Prediction of CNC Machine Tool Cutting Energy Consumption by BP Neural Network

• DOI: 10.6567/iftomm.14th.wc.os20.005
• Publication Date: 2015-11-11
• Authors: Shujie Sun; Tongda Wu; C. H. Yang; Yu Jian Cheng; C.-H. Kuo
• Keywords: Machine tool

The international machine tool producer is toward green production. high-efficiency, low pollution, energy consumption, recovery and reuse of resources are developed tools expected to be included in the consumption restrain. By this trend, a study prediction cutting proposed. Spindle rotation velocity, feed rate, depth machining modeled as input parameters corresponding output parameter. relationship between established based on BP neural network. From results, average error network measured value 1.8% for trained data set 4.9% untrained set. These two small errors show great capability function mapping spindle consumption.