| The impact of Operations and IT-related Industry 4.0 key technologies on organizational resilience G Marcucci, S Antomarioni, FE Ciarapica, M Bevilacqua Production Planning & Control 33 (15), 1417-1431, 2022 | 132 | 2022 |
| A process to implement an artificial neural network and association rules techniques to improve asset performance and energy efficiency A Crespo Márquez, A de la Fuente Carmona, S Antomarioni Energies 12 (18), 3454, 2019 | 51 | 2019 |
| An approach based on association rules and social network analysis for managing environmental risk: A case study from a process industry F Ciarapica, M Bevilacqua, S Antomarioni Process Safety and Environmental Protection 128, 50-64, 2019 | 41 | 2019 |
| A predictive association rule-based maintenance policy to minimize the probability of breakages: application to an oil refinery S Antomarioni, O Pisacane, D Potena, M Bevilacqua, FE Ciarapica, ... The International Journal of Advanced Manufacturing Technology 105 (9), 3661 …, 2019 | 39 | 2019 |
| Defining a data-driven maintenance policy: an application to an oil refinery plant S Antomarioni, M Bevilacqua, D Potena, C Diamantini International Journal of Quality & Reliability Management 36 (1), 77-97, 2019 | 38 | 2019 |
| Lean principles for organizing items in an automated storage and retrieval system: an association rule mining–based approach M Bevilacqua, FE Ciarapica, S Antomarioni Management and Production Engineering Review 10 (1), 29-36, 2019 | 35 | 2019 |
| Data-driven decision support system for managing item allocation in an ASRS: A framework development and a case study S Antomarioni, L Lucantoni, FE Ciarapica, M Bevilacqua Expert Systems with Applications 185, 115622, 2021 | 29 | 2021 |
| Association rules and social network analysis for supporting failure mode effects and criticality analysis: Framework development and insights from an onshore platform S Antomarioni, FE Ciarapica, M Bevilacqua Safety science 150, 105711, 2022 | 27 | 2022 |
| Data-driven predictive maintenance policy based on multi-objective optimization approaches for the component repairing problem O Pisacane, D Potena, S Antomarioni, M Bevilacqua, ... Engineering optimization 53 (10), 1752-1771, 2021 | 23 | 2021 |
| Data-driven decision support tool for production planning: a framework combining association rules and simulation V Fani, S Antomarioni, R Bandinelli, M Bevilacqua Computers in Industry 144, 103800, 2023 | 20 | 2023 |
| More sustainable performances through lean practices: A case study S Antomarioni, M Bevilacqua, FE Ciarapica 2018 IEEE International Conference on Engineering, Technology and Innovation …, 2018 | 18 | 2018 |
| Deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric power plants RF da Silva, MM Bellinello, GFM de Souza, S Antomarioni, M Bevilacqua, ... Energies 14 (24), 8281, 2021 | 15 | 2021 |
| Lean projects’ evaluation: the perceived level of success and barriers S Antomarioni, M Bevilacqua, FE Ciarapica, I De Sanctis, J Ordieres-Meré Total Quality Management & Business Excellence 32 (13-14), 1441-1465, 2021 | 15 | 2021 |
| A data-driven approach to extend failure analysis: a framework development and a case study on a hydroelectric power plant S Antomarioni, MM Bellinello, M Bevilacqua, FE Ciarapica, RF da Silva, ... Energies 13 (23), 6400, 2020 | 13 | 2020 |
| Data-driven approach to predict the sequence of component failures: a framework and a case study on a process industry S Antomarioni, FE Ciarapica, M Bevilacqua International Journal of Quality & Reliability Management 40 (3), 752-776, 2022 | 12 | 2022 |
| Resilience in the Fashion Industry Supply Chain: State of the Art Literature Review S Antomarioni, M Bevilacqua, FE Ciarapica, G Marcucci Business Models and ICT Technologies for the Fashion Supply Chain …, 2019 | 10 | 2019 |
| Data mining and augmented reality: an application to the fashion industry V Fani, S Antomarioni, R Bandinelli, FE Ciarapica Applied Sciences 13 (4), 2317, 2023 | 9 | 2023 |
| Health Indicator for Predictive Maintenance Based on Fuzzy Cognitive Maps, Grey Wolf, and K‐Nearest Neighbors Algorithms G Mazzuto, S Antomarioni, FE Ciarapica, M Bevilacqua Mathematical Problems in Engineering 2021 (1), 8832011, 2021 | 9 | 2021 |
| Implementation of Industry 4.0 Techniques in Lean Production Technology: A Literature Review L Lucantoni, S Antomarioni, FE Ciarapica, M Bevilacqua Management and Production Engineering Review, 83-93-83-93, 2022 | 7 | 2022 |
| The influence of cultural dimensions on lean projects success and barriers S Antomarioni, FE Ciarapica, ID Sanctis, J Ordieres-Meré International Journal of Management and Decision Making 18 (2), 151-182, 2019 | 7 | 2019 |
