Energy Efficiency in Machine Tools - A Self-Learning Approach

被引:8
|
作者
Di Orio, Giovanni [1 ]
Candido, Goncalo [1 ]
Barata, Jose [1 ]
Bittencourt, Jose Luiz [2 ]
Bonefeld, Ralf [3 ]
机构
[1] Univ Nova Lisboa, FCT, Dep Eng Electrotecn, CTS UNINOVA, P-2829516 Caparica, Portugal
[2] FCT, BR-22250 Rio De Janeiro, Brazil
[3] Bosch Rexroth AG, D-97816 Mainz, Germany
关键词
Machine Tool; Energy Efficiency; Data Mining; Context Awareness; Service Oriented Architecture;
D O I
10.1109/SMC.2013.830
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the growing demand to reduce the environmental impact, the manufacturing companies of today are encouraged to adopt new green methodologies, strategies and technologies for increasing the energy efficiency of their manufacturing production lines. These solutions have a great impact on several productivity metrics including availability and costs. The continuous pursuit of productivity and particularly of machine availability has led to an increase of the total energy consumption in production plants. However, productivity gains can also be achieved by reducing the life- cycle costs of the manufacturing production systems. The research currently done under the scope of Self- Learning Production Systems (SLPS) tries to fill the gap between availability and efficiency by providing an innovative and integrated approach for ensuring the efficient utilization of the resources in machine tools.
引用
收藏
页码:4878 / 4883
页数:6
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