A generic energy prediction model of machine tools using deep learning algorithms
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DOI: 10.1016/j.apenergy.2020.115402
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- Marta Daroń & Monika Górska, 2023. "Relationships between Selected Quality Tools and Energy Efficiency in Production Processes," Energies, MDPI, vol. 16(13), pages 1-20, June.
- Mukun Yuan & Jian Liu & Zheyuan Chen & Qingda Guo & Mingzhe Yuan & Jian Li & Guangping Yu, 2024. "Predicting Energy Consumption for Hybrid Energy Systems toward Sustainable Manufacturing: A Physics-Informed Approach Using Pi-MMoE," Sustainability, MDPI, vol. 16(17), pages 1-27, August.
- Alexander I. Balitskii & Andriy M. Syrotyuk & Maria R. Havrilyuk & Valentina O. Balitska & Valerii O. Kolesnikov & Ljubomyr M. Ivaskevych, 2023. "Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation," Energies, MDPI, vol. 16(23), pages 1-26, November.
- Jessica Walther & Matthias Weigold, 2021. "A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry," Energies, MDPI, vol. 14(4), pages 1-24, February.
- Jianhua Cao & Xuhui Xia & Lei Wang & Zelin Zhang & Xiang Liu, 2021. "A Novel CNC Milling Energy Consumption Prediction Method Based on Program Parsing and Parallel Neural Network," Sustainability, MDPI, vol. 13(24), pages 1-16, December.
- Meihang Zhang & Hua Zhang & Wei Yan & Zhigang Jiang & Shuo Zhu, 2023. "An Integrated Deep-Learning-Based Approach for Energy Consumption Prediction of Machining Systems," Sustainability, MDPI, vol. 15(7), pages 1-17, March.
- Chou, Jui-Sheng & Truong, Dinh-Nhat & Kuo, Ching-Chiun, 2021. "Imaging time-series with features to enable visual recognition of regional energy consumption by bio-inspired optimization of deep learning," Energy, Elsevier, vol. 224(C).
- Fath U Min Ullah & Noman Khan & Tanveer Hussain & Mi Young Lee & Sung Wook Baik, 2021. "Diving Deep into Short-Term Electricity Load Forecasting: Comparative Analysis and a Novel Framework," Mathematics, MDPI, vol. 9(6), pages 1-22, March.
- Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
- Hongyi Wu & Xuanyi Wang & Xiaolei Deng & Hongyao Shen & Xinhua Yao, 2024. "Review on Design Research in CNC Machine Tools Based on Energy Consumption," Sustainability, MDPI, vol. 16(2), pages 1-20, January.
- Li, Lei & Huang, Haihong & Zou, Xiang & Zhao, Fu & Li, Guishan & Liu, Zhifeng, 2021. "An energy-efficient service-oriented energy supplying system and control for multi-machine in the production line," Applied Energy, Elsevier, vol. 286(C).
- Tan, Daniel & Suvarna, Manu & Shee Tan, Yee & Li, Jie & Wang, Xiaonan, 2021. "A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing," Applied Energy, Elsevier, vol. 291(C).
- Wang, Jinling & Tian, Yebing & Hu, Xintao & Han, Jinguo & Liu, Bing, 2023. "Integrated assessment and optimization of dual environment and production drivers in grinding," Energy, Elsevier, vol. 272(C).
- do Carmo, Pedro R.X. & do Monte, João Victor L. & Filho, Assis T. de Oliveira & Freitas, Eduardo & Tigre, Matheus F.F.S.L. & Sadok, Djamel & Kelner, Judith, 2023. "A data-driven model for the optimization of energy consumption of an industrial production boiler in a fiber plant," Energy, Elsevier, vol. 284(C).
- Abdulgani Kahraman & Mehmed Kantardzic & Muhammet Mustafa Kahraman & Muhammed Kotan, 2021. "A Data-Driven Multi-Regime Approach for Predicting Energy Consumption," Energies, MDPI, vol. 14(20), pages 1-17, October.
- Oh, Jiyoung & Min, Daiki, 2024. "Prediction of energy consumption for manufacturing small and medium-sized enterprises (SMEs) considering industry characteristics," Energy, Elsevier, vol. 300(C).
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Keywords
Energy consumption; Machine tools; Deep learning; Data-driven; Energy consumption features;All these keywords.
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