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International Journal of Computer Integrated Manufacturing Volume 31, 2018 - Issue 4-5: Smart Energy Efficient Manufacturing
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Original Articles

A hybrid approach to energy-efficient machining for milled components via STEP-NC

Honghui WangSchool of Mechanical Engineering, Shandong University, Jinan, P. R. China;Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, Shandong University, Jinan, P.R. ChinaView further author information
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Xun XuDepartment of Mechanical Engineering, School of Engineering, University of Auckland, Auckland, New ZealandView further author information
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Chengrui ZhangSchool of Mechanical Engineering, Shandong University, Jinan, P. R. China;Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, Shandong University, Jinan, P.R. ChinaCorrespondence[email protected]
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&
Tianliang HuSchool of Mechanical Engineering, Shandong University, Jinan, P. R. China;Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, Shandong University, Jinan, P.R. ChinaView further author information
Pages 442-456 | Received 06 Sep 2016, Accepted 14 Apr 2017, Published online: 08 May 2017

Citations (13)

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Xiaoyang Zhu & Yangjian Ji. (2023) A digital twin-based multi-objective optimization method for technical schemes in process industry. International Journal of Computer Integrated Manufacturing 36:3, pages 443-468.
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Articles from other publishers (12)

Hongyan Chu, Ke Dong, Jun Yan, Zhuoran Li, Zhifeng Liu, Qiang Cheng & Caixia Zhang. (2023) Flexible process planning based on predictive models for machining time and energy consumption. The International Journal of Advanced Manufacturing Technology 128:3-4, pages 1763-1780.
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S Borojević, B Sredanović, M Milošević, M Sekulić & S Janković. (2023) Energy efficiency of the Process Planning Design in the scope of Industry 4.0. Journal of Physics: Conference Series 2540:1, pages 012013.
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Kang Cheng, Gang Zhao, Wei Wang & Yazui Liu. (2022) An estimation methodology of energy consumption for the intelligent CNC machining using STEP-NC. The International Journal of Advanced Manufacturing Technology 123:1-2, pages 627-644.
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Xianli Liu, Linhao Han, Shi Wu, Yue Meng, Caixu Yue & Steven Y. Liang. (2022) Influence of blade curvature characteristics on energy consumption in machining process. The International Journal of Advanced Manufacturing Technology 121:3-4, pages 1867-1885.
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Gang Zhao, Kang Cheng, Wei Wang, Yazui Liu & Zhihua Dan. (2022) A milling cutting tool selection method for machining features considering energy consumption in the STEP-NC framework. The International Journal of Advanced Manufacturing Technology 120:5-6, pages 3963-3981.
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Yan He, Xiaocheng Tian, Yufeng Li, Yulin Wang, Yan Wang & Shilong Wang. (2022) Modeling and analyses of energy consumption for machining features with flexible machining configurations. Journal of Manufacturing Systems 62, pages 463-476.
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Yu Zhang, Xian Yu, Jian Sun, Yongsheng Zhang, Xun Xu & Yadong Gong. (2022) Intelligent STEP-NC-compliant setup planning method. Journal of Manufacturing Systems 62, pages 62-75.
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Alvaro Luis Fraga, Marcela Vegetti & Horacio Pascual Leone. (2020) Ontology-based solutions for interoperability among product lifecycle management systems: A systematic literature review. Journal of Industrial Information Integration 20, pages 100176.
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Nitesh Sihag & Kuldip Singh Sangwan. (2020) A systematic literature review on machine tool energy consumption. Journal of Cleaner Production 275, pages 123125.
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Honghui Wang, Ray Y. Zhong, Guijie Liu, WeiLei Mu, Xiaojie Tian & Dingxin Leng. (2019) An optimization model for energy-efficient machining for sustainable production. Journal of Cleaner Production 232, pages 1121-1133.
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Honghui Wang, Guijie Liu, Qingli Zhang & WeiLei Mu. (2019) Developing an energy-efficient process planning system for prismatic parts via STEP-NC. The International Journal of Advanced Manufacturing Technology 103:9-12, pages 3557-3573.
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Theofanis P. Raptis, Andrea Passarella & Marco Conti. (2019) Data Management in Industry 4.0: State of the Art and Open Challenges. IEEE Access 7, pages 97052-97093.
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