5-axis CNC Machine Research Articles

Post-processing algorithm of five-axis CNC machine tool under rotation angle optimization

During the operation of 5-axis CNC machine tools, the angle deviation of the rotation axis greatly affects the tool path control. Therefore, a post-processing algorithm of five-axis CNC machine tool with optimized rotation angle was proposed. Firstly, the basic The structure of the machine tool was analyzed, the Hausdoff distance was used to obtain the matching error between the actual machined surface and the difference surface, and the error compensation method was used to compensate the obtained error, and the rotation axis angle of the machine tool was completed according to the processing result. Based on the optimization results, the machine tool coordinate system was established, and the machine tool post-processor was developed through the coordinate transformation results and integrated into the relevant software to realize the post-processing of the machine tool. The experimental results show that the proposed method achieves better processing results when used for post processing of machine tools.

Optimum error design and 5-axis CNC machining of preloaded roller-gear-cam in roller-drive system

Roller-gear-cam (RG-cam) drive systems in machine tool rotary tables provide enhanced rotation accuracy and superior transmission efficiency due to their preloaded design. However, achieving a controllable preload engagement between the roller and RG-cam requires the use of 5-axis CNC machining using a non-formed tool, which inevitably introduces machining errors. Accordingly, this study proposes a comprehensive method for the design, analysis, and manufacture of a precision RG-cam system on a conventional 5-axis CNC machine tool. Notably, the proposed method enables the machining errors to be controlled and minimized. The feasibility of the proposed approach is demonstrated by machining a prototype roller-drive system on a 5-axis CNC machine. The accuracy of the machined RG-cam is evaluated in accordance with the ISO 230-2 standard. It is shown that the forward and reverse rotational errors of the RG-cam over a single revolution are less than 10 s.

Develop a postprocessor for 5-axis CNC machines head-table type and head-head type based on determining coordinate transformation matrices

Develop a postprocessor for 5-axis CNC machines head-table type and head-head type based on determining coordinate transformation matrices

Accurate Detection and Smoothness-Oriented Avoidance Method of Singularity in 5-Axis CNC Machining

As an inherent flaw in the kinematic chain mechanism of 5-axis machine tools, singularity can induce dramatic changes in machine axes motion and unfavorable fluctuations in feedrate. For effective singularity avoidance, it is desirable to first achieve accurate and efficient singularity detection and then eliminate the singularity without impairing tool orientation smoothness. This paper presents a novel approach for accurately detecting and smoothly avoiding the singularity in 5-axis CNC machining. In the detection method, two exclusion criteria are presented to efficiently exclude most non-singular segments of the tool orientation spline, and a curve intersection-based algorithm is thus developed to accurately identify the singular segments. In the singularity avoidance method, a concept of admissible tool orientation annulus (ATOA) is introduced, which serves to confine the range and magnitude of the tool orientation spline’s adjustments, and a local adjustment algorithm is then developed to enable the escape of the tool orientation from the singular region with controllable direction and deviation, while maintaining its continuity and smoothness. The effectiveness of singularity avoidance and the kinematic performance of the tool orientation modified by our method, are comparable to a state-of-the-art singularity avoidance algorithm. Finally, the conducted experiments validate the proposed method.

MINIMIZATION OF DEFLECTION ERROR IN FIVE AXIS MILLING OF IMPELLER BLADES

The 5-axis CNC machine tools are used for manufacturing free form surfaces of sophisticated parts such as turbine blades, airfoils, impellers, and aircraft components. The virtual machining systems can be used in order to analyze and modify the 5-axis CNC machine tools operations. Cutting forces and cutting temperatures induce deflection errors in thin-walled structures such as impeller blades through machining operations. Thin-walled impeller blades' flexibility can result in machining errors such as overcutting or undercutting. So, decreasing the deflection error during machining operations of impeller blades can achieve the desired accuracy in produced parts. Optimized machining parameters can be obtained to minimize the deflection of machined impeller blades. In terms of precision and efficiency enhancement in component production processes, a virtual machining system is developed to predict and minimize deflection errors of 5-axis milling operations of impeller blades. The deflection error in machined impeller blades is calculated by using finite element analysis. The optimization methodology based on the genetic algorithm is applied to minimize the deflection error of impeller blades in machining operations. To validate the integrated virtual machining system in the study, the impeller is milled by using a 5-axis CNC machine tool. The CMM machine is used in order to measure and analyze deflection error in the machined impeller blades. As a result, by using the developed virtual machining system in the study, accuracy and efficiency in 5-axis milling operations of impellers can be increased.

