Machining Center Research Articles

Improvement of structural/tribological properties and milling performances of tungsten carbide cutting tools by bilayer TiAlN/TiSiN and monolayer AlCrSiN ceramic films

In this study, bilayer TiAlN/TiSiN and monolayer AlCrSiN ceramic films were grown on carbide cutting tool material by cathodic arc physical vapor coating (CAPVD) method to improve the structural/tribological properties and milling performances. The ceramic films were applied on cylindrical test samples and carbide end mills. The coated materials' structural, mechanical, and tribological properties were determined via scanning electron microscope (SEM), X-ray diffraction meter (XRD), tribometer, microhardness tester, and optical profilometer. DIN 40CrMnNiMo8-6-4 steel workpieces were machined by using a CNC vertical machining center to determine the actual working performance of the coated and uncoated cutting tools. The wear performance of the cutting tools after machining was determined by measuring the flank wear widths and mass losses. The hardness and adhesion results of the coated sample with bilayer TiAlN/TiSiN were higher than the coated sample with monolayer AlCrSiN. According to the scratch test results, the best adhesion results were obtained for TiAlN/TiSiN coating. The critical load value was determined as about 105 N. As a result, the wear rate value of the TiAlN/TiSiN thin film coated sample was lower. After machining, the mass loss of TiAlN/TiSiN coated tools was lower than AlCrSiN coated tools. In addition, the surface roughness value of the workpiece machined by the cutting tool coated with AlCrSiN was higher than the cutting tool coated with TiAlN/TiSiN.

Development of a computer vision-based system for part referencing in CNC machining centers

Development of a computer vision-based system for part referencing in CNC machining centers

Cutting Performance of Multicomponent AlTiZrN-Coated Cemented Carbide (YG8) Tools during Milling of High-Chromium Cast Iron

In order to improve the cutting performance of cemented-carbide (YG8) tools during the milling of high-chromium cast iron, AlTiZrN coating was deposited on the surface of YG8 samples and milling tools by physical vapor deposition (PVD) technology. The micromorphology and mechanical properties of the coating were studied by the experimental method, and the cutting performance of the coated tools was tested by a milling machining center. The results show that the AlTiZrN coating presents the face-centered cubic (fcc) structure of TiN. The average microhardness is 3887 HV0.05. The bonding strength between the coating and the substrate meets the standard HF3 and is up to the requirements. The coefficient of friction (COF) of the coating is about 0.32. AlTiZrN coating can significantly improve the life of cemented-carbide tools. At cutting speeds of 85, 105, and 125 mm/min, the lives of the AlTiZrN-coated tools increased by 20.7%, 22.4%, and 35.2%, respectively, compared with the uncoated tools. Under the same cutting condition, AlTiZrN-coated tools have better cutting and chip-breaking performance than uncoated tools. With the increase in cutting speed, the workpiece chips produced by AlTiZrN-coated tools are smaller and more uniform, and the scratches on the machined surface are smoother. Therefore, at higher cutting speeds, AlTiZrN-coated tools have more advantages in life and cutting performance than that of uncoated tools. During the cutting process, the wear mechanisms of the AlTiZrN-coated tools mainly included friction, oxidation, and bonding, while oxidation and bonding wear were the main wear mechanisms in the later stage of wear.

Improved Synchronous Motion of Linear and Rotary Axes While Avoiding Torque Saturation Under a Constant Feed Speed Vector at the Endmilling Point – Investigation of Motion Error Under Numerical Control Commanded Motion –

A five-axis machining center is known for its synchronous control capability, allowing complicated three-dimensional surfaces, such as propellers and hypoid gears, to be quickly created. Prior research has shown that it is necessary to improve not only the machined shape accuracy but also the machined surface roughness of free-form surfaces. Therefore, in this research, we aimed to maintain the feed speed vector at the endmilling point by controlling two linear axes and a rotary axis with a five-axis machining center to improve the machined surface quality. In previous research, we suggested reducing the shape error of machined workpieces (referred to as shape error in this research) by considering the differences in the servo characteristics of the three axes in the machining method. The shape error was significantly decreased by applying the proposed method, which uses a parameter (referred to as precedent control coefficient in this research) determined by calculation, rather than trial and error. Moreover, to maintain the feed speed vector at the endmilling point when machining complex shapes, a rapid velocity change in each axis is required, causing inaccuracy owing to torque saturation. The results of the experiments and simulations of previous research indicated that torque saturation can be evaluated via simulation. In this research, to reduce the shape error while avoiding torque saturation when movement has high angular velocity, we developed a theoretical method to obtain the most suitable precedent control coefficient of each axis by using a block diagram that considers torque saturation. Therefore, both shape error reduction and torque saturation avoidance can be realized by using the proposed method.

