Pulsed Magnetic Field Treatment of TiAlSiN Coated Milling Tools For Improved Cutting Performances

In this study a pulsed magnetic treatment was attempted to improve the cutting performance of the TiAlSiN coated WC-12wt%Co cemented carbide end mills and the effects of the strength of the pulsed magnetic field on the cutting forces, the cutting vibrations, the tool wear, the machined surface roughness and mechanical properties were investigated. It is found that the cutting performances of the coated tools are successfully improved with a relatively lower cutting force and less wear area. The average resultant cutting force Fxyave decrease by 14.53% in the last machining process when the optimum processing parameters of 0.5T magnetic field is used, accompanying a maximum decrease of 46.8% in the cutting vibration. The maximum reductions of 57.65% and 25.4% in the flank wear and the average surface roughness of the workpiece are obtained respectively after the treatment. Both the hardness and toughness of the cemented carbides are slightly improved with the imposition of the field. The improvements in the cutting performance of the tool are attributed to the enhanced adhesion strength between the coating and matrix, which is caused by the increased compressive residual stress induced by the PMT.

Investigation of Gas Nitriding Effect on Damping Ratio of Steel 1.7225 and Cutting Vibration of Indexable End Mill Made from It During the Straight Groove

End-milling is a cutting technology that removes material from machined workpieces by end mill and is widely used to manufacture parts. Moreover, this process is prone to vibration due to low stiffness. Also, nitriding is a surface hardening process with lots of effects on mechanical properties. This study investigated the effect of gas nitriding on a nitrided end mill in comparison with an unnitrided end mill and showed significant improvement in vibration peak and RMS during end milling. To clarify the reason for this improvement this article carried out a modal test to show how nitriding affected the natural frequency and damping ratio of the nitrided and unnitrided samples and showed that tool rigidity remained the same while damping ratio increased so we claimed nitriding improved damping ratio without change of tool rigidity. For verifying this claim we modeled, meshed, and analyzed for obtaining tool natural frequency both for nitrided and unnitrided tool and compared with extracted natural frequencies from each tool FFT diagram during straight grooving. We showed that the natural frequencies were the same with less than 3 percent change so we concluded that nitriding led to better tool performance by increasing the damping ratio without any significant change in the tool stiffness.

Integrated Design of Spindle Speed Modulation and Cutting Vibration Suppression Controls Using Disturbance Observer for Thread Milling

In thread milling, there exists a trade-off between thread manufacturing efficiency and thread quality. In this study, an integrated design of spindle speed modulation (SSM) and cutting vibration suppression (CVS) controls using a disturbance observer were developed to simultaneously ensure superior quality and high manufacturing efficiency. The proposed integrated design not only controls the cutting torque while suppressing cutting vibrations but also ensures cost-effectiveness and mitigates the installation problems prevalent in existing sensor-based methods. The SSM control uses a disturbance observer to estimate the cutting torque required on the spindle during thread milling. The estimated cutting torque is used as a feedback signal so that the SSM control can modulate the spindle speed to make the cutting torque achieve a preset torque command. To further avoid cutting vibrations in thread milling, the CVS control analyzes the estimated cutting torque, detects the occurrence of cutting vibrations, and then adjusts the torque command of the SSM control to suppress the cutting vibrations. In this study, thread milling experiments were performed on a computer numerical control milling machine using the workpiece with stacked materials. The feasibility and performance of the proposed integrated design were validated by experiments.

A Predictive Model of Dimensional Deviation Based on Regeneration PSO-SVR with Cutting Feature Weight in Milling

Support vector regression (SVR) optimized by particle swarm optimization (PSO) has low predictive accuracy and premature convergence in milling. To solve this problem, A PSO-SVR model combined with the cutting feature weight was proposed in this paper. Firstly, basing on the SVR, the feature weight was integrated with the kernel function, and added the premature judging to the PSO to improve the global searching ability. Secondly, the mathematical model composed of the cutting force, temperature and cutting vibration was built based on the datasets obtained by experiment. The covariance was calculated to get the characteristic weights of process parameters, which promoted the incremental data in turn. Finally, the predictive model of the dimensional deviation was established based on the promoted PSO-SVR and the result was compared with the general PSO-SVR. The accuracy of the predictive model reached 97.5%. And compared with the predictive model of the general PSO-SVR without feature weighting, the dimensional deviation predictive accuracy and generalization ability of the regeneration PSO-SVR predictive model with feature weighting was improved by 37.75% and 24.5%.

