Research On Cutting Power Modeling And Cutting Parameters Optimization During Micro-Milling Process

Considering the large consumption of the limited energy caused by manufacturing industry and resources constraints around the world,“Low Carbon Manufacturing” becomes a current hot topic,and its core connotation refers to the conservation of the resource and energy.Modeling the energy consumption during machining process and optimizing the cutting parameters to reduce energy consumption are very important.As a combination of the advanced technologies such as numerical control machining,precision and ultra-precision machining,micro equipment monitoring,and cutting tool fabrication,etc.,micro-milling technology can be used to fabricate the micro parts and components with three dimensional complex structures required by aerospace and biomedicine fields,and it has some excellent advantages such as high machining accuracy and low energy.Due to the micro scale,tool wear during micro-milling process is more serious compared with traditional milling process,and it has a great influence on the cutting energy consumption.The author built a 3D finite element simulation model based on DEFORM to investigate the effects of the cutting parameters on tool wear condition during micro-milling process and realized the prediction of the micro tool flank wear condition.Considering the effect of tool wear,a micro-milling cutting power analytical model was developed.Based on LEM current sensor,transformer and Lab VIEW platform,an on-line power monitoring system for micro-milling machine tool main transmission system was constructed.Two multi-objective optimization models were developed respectively to determine the optimal combination of cutting parameters.One is to maximize materials removal rate(MRR)and minimize surface roughness simultaneously,and the other minimize special energy consumption(SEC)and surface roughness simultaneously in micro-milling process.The main contributions are as follows:First of all,a 3D simulation model for micro-milling process was built based on the software DEFORM,and the influence of feed per tooth on tool wear was studied.A new tool wear prediction method for micro-milling process was presented based on the developed 3D simulation model,and its accuracy was verified by the experimental results.Secondly,based on our preliminary three-dimensional dynamic cutting forces prediction model,a modified micro-milling cutting forces analytical model was presented considering the tool flank wear effect.The experimental results verified that the modified model could predict the micro-milling cutting forces more accurately.Furthermore,the cutting power analytical model for micro-milling process was developed based on the relationship between the cutting power and the cutting force.Thirdly,an on-line power monitoring system for micro-milling machine tool main transmission system was constructed based on Lab VIEW platform.The comparison between the experimental and theoretical results of the idle power and cutting power of the micro-milling machine tool’s main transmission system verified the validity of the built system.Finally,some experiments of micro-milling were conducted.The multi-objective optimization problem was solved to determine the optimal cutting parameters which maximize materials removal rate(MRR)and minimize surface roughness simultaneously by the Genetic Algorithm(GA).The Taguchi-based grey relational analysis was applied to determine the optimal cutting parameters which minimize special energy consumption(SEC)and surface roughness simultaneously in micro-milling process.The study could provide a reference for the optimization of cutting parameters during micro-milling process.