Feedforward Model-Based Intelligent Compensation System for Spindle Dynamic Thermal Error

Among spindle dynamic errors, thermal error is an important factor affecting machining precision, the most convenient and economical solution for which is dynamic compensation of thermal error. In view of defects of complicated system, complex debugging, poor stability, high cost, etc., in the existing compensation approaches, thermal error compensation technology is investigated with compensation model established to complete the system design. The system is tested on the spindle of precise horizontal machining center. In the experiment, multiple linear regression, BP neural network, etc. are taken for technical analysis with dynamic feedforward model established. The experimental results indicate that the compensation system under study has dynamic compensation rate of over 90%, while the spindle has greatly shorter warm-up time, which can operate normally before entering the thermal steady state. The finally completed feedforward model-based intelligent compensation control system has good steady-state and dynamic compensation performance. In particular, its self-correction function greatly improves system adaptability and simplifies operation in use.

Increasing Machining Accuracy Based on CNC Machine Tool Correction Data by Using Ad Hoc Modification

The geometric accuracy of a workpiece represents one of the key parameters defining its quality, and it is affected by the appropriate selection of the machine tool, control system, NC program and cutting conditions. Up-to-date control systems contain advanced compensation functions, which increase the volumetric accuracy of the machine tools. Nevertheless, these functions use correction data measurements within the machine tool’s periodic maintenance plan. This paper introduces a method for ad hoc correction data modification. This modification is based on the difference between the real and nominal workpiece geometries, which are evaluated on a coordinate-measuring machine as a standard process in high-accuracy workpiece production. Correction data are compiled in the form of a three-dimensional structured mesh, where nodes of the mesh contain such correction values that interpolations within the mesh suppress workpiece geometric deviations. The correction mesh calculations are based on the assumption that the nodes are connected by imaginary springs and that they are initially in force equilibrium. Force disbalance is introduced by workpiece geometric deviations evaluated at arbitrary points. Then the new position of force-balanced nodes is calculated. Experimental results on a three-axis machining center have verified the proposed method, where geometric accuracy of the workpiece increased more than 85% without any negative effect on surface quality. The approach presented is efficient for increasing workpiece accuracy without the need for NC program modification.

Minimization of Total Variable Cost through Determination of Batch Transfer Size at m Serial CNC-Machining Centers

Background: In a batch production series consisting of several process stages for discrete products, the determination of the transfer batch size greatly affects the batch waiting time. For production using a Computer Numerical Control (CNC)-machining center, several process stages can be carried out on one machine with quick setup. The use of a single machine for all stages of the process certainly does not require transfer to the next machine. Thus, there are no material handling costs. However, the use of a single machine will result in longer batch waiting times as the production batch size increases. An increase in the batch waiting time will result in an increase in work-in-process (WIP) inventory cost. This research was conducted to reduce the total variable cost consisting of WIP inventory cost and material handling cost. Methods: This research was conducted in two steps. The first step is to divide the process stages, I into m serial CNC machining centers, where in this study I=m. The second step is to determine the same size of transfer batch, Qij for a certain number of transfers, J that produces the minimum total variable cost. Results: The results showed that J=5 resulted in a total variable cost of Rp. 146,800.00, while J=10 resulted in a total variable cost of Rp. 178,900.00. Conclusion: In conclusion, the total variable cost decreases if the size of transfer batch is reduced to a certain amount and will increase again along with the reduction in the size of transfer batch.

Programming methodology for multi-axis CNC woodworking machining center for advanced manufacturing based on STEP-NC

ABSTRACT The paper proposes a programming methodology for advanced manufacturing based on STEP-NC, a compliant to multi-axis CNC woodworking machining center. The equivalent virtual machine in the CAD/CAM, STEP-NC environment, is developed as a part of a programming system for considered CNC woodworking machining center. STEP-NC aims to provide a digital thread for CNC manufacturing running in the STEP-NC System world via the Internet that can enable advanced e-Manufacturing. Virtual machine as a digital twin is configured and implemented into the control system based on LinuxCNC, but configured virtual machine as a Web interface based on STEP-NC, also. The developed methodology is validated through machining simulation using the configured digital twin in the control system and machining experiments on the real machine.