Deformation error compensation in 5-Axis milling operations of turbine blades

The precision and performance of machined flexible parts are under influence of deformation errors during end milling operations. Thus, prediction and compensation of deformation errors during milling operations of flexible parts can provide a key tool in accuracy enhancement of part production. In this study, an improved virtual machining system is proposed in order to assess and compensate deformation errors caused by cutting temperature and forces in 5-axis milling operations of flexible parts. The improved Johnson–Cook model is utilized to investigate the cumulative impact of strain rate and deformation temperatures on flow stress during milling operations of turbine blade. To estimate deformation errors caused by cutting forces and temperature on the workpiece and cutting tool, the finite element analysis is then applied. As a result, volumetric vectors of deformation error at each cutting location along the machining pathways are then generated in order to be compensated within new compensated machining tool paths. Thus, the deformation error created by cutting forces and temperature on the workpiece and cutting tool are compensated in order to enhance accuracy during 5-axis milling operation of flexible turbine blades. Experiments are carried out using a 5-axis CNC machine tool and errors are quantified using a CMM to verify the developed strategy in the study. As a consequence, precision of machining operations on flexible turbine blades can be enhanced by employing the developed virtual machining system in the study.

Dimensional, geometrical, thermal and tool deflection errors compensation in 5-Axis CNC milling operations

ABSTRACT The dimensional, geometrical, thermal and tool deflection errors which have a big portion of the overall error of machined parts need more attention in precision of components produced by using CNC machine tools. As a result, it is essential to simulate and compensate the errors in the machined components in order to increase accuracy of machined parts. In order to simulate and analyse the real manufactured components in virtual environments, virtual machining systems are proposed. In this paper, application of virtual machining system is investigated in order to simulate and compensate dimensional, geometrical, thermal and tool deflection errors in 5-axis milling operations of free form surfaces. The volumetric error vectors regarding the dimensional, geometrical, thermal and tool deflection errors at each cutting tool location throughout the machining pathways are calculated and compensated utilising the study’s created virtual machining technology. In order to validate the study, a sample workpiece free from surfaces is milled by using the 5-axis CNC machine tool. The machine part is then measured by suing the CMM machine in order to obtain the dimensional, geometrical, thermal and tool deflection errors during milling operations of free form surfaces. Thermal sensors are also installed to the different locations of CNC machine tool in order to measure the thermal error of CNC machine tool during machining operations. Finally, in order to improve accuracy in 5-axis milling operations of free form surfaces, new cutting tool paths regarding the compensated volumetric errors of dimensional, geometrical, thermal, and tool deflection errors are generated. As a result, by utilising the proposed virtual machining system in the research work, precision as well as reliability during 5-axis milling operations of free form surfaces can be enhanced.

Multiple criterion optimization in milling of AISI H11 mold steel under MQL condition

In this investigation, the method of minimum quantity lubrication (MQL) is utilized in the procedure of finishing milling of AISI H11 steel instead of the conventional lubrication method. The variants are three three-level experimental cutting parameters, including [Formula: see text]-cutting speed, [Formula: see text]-feed per tooth, and [Formula: see text]-depth of cut. The responses are production rate (MRR, in mm3/min), cutting force ([Formula: see text], in N), and surface roughness ([Formula: see text], in [Formula: see text]m). The purpose of this study is to generate the mathematical regression models for the responses ([Formula: see text], [Formula: see text], and MRR), and solve the multi-objective optimization problem to estimate the appropriate input parameters respecting the defined criteria for [Formula: see text], [Formula: see text], and MRR. Experimental research was conducted with an experimental matrix designed by Box–Behnken Design (BBD). The experimental runs were executed on a 5-axis CNC machine tool, model DMU50. The desirability function (DF) method is used to resolve the problem of multi-attribute optimization. The results show that the optimum process variables include [Formula: see text] m/min, [Formula: see text] mm/tooth, [Formula: see text] mm, corresponding to [Formula: see text]m, [Formula: see text] N, and [Formula: see text] mm3/min.

