Litcius/Paper detail

Cutting Energy Consumption Modelling of End Milling Cutter Coated with AlTiCrN

Yue Meng, Xinsheng Sun, Shengming Dong, Yue Wang, Xianli Liu

2023Coatings8 citationsDOIOpen Access PDF

Abstract

As an indispensable piece of equipment in the manufacturing industry, the machine tool is low-energy-efficiency and high-energy-consumption in operation. Therefore, it is urgent to establish a cutting energy consumption model to guide production and reduce the energy consumption of the machining process. In this paper, the AlTiCrN-coated cutting tool is taken as the object of study, and the cutting energy consumption model is established. The cutting energy consumption model is composed of a machining time model and a cutting power model. The cutting power model can be divided into the shear deformation power model of the workpiece, the friction power model of the flank surface and the friction power model of the rake surface. The influence of the edge shape is taken into account in the establishment of the friction power model of the flank surface. The machining time model considering the S-type acceleration and deceleration stage is established. The accuracy of the model was verified by experiments. Experimental results show that the model has high accuracy. The Taguchi method was used to carry out the numerical experiment with the cutting energy consumption of the machine tool as the response. The influences of cutting parameters on energy consumption are analyzed. Cutting width is the most important factor, followed by cutting depth, then feed rate and spindle speed. The physical principle of the influence of cutting parameters on cutting energy consumption is revealed.

Topics & Concepts

MachiningEnergy consumptionRake angleEnhanced Data Rates for GSM EvolutionMechanical engineeringPower (physics)Taguchi methodsMachine toolAccelerationEnergy (signal processing)Cutting toolEngineeringAutomotive engineeringComputer scienceMachine learningTelecommunicationsQuantum mechanicsClassical mechanicsPhysicsStatisticsElectrical engineeringMathematicsAdvanced machining processes and optimizationAdvanced Machining and Optimization TechniquesEnergy Efficiency and Management