Power Consumption Assessment of Machine Tool Feed Drive Units

被引:12
|
作者
Yoon, Hae-Sung [1 ]
Lee, Jang-Yeob [2 ]
Kim, Min-Soo [2 ]
Kim, Eunseob [2 ]
Shin, Yong-Jun [2 ]
Kim, Sung-Yong [2 ]
Min, Sangkee [3 ]
Ahn, Sung-Hoon [2 ,4 ]
机构
[1] Korea Aerosp Univ, Sch Aerosp & Mech Engn, 76 Hanggongdaehak Ro, Goyang 10540, Gyeonggi Provin, South Korea
[2] Seoul Natl Univ, Dept Mech & Aerosp Engn, 1 Gwanak Ro, Seoul 08826, South Korea
[3] Univ Wisconsin, Dept Mech Engn, 1513 Univ Ave, Madison, WI 53706 USA
[4] Seoul Natl Univ, Inst Adv Machines & Design, 1 Gwanak Ro, Seoul 08826, South Korea
基金
新加坡国家研究基金会;
关键词
Energy; Machine tool; Modeling; ENERGY-CONSUMPTION; PARAMETER OPTIMIZATION; MATERIAL REMOVAL; IMPACT;
D O I
10.1007/s40684-019-00063-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Numerous efforts have been made to assess and model the power consumption of machining process, which has led to many standards for energy labeling of machine tools. However, more investigation is required to improve the applicability of these standards because the energy patterns of machines vary widely with respect to the machine type, size, and configuration. Hence, it is aimed to develop a methodology to determine the power consumption characteristics of a wide variety of machine tools. This research focuses on the power consumption of feed drive units, which are largely varying components with respect to machine tool configurations. Two notable phenomena were observed during our experiments. First, the power consumption of an axis in the gravitational direction exhibited a different pattern from that along those of the other axes. Movement in the gravitational direction was investigated in more detail from the perspective of the machine tool configuration. Second, during multi-axis movement, no power correlation between different axes was confirmed. Regardless of the axis composition, no correlation was detected between the individual power consumption profiles of each axis. Elucidating the power consumption characteristics of feed drive units would contribute toward standardization and simplification of power measurement procedures.
引用
收藏
页码:455 / 464
页数:10
相关论文
共 50 条
  • [41] Implementation of drive mechanism to control worktable motion in planer machine tool
    Chelliah, Sivakumar
    Selvarani, A. Geetha
    Yogaraj, D.
    Tiwari, Piyush
    Vishwakarma, Bhaskar
    Sharma, Abhishek
    MATERIALS TODAY-PROCEEDINGS, 2022, 62 : 2347 - 2350
  • [42] INFLUENCE OF PARAMETERS OF MILLING PROCESS ON THE ENERGY CONSUMPTION OF THE MACHINE TOOL
    Borkowski, Wojciech
    Skoczynski, Waclaw
    Piorkowski, Pawel
    Jankowski, Tomasz
    Roszkowski, Andrzej
    Foremniak, Michal
    ADVANCES IN SCIENCE AND TECHNOLOGY-RESEARCH JOURNAL, 2018, 12 (03): : 24 - 31
  • [43] Power consumption and tool life models for the production process
    Garg, A.
    Lam, Jasmine Siu Lee
    Gao, L.
    JOURNAL OF CLEANER PRODUCTION, 2016, 131 : 754 - 764
  • [44] Cutting Process Consideration in Dynamic Models of Machine Tool Spindle Units
    Danylchenko, Yurii
    Storchak, Michael
    Danylchenko, Mariia
    Petryshyn, Andrii
    MACHINES, 2023, 11 (06)
  • [45] CONTROL OF HYBRID ELECTRIC-HYDRAULIC DRIVE FOR VERTICAL FEED AXES OF MACHINE TOOLS
    Fiala, S.
    Bubak, A.
    Novotny, L.
    MM SCIENCE JOURNAL, 2019, 2019 : 3228 - 3235
  • [46] Predicting Power Consumption Using Machine Learning Techniques
    Allal, Zaid
    Noura, Hassan
    Salman, Ola
    Vernier, Flavien
    20TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC 2024, 2024, : 1522 - 1527
  • [47] Energy, power and heat flow of the cooling and fluid systems in a cutting machine tool
    Weber, Juliane
    Weber, Juergen
    Shabi, Linart
    Lohse, Harald
    7TH HPC 2016 - CIRP CONFERENCE ON HIGH PERFORMANCE CUTTING, 2016, 46 : 99 - 102
  • [48] Analysis of power consumption in heterogeneous virtual machine environments
    Negru, Catalin
    Mocanu, Mariana
    Cristea, Valentin
    Sotiriadis, Stelios
    Bessis, Nik
    SOFT COMPUTING, 2017, 21 (16) : 4531 - 4542
  • [49] Deep learning analysis for energy consumption of shield tunneling machine drive system
    Elbaz, Khalid
    Yan, Tao
    Zhou, Annan
    Shen, Shui-Long
    TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2022, 123
  • [50] Experimental derivation of a condition monitoring test cycle for machine tool feed drives
    Maximilian Benker
    Sebastian Junker
    Johannes Ellinger
    Thomas Semm
    Michael F. Zaeh
    Production Engineering, 2022, 16 : 55 - 64