Investigations on the causes of process vibrations in CNC grinding processes and their effects on achievable surface qualities on fused silica

The presented investigations build on the results already presented at EOSAM 2022 on the in-situ monitoring of grinding processes, in which high correlations between vibrometry, force and topography data of machined fused silica samples could already be proven. With the help of new measurement setups, it was possible to also detect high-frequency vibration components in CNC grinding processes and to check their effects on the resulting surface qualities. The investigations were carried out on a 5-axis CNC machine and monitored with the help of vibrometric and white-light interferometric measurement technology. The aim was to look at the influences of process-side parameters on the process vibrations and the resulting surface qualities.

Development of technological process of metal machining from stamping on 5-axis CNC milling machine

The technological process of compressor working blade production from stamping with minimum allowance for machining of the working part, on 5-axis CNC machine aimed at reducing the units of machine equipment has been developed. The tooling for basing the working part of the blade on the principle of six-point basing adapted to the design of the machine tool is realised. The geometrical parameters of the obtained blade were analysed with its mathematical model by 3D scanning method.

State identification of a 5-axis ultra-precision CNC machine tool using energy consumption data assisted by multi-output densely connected 1D-CNN model

State identification of a 5-axis ultra-precision CNC machine tool using energy consumption data assisted by multi-output densely connected 1D-CNN model

Intelligent Operation Monitoring of an Ultra-Precision CNC Machine Tool Using Energy Data

Ultra-precision CNC machine tools play a significant role in the machining of precision dies and molds, optics, consumer electronics, etc., Due to the nature of ultra-precision machining, a subtle change in process condition, machine anomalies, etc. may significantly influence the machining outcome. Hence, continuous monitoring of the equipment’s operation is required to better understand the variations associated with the process and the machine. The conventional monitoring platform requires comprehensive data analysis using multiple sensors, and controller data to detect, diagnose, and prognose machine and process conditions. This increases the cost and complexity of installing a monitoring platform. The energy consumption data contains valuable information that could be potentially used to identify machine and process variations. The information can also be used to develop potential energy-saving strategies in an effort towards Green Manufacturing. This paper proposes an intelligent energy monitoring method using a 1-dimensional convolutional neural network (1D-CNN) to effortlessly and accurately obtain the working status information of the machine with minimal retrofitting. The 1D-CNN uses the energy consumption data to determine the equipment’s operation status by identifying the working components and the feed rate of the moving axis. The hyper-parameters of the developed model were optimized to improve the prediction accuracy. The paper also compares different Deep Learning and Machine Learning algorithms to gauge their effective performance in this application. Finally, the model with the highest accuracy was validated on a 5-axis ultra-precision CNC machine tool. Results show that 1D-CNN performs better than multi-layer neural networks and machine learning algorithms in processing time-series datasets. The classification accuracy of 1D-CNN on the detection of operation status and feed rate of each axis can reach 95.7 and 91.4%, respectively. Further studies are currently in progress to improve prediction accuracy of the model, and to detect subtle changes in energy consumption which would enable identification of the machine and process anomalies.

Least variation in tool orientation control for 5-axis CNC machining

We address the problem of minimizing the variation of the tool axis orientation of a 5-axis CNC machine equipped with a ball-end cutter that is designed to maintain a constant cutting speed, which is ensured by a fixed angle ψ between the tool axis a(t) and the workpiece surface normal n(t) at each point of contact as the cutter moves along a specified toolpath. The configuration can be mathematically translated into a pair of curves a(t) and n(t) on the unit sphere with constant parametric distance ψ, and the least variation of the tool axis orientation is achieved when the overall length of the curve a(t) is minimized under certain auxiliary boundary conditions. Using the calculus of variation we show that the solution a(t) consists of arcs of great circles and offset curves of n(t) on the unit sphere. A numerical approximation scheme based on Euler's method of finite differences is also provided.

Design of X-axis Feed System of Cradle Five Axis CNC Machine Tool and its Computer Finite Element Analysis

For the design of the x-axis feed system of the cradle five axis CNC machine tool, the entity modeling is carried out by using CATIA P3 v5r21 and Auto CAD; the x-axis design of the cradle five axis CNC machine tool is carried out and the accuracy and strength are checked; the CAE analysis of the structural strength and stability is carried out by using the general structural analysis module. The DMU kinematics module is used to eliminate the interference. Optimize the structural parameters to improve the stability and accuracy of machine tools.