Application of Bispectrum Diagonal Slice Feature Analysis in Tool Wear States Monitoring

Tool wear is unavoidable during machining, which is one of the most common tool failure modes. It is significant to evaluate the tool state quickly and effectively for timely tool change strategy. The cutting vibration signals after tool wear show strong non-Gaussian characteristics. Higher order spectrum is a powerful tool for analyzing the non-Gaussian characteristics of signals, and can restrain noise and provide more information than classical power spectrum analysis. This paper presents a milling tool wear state monitoring method based on higher order spectrum entropy. Due to the large amount of calculation of bispectrum, bispectrum diagonal slice is investigated. And the diagonal slice spectral entropy is proposed as tool wear indicator to monitor tool state. To verify the proposed method, cutting vibration signal of CNC machining center were collected and analyzed. The experimental results showed that the proposed approach can effectively monitor and diagnose the tool state, and has good robustness. It is feasible and effective for on-line monitoring milling tool wear.

Full coverage cutting path planning of robotized roadheader to improve cutting stability of the coal lane cross-section containing gangue

The purpose of this work is to improve the cutting stability of robotized roadheader through the full coverage cutting path planning of the coal lane cross-section containing gangue. Cutting gangue will bring serious pick wear and severe vibration, which will reduce the service life of robotized roadheader. Therefore, the strategy that avoiding the gangue and cutting the remaining coal-rock was recommended. Firstly, the environment grid map of the cross-section containing gangue was established and the grid attribute was assigned. To describe the arbitrary position of gangue, a random generation method was developed. On this basis, the combination of biologically inspired neural network (BINN) and floating template method was proposed to overcome the shortcomings of traditional BINN and the full coverage cutting path planning simulation was carried out. The simulation shows a better result that the average repetition rate is approximately 10% under the condition that the cutting coverage rate is more than 95%. Finally, the cutting experiment of the coal-rock sample containing gangue on the robotized roadheader cutting platform was performed. Based on the infrared thermography and cutting signal obtained by the previous round cutting, the cutting path of the second round was planned and the cutting experiment was conducted. The experiment results show that the cutting temperature rise and the cutting vibration of the second round cutting can be effectively reduced by approximately 60% and 90%, which demonstrated that the cutting stability of the cross-section containing gangue can be effectively improved by the cutting path planning strategy of avoiding gangue.

Cutting Performance of Austenitic and Duplex Stainless Steels with Drills of Three Cutting Edges

Austenitic and duplex stainless steels are considered be the best in corrosion resistance among different grades of stainless steels. Due to high strength, duplex stainless steels applications are increasingly as an alternative to the austenitic stainless steels. In this sense, the machining study of this materials is an important issue, in order to better understand the performance of the tools and the quality of the parts manufactured for high-demand industries. In this research, the machinability of both stainless steels was evaluated in the drilling operation, using drills with three cutting edges. This type of drill geometry is particularly useful when conventional solid carbide drills fail. The drill point of triple edge is very stable, demonstrating optimal positioning accuracy and better performance in deep bores. Using the same tool geometry, a comparative analysis of drilling performance on austenitic and duplex stainless steels was made. In experimental procedure, external low-pressure cooling or internal high-pressure cooling was applied alternatively. The cutting vibration, the tool wear, the roughness and the hole diameter accuracy were evaluated in the series of holes made. The obtained results show that the most important factor to increase the number of holes made is the use of high-pressure internal cooling. When external cooling is used, AISI 304 have a worse behaviour than duplex stainless steel, due to greater susceptibility to built-up-edge formation and work hardening. The tool deterioration is mainly non-uniform chipping for external cooling and flank wear for internal cooling.

Experimental Study on Coupling Characteristics of Cutting Heat and Cutting Vibration Under Different Tool Wear States

The thermo-mechanical-vibration coupling characteristics of turning system has always been an important research topic in the field of machining, and the material, states and performance of cutting tools will directly affect this coupling characteristics. In this paper, a synchronous testing system for cutting temperature and cutting vibration is built to collect the cutting temperature and cutting vibration near the tip of three worn tools D1 (new blade), D2 (moderately worn blade) and D3 (severely worn blade). Based on the test data and the grey correlation theory, the coupling characteristics of cutting temperature rise and cutting vibration of tools in different wear states are analyzed. Based on the experimental data and least square method, (1) the regression model of cutting temperature rise about cutting vibration and cutting parameters (2) the regression model of cutting vibration about cutting temperature rise and cutting parameters have been established respectively. The undetermined parameters and correlation coefficients are obtained by MATLAB software programming. The research show that the coupling of cutting heat and cutting vibration of tools D1 and D2 is one-way coupling, that is, cutting vibration significantly affects cutting heat, but cutting heat has little effect on cutting vibration, while the coupling of cutting heat and cutting vibration of tool D3 is a bidirectional coupling.