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Enzo Morosini Frazzon
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2020 – today
- 2024
- [j13]Satie L. Takeda-Berger
, Enzo Morosini Frazzon
An inventory data-driven model for predictive-reactive production scheduling. Int. J. Prod. Res. 62(9): 3059-3083 (2024) - 2023
- [j12]Guilherme Luz Tortorella
Readiness of Brazilian Industrial Engineering postgraduate programs for Industry 4.0: A knowledge dimensions assessment. Comput. Appl. Eng. Educ. 31(3): 501-519 (2023) - [j11]Maurício Randolfo Flores da Silva
Integration of machine learning and simulation for dynamic rescheduling in truck appointment systems. Simul. Model. Pract. Theory 125: 102747 (2023) - 2022
- [j10]Iracyanne Retto Uhlmann
Hybrid flow shop rescheduling for contract manufacturing services. Int. J. Prod. Res. 60(3): 1069-1085 (2022) - 2021
- [j9]Marina Meireles Pereira
A data-driven approach to adaptive synchronization of demand and supply in omni-channel retail supply chains. Int. J. Inf. Manag. 57: 102165 (2021) - [j8]Enzo Morosini Frazzon
Intelligent methods and systems for decision-making support: Toward digital supply chain twins. Int. J. Inf. Manag. 57: 102281 (2021) - [j7]Filipe Marinho de Brito
Design Approach for Additive Manufacturing in Spare Part Supply Chains. IEEE Trans. Ind. Informatics 17(2): 757-765 (2021) - 2020
- [j6]Enzo Morosini Frazzon
Manufacturing networks in the era of digital production and operations: A socio-cyber-physical perspective. Annu. Rev. Control. 49: 288-294 (2020) - [j5]Yuri Triska
Proposition of a simulation-based method for port capacity assessment and expansion planning. Simul. Model. Pract. Theory 103: 102098 (2020) - [c22]Nicollas Luiz Schweitzer de Souza
Integrated Production and Maintenance Planning: A Systematic Literature Review. ICPR-Americas (1) 2020: 342-356 - [i1]Filipe Marinho de Brito, Gélson da Cruz Júnior, Enzo Morosini Frazzon, João Pedro Tavares Vieira Basto, Symone G. S. Alcalá:
Design Approach for Additive Manufacturing in Spare Part Supply Chains. CoRR abs/2011.10572 (2020)
2010 – 2019
- 2019
- [j4]Ian M. Cavalcante
A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing. Int. J. Inf. Manag. 49: 86-97 (2019) - [j3]Enzo Morosini Frazzon
Simulation-Based Analysis of Intelligent Maintenance Systems and Spare Parts Supply Chains Integration. J. Intell. Syst. 28(1): 31-42 (2019) - [c21]Isabela Maganha
Proposal of a Reconfigurability Index Using Analytic Network Process. IEEM 2019: 1310-1313 - [c20]Filipe Marinho de Brito, Gélson da Cruz Júnior, Enzo Morosini Frazzon
An Optimization Model for the Design of Additive Manufacturing Supply Chains. INDIN 2019: 881-885 - 2018
- [j2]Enzo Morosini Frazzon
Hybrid approach for the integrated scheduling of production and transport processes along supply chains. Int. J. Prod. Res. 56(5): 2019-2035 (2018) - [c19]Matheus Cardoso Pires, Enzo Morosini Frazzon
Collaborative Distributed Operational Planning for Spare Parts Supply Chains. LDIC 2018: 95-101 - [c18]Ricardo Pimentel, Pedro P. P. Santos, Apolo M. Carreirão Danielli, Enzo Morosini Frazzon
Towards an Adaptive Simulation-Based Optimization Framework for the Production Scheduling of Digital Industries. LDIC 2018: 257-263 - [c17]Ian M. Cavalcante
Cloud-Based Additive Manufacturing as a Strategy for Product Variety: A Simulation Study. SOHOMA 2018: 53-66 - 2017
- [c16]G. Avventuroso, Ruben Foresti
Production paradigms for additive manufacturing systems: A simulation-based analysis. ICE/ITMC 2017: 973-981 - [c15]Mirko Kück
Towards adaptive simulation-based optimization to select individual dispatching rules for production control. WSC 2017: 3852-3863 - 2016
- [c14]Matheus Cardoso Pires, Enzo Morosini Frazzon
A Communication Procedure Between Tactical and Operational Levels in Spare Parts Supply Chains. APMS 2016: 61-68 - [c13]Mirko Kück
Potential of data-driven simulation-based optimization for adaptive scheduling and control of dynamic manufacturing systems. WSC 2016: 2820-2831 - 2014
- [j1]Enzo Morosini Frazzon
Spare parts supply chains' operational planning using technical condition information from intelligent maintenance systems. Annu. Rev. Control. 38(1): 147-154 (2014) - [c12]Silvia S. C. Botelho
Including operator's skill and environment conditions in IMS. INDIN 2014: 295-300 - [c11]Enzo Morosini Frazzon
Simulation model concept for evaluating spare parts supply chain planning methods. INDIN 2014: 560-565 - [c10]Rafael Penna, Marcos Amaral, Danúbia Bueno Espíndola, Silvia S. C. Botelho
Visualization tool for cyber-physical maintenance systems. INDIN 2014: 566-571 - [c9]Eduardo Francisco Israel, Enzo Morosini Frazzon
Operational Supply Chain Planning Method for Integrating Spare Parts Supply Chains and Intelligent Maintenance Systems. LDIC 2014: 453-462 - [c8]Marcos Ronaldo Albertin, Heráclito Lopes Jaguaribe Pontes
Industrial Performance Assessment Through the Application of a Benchmarking and Monitoring System. LDIC 2014: 643-653 - 2012
- [c7]Willian Chaves Mates, Enzo Morosini Frazzon, Jens Hartmann, Sérgio Fernando Mayerle:
A Graph Model for the Integrated Scheduling of Intermodal Transport Operations in Global Supply Chains. LDIC 2012: 301-311 - [c6]Enzo Morosini Frazzon, Joarez Pintarelli, Thomas Makuschewitz, Bernd Scholz-Reiter
Simulation-Based Analysis of Integrated Production and Transport Logistics. LDIC 2012: 499-508 - [c5]Jens Hartmann, Thomas Makuschewitz, Enzo Morosini Frazzon
A Genetic Algorithm for the Integrated Scheduling of Production and Transport Systems. OR 2012: 533-539
2000 – 2009
- 2009
- [c4]Antonio G. N. Novaes, Enzo Morosini Frazzon
Dynamic Vehicle Routing in Over Congested Urban Areas. LDIC 2009: 49-58 - [c3]Enzo Morosini Frazzon
Converting Knowledge into Performance Within Global Production and Logistic Systems. LDIC 2009: 433-442 - [c2]Bernd Scholz-Reiter
Dynamic Scheduling of Production and Inter-Facilities Logistic Systems. LDIC 2009: 443-453 - 2007
- [c1]Bernd Scholz-Reiter
Sustainability and Effectiveness in Global Supply Chains: Toward an Approach Based on a Long-term Learning Process. LDIC 2007: 251-258
Coauthor Index
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last updated on 2024-07-08 21:30 CEST by the dblp team
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