The incremental sheet forming; technology, modeling and formability: A brief review

The constant need to improve manufacturing processes and production methods, with the aim of making these processes more flexible and precise, and subsequently solving problems of conformity, quality of manufactured parts and productivity, drives manufacturers to develop original manufacturing techniques. The incremental sheet metal forming process, one of these novel techniques, has attracted a great deal of attention in recent decades. This paper presents a review of recent work done in this area and captures ideas for future work based on studies conducted by several researchers. A review of advanced investigations considering the following terms of interest: process, tools, formability, modeling and simulation is developed. Overall, it can be said that ISF process still requires further research to exploit the fabrication of new materials such as novel nanocomposites and Functionally graded materials (FGM). Test the performance of 4- and 5-axis CNC machines to manufacture industrial parts. Finally, apply new hybrid technics at the aim to improve the geometric accuracy, formability and the productivity of ISF process.

Implementation of Marketing, Operational, and Human Capital Strategies for the Development of PT Sangyo Jaya Abadi (Subsidiary of PT Kuroshio Jaya Abadi)

Research conducted by PT Sangyo Jaya Abadi (PT SJA) has short-term goals: (1) to maintain customers of PT Kuroshio Jaya Abadi and increase publicity by participating in events/exhibitions at least every two years which are participated by many companies engaged in the automotive industry and oil & gas and other industries (2) to prepare raw materials and manpower for parts production according to customer requests (3) to obtain human resources with high competence and integrity. The long-term goals are (1) to increase the utilization of the premise by studying the development of subsidiaries in the field of machining precision (2) to develop the manufacture of Mold & Dies (3) to create a corporate culture that refers to innovation, creativity and continuous learning. This research uses qualitative spradley to describe the cultural characteristics more deeply in a systematic way that will have an impact on decision making by PT Sangyo Jaya Abadi. Target options that can be considered by PT Sangyo Jaya Abadi, reach all customer holding companies (PT Kuroshio Jaya Abadi) and get a name in the customer; addition of CNC machines with more modern and latest technology (5-Axis CNC machining); make purchases of raw materials needed for the manufacture of parts & other tools in accordance with the maximum stock quantity and forecast demand; cooperate with technology providers to produce Mold & Dies; manpower planning on understanding the technology of each line of the company reached 75%; and training and development programs in manufacturing technology, conducted every 6 months, especially for modern CNC machines (5-Axis CNC machining).

Optimization of grinding processes on fused silica components using in-process vibrometry and dynamometer measurements

The presented investigations deal with real-time evaluation and recording of vibrations and forces during a CNC grinding process, as well as the analysis and control of process influences on the surface quality of optical components. The experiments were carried out on a 5-axis CNC machine. Rapid subsequent analysis of the topography resulting from grinding is achieved with the aid of white light interferometry. The aim of the investigations is to reduce the surface deviations (roughness, mid-spatials, waviness) influenced by process factors. It is shown that the vibration data measured during the grinding process correlate to a high degree with the recorded topography data.

Calibration of a 5-Axis CNC Machine for Making Orthoses by Means of a Vision System

Calibration of a 5-Axis CNC Machine for Making Orthoses by Means of a Vision System

On the Application of Impeller in Multi Axis CNC Machine Tools

Multi axis CNC machine tool has good linkage processing effect. Through the application of integral impeller in CNC machine tools, to improve the adaptability of CNC machine tools to complex surface processing parts, to improve the accuracy of multi axis CNC machine tools. The first part of this paper introduces the integral impeller and its machining characteristics; the second part introduces the basic NC machining process of integral impeller; the third part discusses the application of impeller in multi axis CNC machine tools from the creation of guide track, the simulation of integral impeller, software processing and generation. The purpose is to provide some reference for the processing and production of integral impeller.

Minimization of surface roughness in 5-axis milling of turbine blades

The Reynolds number of turbine blades can be reduced by decreasing the surface roughness of the blades, which decreases energy loss in energy production systems. Due to the challenges of the polishing process in reducing roughness of machined blades, the application of optimized machining parameters to decrease surface roughness is a practical solution. Virtual machining system is explored in this research to improve the efficiency of machined parts. The aim of this research is to provide a virtual machining system that can predict and effectively reduce roughness in gas turbine blade 5-axis machining operations. The machining parameters were optimized using Genetic algorithm to reduce surface roughness. The turbine blades were machined using a 5-axis CNC machine tool, and the surface roughness of the machined parts was measured using a CMM machine to validate the developed methodology in the study. The optimized machining parameters result in a 26.2% reduction in observed surface roughness and a 27.3% reduction in expected surface roughness in the machined blades. The developed virtual machining system can be used to improve the surface quality of machined turbine blades and hence improve the efficiency of gas turbines during the power production in gas turbines.