On the Exploitation of Automated Planning for Reducing Machine Tools Energy Consumption Between Manufacturing Operations

被引:0
|
作者
Parkinson, Simon [1 ]
Longstaff, Andrew [1 ]
Fletcher, Simon [1 ]
Vallati, Mauro [1 ]
Chrpa, Lukas [2 ,3 ]
机构
[1] Univ Huddersfield, Huddersfield, W Yorkshire, England
[2] Czech Tech Univ, Prague, Czech Republic
[3] Charles Univ Prague, Prague, Czech Republic
关键词
OPTIMIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
DThere has recently been an increased emphasis on reducing energy consumption in manufacturing, driven by the fluctuations in energy costs and the growing importance given to environmental impact of manufactured goods. Lots of attention has been given to the reduction of machine tools energy consumption, as they require large amounts of energy to perform manufacturing tasks. One area that has received relatively little interest, yet could harness great potential, is reducing energy consumption by planning machine activities between manufacturing operations, while the machine is not in use. The intuitive option - which is currently exploited in manufacturing- is to leave the machine in a normal operating state in anticipation of the next manufacturing job. However, this is far from optimal due to the thermal deformation phenomenon, which usually require an energy-intensive warm-up cycle in order to bring all the components (e.g. spindle motor) into a suitable (stable) state for actual machining. Evidently, the use of this strategy comes with the associated commercial and environmental repercussions. In this paper, we investigate the exploitability of automated planning techniques for planning machine activities between manufacturing operations. We present a PDDL 2.2 formulation of the task that considers energy consumption, thermal deformation, and accuracy. We then demonstrate the effectiveness of the proposed approach using a case study which considers real-world data.
引用
收藏
页码:400 / 408
页数:9
相关论文
共 50 条
  • [31] Enabling cognitive manufacturing through automated on-machine measurement planning and feedback
    Zhao, Yaoyao Fiona
    Xu, Xun
    [J]. ADVANCED ENGINEERING INFORMATICS, 2010, 24 (03) : 269 - 284
  • [32] Energy-efficient manufacturing on machine tools by machining process improvement
    Fujishima, Makoto
    Mori, Masahiko
    Oda, Yohei
    [J]. PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT, 2014, 8 (1-2): : 217 - 224
  • [33] Analyzing information flow collected across planning and execution stages of machine tools operations
    Industrial Cyber-Physical Systems Research Center, National Institute of Advanced Industrial Science and Technology, Japan
    [J]. Int. Conf. Lead. Edge Manuf. Technol. Century, LEM, 1600, (585-588):
  • [34] Analysis of the integration between operations management manufacturing tools with discrete event simulation
    Ferro R.
    Ordóñez R.E.C.
    Anholon R.
    [J]. Production Engineering, 2017, 11 (4-5) : 467 - 476
  • [35] Experimental study on energy consumption of computer numerical control machine tools
    Lv, Jingxiang
    Tang, Renzhong
    Jia, Shun
    Liu, Ying
    [J]. JOURNAL OF CLEANER PRODUCTION, 2016, 112 : 3864 - 3874
  • [36] Electrical energy consumption of CNC machine tools based on empirical modeling
    Zhipeng Jiang
    Dong Gao
    Yong Lu
    Linghao Kong
    Zhendong Shang
    [J]. The International Journal of Advanced Manufacturing Technology, 2019, 100 : 2255 - 2267
  • [37] Approach to forecast energy consumption of machine tools within the design phase
    Doreth, Karl
    Henjes, Jan
    Kroening, Stefan
    [J]. WGP CONGRESS 2013: PROGRESS IN PRODUCTION ENGINEERING, 2013, 769 : 278 - 284
  • [38] Review on Design Research in CNC Machine Tools Based on Energy Consumption
    Wu, Hongyi
    Wang, Xuanyi
    Deng, Xiaolei
    Shen, Hongyao
    Yao, Xinhua
    [J]. SUSTAINABILITY, 2024, 16 (02)
  • [39] Electrical energy consumption of CNC machine tools based on empirical modeling
    Jiang, Zhipeng
    Gao, Dong
    Lu, Yong
    Kong, Linghao
    Shang, Zhendong
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 100 (9-12): : 2255 - 2267
  • [40] Determination of the machine energy consumption profiles in the mass-customised manufacturing
    Cupek, Rafal
    Ziebinski, Adam
    Zonenberg, Dariusz
    Drewniak, Marek
    [J]. INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2018, 31 (06) : 537 - 561