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Li Yi
Li Yi
Digital Twin International Research Center, BUAA
在 buaa.edu.cn 的电子邮件经过验证
标题
引用次数
引用次数
年份
Modeling and implementation of a digital twin of material flows based on physics simulation
M Glatt, C Sinnwell, L Yi, S Donohoe, B Ravani, JC Aurich
Journal of Manufacturing Systems 58, 231-245, 2021
1262021
How to integrate additive manufacturing technologies into manufacturing systems successfully: A perspective from the commercial vehicle industry
L Yi, C Gläßner, JC Aurich
Journal of Manufacturing Systems 53, 195-211, 2019
1032019
An eco-design for additive manufacturing framework based on energy performance assessment
L Yi, M Glatt, P Sridhar, K de Payrebrune, BS Linke, B Ravani, JC Aurich
Additive Manufacturing 33, 101120, 2020
472020
Process monitoring of economic and environmental performance of a material extrusion printer using an augmented reality-based digital twin
L Yi, M Glatt, S Ehmsen, W Duan, JC Aurich
Additive Manufacturing 48, 102388, 2021
332021
A method for energy modeling and simulation implementation of machine tools of selective laser melting
L Yi, M Glatt, TYT Kuo, A Ji, B Ravani, JC Aurich
Journal of cleaner production 263, 121282, 2020
262020
Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems
J Mertes, D Lindenschmitt, M Amirrezai, N Tashakor, M Glatt, ...
Journal of Manufacturing Systems 64, 578-593, 2022
252022
An energy model of machine tools for selective laser melting
L Yi, N Krenkel, JC Aurich
Procedia Cirp 78, 67-72, 2018
242018
Development and validation of an energy simulation for a desktop additive manufacturing system
L Yi, B Ravani, JC Aurich
Additive manufacturing 32, 101021, 2020
232020
Technical product-service systems: analysis and reduction of the cumulative energy demand
MF Glatt, L Yi, G Mert, BS Linke, JC Aurich
Journal of Cleaner Production 206, 727-740, 2019
232019
A use case to implement machine learning for life time prediction of manufacturing tools
R Oberle, S Schorr, L Yi, M Glatt, D Bähre, JC Aurich
Procedia Cirp 93, 1484-1489, 2020
202020
Energy simulation of the fused deposition modeling process using machine learning approach
L Yi, C Gläßner, N Krenkel, JC Aurich
Procedia CIRP 86, 216-221, 2019
182019
A case study on the part optimization using eco-design for additive manufacturing based on energy performance assessment
L Yi, S Ehmsen, M Glatt, JC Aurich
Procedia CIRP 96, 91-96, 2021
142021
An integrated energy management system using double deep Q-learning and energy storage equipment to reduce energy cost in manufacturing under real-time pricing condition: A …
L Yi, P Langlotz, M Hussong, M Glatt, FJP Sousa, JC Aurich
CIRP Journal of Manufacturing Science and Technology 38, 844-860, 2022
122022
Concept of hybrid modeled digital twins and its application for an energy management of manufacturing systems
P Langlotz, M Klar, L Yi, M Hussong, FJP Sousa, JC Aurich
Procedia CIRP 112, 549-554, 2022
122022
A study on impact factors of the energy consumption of the fused deposition modeling process using two-level full factorial experiments
L Yi, T Chen, S Ehmsen, C Gläßner, JC Aurich
Procedia CIRP 93, 79-84, 2020
112020
Scalability investigation of Double Deep Q Learning for factory layout planning
M Klar, M Hussong, P Ruediger-Flore, L Yi, M Glatt, JC Aurich
Procedia CIRP 107, 161-166, 2022
92022
Modeling and software implementation of manufacturing costs in additive manufacturing
L Yi, S Ehmsen, M Glatt, JC Aurich
CIRP Journal of Manufacturing Science and Technology 33, 380-388, 2021
92021
Process chain analysis of directed energy deposition: energy flows and their influencing factors
S Ehmsen, L Yi, JC Aurich
Procedia CIRP 98, 607-612, 2021
92021
Development of a simulation tool for predicting energy consumption of selective laser melting by using MATLAB/Simulink
L Yi, B Ravani, JC Aurich
Procedia CIRP 81, 28-33, 2019
82019
Optical sensor-based process monitoring in additive manufacturing
L Yi, A Shokrani, R Bertolini, U Mutilba, MG Guerra, EG Loukaides, ...
Procedia CIRP 115, 107-112, 2022
72022
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