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AI Based Modelling and Optimization of Turning Process     AI  ANN  Turning machining  PSO       font style='font-size:12px;'> 2015/1/12
In this thesis, Artificial Neural Network (ANN) technique is used to model and simulate the Turning Process. Significant machining parameters (i.e. spindle speed, feed rate, and, depths of cut) and pr...
The tuned mass damper(TMD) has been successfully applied to the vibration control in machining, while the most widely adopted tuning is equal peaks, which splits the magnitude of the frequency respons...
Due to the extensive use of highly automated machine tools in the industry, manufacturing requires reliable models for the prediction of output performance of machining processes. The prediction of su...
This paper presents machining parameters (turning process) optimization based on the use of artificial intelligence. To obtain greater efficiency and productivity of the machine tool, optimal cutting ...
Among the most important data produced and stored is product data. CAD data forms one of many contributors to product data. Although in most circumstances CAD data can be processed within the CIM env...
Surface roughness, an indicator of surface quality, is one of the most specified customer requirements in machining of parts. In this study, the experimental results corresponding to the effects of di...
分析了最小量润滑(MQL)切削中供液方位、供液距离等因素对切削液渗透能力的影响。在SB-CNC超精密数控机床上进行了MQL车削45号钢试验,通过对切削力、表面粗糙度和切屑形态的研究表明:喷嘴位于主后刀面且距刀尖20mm处供应较大量的切削液能达到良好的切削效果。
Purpose: This paper aims to study the cutting parameters influence (cutting speed, feed rate, cutting depth and tool radius nose) on the cutting forces (cutting force, feed rate cutting force and pene...
Purpose: A multi-scale model is proposed to explain the effect of material induced vibration and the quantitative relation between cutting force and the surface quality from dislocations, grain orient...

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