Research Progress on ultra-precision machining technology
It becomes more and more emphasizing that micro-milling is widely used in the micro and ultra-precision device machining, due to the unique advantages with various materials and complex 3D curved surface processing. However, in the micro machining the tool wears rapidly, and it affects the machining accuracy and quality of parts directly. Meanwhile, serious wear will cause cutting vibration, damaging the machine and workpiece. Thus, tool wear has been one of the most important factors that restrict the development and application of the ultra-precision micro-milling technology.
Recently, Dr. Zhu Kunpeng together with his colleagues from Institute of Advanced Manufacturing Technology, Hefei Institute of Physical Science, Chinese Academy of Science, has put forward a new kind of theory about tool wear criterion and a method about rapid on-line detection. The method determines the micro-milling tool conditions by the singularity of waveform of cutting force. It is found robust to the noise and not affected by working condition variations. This method extends the idea of tool condition monitoring, realizing on-line monitoring on the tool breakage and wear with universality and practicality, and providing theory technique fundamental on the on-line monitoring of machining status, intelligent compensation of tool wear , and process control and optimization of ultra-precision milling.
This research results focuses on the topic “Online Condition Monitoring in Micro-Milling: A Force Waveform Shape Analysis Approach”, published in IEEE Transactions on Industrial Electronics, volume 6, 2015. IEEE Transactions on Industrial Electronics is one of the renowned international journals in industrial automation field, which impact factor is 6.50. The research work is supported by the 100 Talents Program of Chinese Academy of Sciences and National Natural Science Foundation of China.
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7010911
More related research of the author can be found at:
http://link.springer.com/article/10.1007/s00170-013-5258-5
