing
2022 Pilati F.; Lelli G.; Regattieri A.; Ferrari E.
Data-Driven Fault Detection and Diagnosis: Challenges and Opportunities in Real-World Scenarios
2022 Calabrese, F; Regattieri, A; Bortolini, M; Galizia, FG
Data-Driven Predictive Maintenance in Evolving Environments: A Comparison Between Machine Learning and Deep Learning for Novelty Detection
2022 Del Buono F.; Calabrese F.; Baraldi A.; Paganelli M.; Regattieri A.
Fault Diagnosis in Industries: How to Improve the Health Assessment of Rotating Machinery
2022 Calabrese F.; Regattieri A.; Bortolini M.; Galizia F.G.
Genetic Programming-Based Feature Construction for System Setting Recognition and Component-Level Prognostics
2022 Calabrese F.; Regattieri A.; Galizia F.G.; Piscitelli R.; Bortolini M.
Multivariate multi-output LSTM for time series forecasting with intermittent demand patterns
2022 Gabellini M.; Calabrese F.; Regattieri A.; Ferrari E.
Semi-Automatic Rapid Upper Limb Assessment (RULA) with Azure Kinect of assembly and disassembly tasks, and the related learning curve
2022 Coruzzolo A.M.; Rossini S.; Neri A.; Lolli F.; Gamberini R.; Regattieri A.
An optimisation model for the dynamic management of cellular reconfigurable manufacturing systems under auxiliary module availability constraints
2021 Bortolini M.; Ferrari E.; Galizia F.G.; Regattieri A.
Bi‐objective design and management of reconfigurable manufacturing systems to optimize technical and ergonomic performances
2021 Bortolini M.; Botti L.; Galizia F.G.; Regattieri A.
Feature-based multi-class classification and novelty detection for fault diagnosis of industrial machinery
2021 Calabrese F.; Regattieri A.; Bortolini M.; Galizia F.G.; Visentini L.
Predictive maintenance: a novel framework for a data-driven, semi-supervised, and partially online prognostic health management application in industries
2021 Calabrese F.; Regattieri A.; Bortolini M.; Gamberi M.; Pilati F.