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Bo Li,Xitian Tian,Min Zhang 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.9 No.1
The natural energy crisis and the increasingly serious environmental problems have imposed all industries to reduce energy consumption. During milling process, selecting a correct cutting parameters can not only greatly improve production quality and processing efficiency, but also can reduce energy consumption, in addition, tool wear also has a great impact on them. Therefore, a milling power consumption model of CNC machine tools is established based on modern machining theory is established in this article, unlike traditional energy consumption models, our model takes full account of cutting conditions and tool wear. The surface roughness of parts is one of the important indicators to measure the machining quality of machine tools. Therefore, taking milling process as research object, a multi-objective cutting parameters optimization model that takes the machining surface roughness, material removal rate (MRR) and machining energy consumption as the optimization goals was established. Furthermore, an intelligent optimization algorithm was proposed based on improved Teaching–Learning- Based Optimization (TLBO) to solve the model under various limited milling conditions. Finally, comparing experimental results of optimized parameter and empirical parameters, it shows that goals of reducing energy consumption, improving productivity and machining quality can be achieved by optimizing cutting parameters.
Lu Li,Mingyi Zhang,Ying Liu,Xitian Zhang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2015 NANO Vol.10 No.5
BiOX ( X=Cl , Br, I) nanosheet arrays have been grown on the surface of carbon cloth as recycled photocatalysts. Photocatalytic tests display that the BiOCl/carbon cloth heterostructures possess a much higher degradation rate compared with BiOCl grown on a fluorine-doped tin oxide(FTO) planar substrate. The photocatalytic experimental results indicate that BiOCl/carbon cloth heterostructures show excellent cyclic properties.