Machining Centres Products and News in Brief

Steed Webzell takes a look at a flurry of recent machining centre installations across the subcontracting, OEM and research sectors

Pragmatic Solutions for Prismatic Parts

Steed Webzell takes a look at a flurry of recent machining centre installations across the subcontracting, OEM and research sectors

A new lubrication approach in the SPIF process: Evaluation of the applicability and tribological performance of MQL

The abrupt changes in the customer demands and the need to achieve versatility in production for satisfying the different needs of consumers have resulted in the development of rapid prototyping processes. Single Point Incremental Forming (SPIF) is a forming method which doesn’t require dies for production and thus enables to greatly reduce the manufacturing costs for low to medium batch productions while enabling versatile manufacturability. One of the major disadvantages of this process is the poor surface quality of formed parts due to friction between tool and sheet interfaces. For this reason, suitable lubrication techniques and the use of lubricants are of great importance in obtaining the desired surface quality. In this study, the Minimum Quantity Lubrication (MQL) technique, which provides significant improvements in metal cutting processes with its effective lubricating feature, has been applied for SPIF process to investigate its effectiveness in SPIF processes. For this purpose, a series of experiments have been carried out by forming 7128 sheet metals with SPIF process in a CNC vertical machining center. In the experiments, SPIF parameters (feed rate, tool stepdown, etc.) have been kept constant and the effects of MQL parameters on surface roughness/topography, thickness distribution, roundness deviation, angular deviation have been focused. Three different pressures (4, 6, and 8 bar), three different flow rates (50, 75, and 100 mL/h) and three different vegetable-based oils with different viscosities have been selected as MQL parameters. In addition, 7128 sheet metal has been formed with the SPIF process by using a paste lubricant for the comparison of paste lubricated and MQL assisted SPIF process. Finally, friction tests have been carried out in a ball-on-disk device to determine the friction coefficients of the oils. Experimental results have shown that the increase in pressure has greatly increased the surface quality and dimensional accuracy, while the increased flow rate level improved the surface quality and dimensional accuracy up to a certain value (75 mL/h). It has been concluded that the surface quality can be improved by 14.60% with the MQL assisted SPIF process over the paste lubricated SPIF process, which has proved the applicability and superiority of MQL technique for SPIF processes.

Optimal cutting condition selection for high quality receptance measurements by sweep milling force excitation

In large machine tool applications, where machine's productivity is limited by structural chatter vibrations, an accurate dynamic characterization is vital for predicting reliable stability lobes. Motivated by the fact that the sweep milling force excitation method shows a great potential, this paper conducts a numerical stability analysis for optimizing the tool radial engagement employed during the characterization cutting tests. Additionally, an alternative spectra computation technique is proposed which considerably improves the signal to noise ratio over the existing technique. The receptance measurement is demonstrated using time domain simulations and applied in a large-scale three axis machining centre obtaining more accurate stability boundary predictions. The source code of the temporal milling simulation and the sweep milling signal processing is freely available to reproduce the simulation and experimental results. https://github.com/OierFranco/SMFE.

Innovative Research and Development of CNC Heavy Horizontal Machining Center

Innovative Research and Development of CNC Heavy Horizontal Machining Center

THERMAL-DEFORMATION BEHAVIOR OF THE COMPOSITE MATERIAL BED

The thermal stability of the machining centers plays a major role in ensuring the production repeatability. All machine tools producers take various steps to ensure it. One of the ways to permanently maintain and stabilize the behavior of the machine tool is the use of active cooling and the choice of appropriate material of which the individual parts of the supporting system are made. In most cases, manufacturers of the machining centers use traditional metallic materials (steel, cast iron) for construction of the machine supporting system. However, these materials have some physical limitations. These materials can be replaced by or combined with unconventional materials to improve the thermal stability of the machine. The hybrid composite supporting structures are formed this way. The authors of this article examine the impact of steel-concrete composite material on thermal-deformation behavior of the bed in a vertical turning machining center for medium-heavy workpieces. The composite consists of the steel weld, filled with high-strength concrete.

AN IMPACT OF THE STEEL-CONCRETE COMPOSITE SUPPORTING STRUCTURE ON THE DYNAMIC PARAMETERS OF THE MACHINING CENTER

A self-excited vibration, called “chatter”, is a main limiting factor in chip-forming metal machining. The reduction of machining productivity, worsened machined surface quality and the reduction of lifetime of the machine tool parts, particularly the cutting tool itself, occur as a result of the chatter. There are more ways to suppress this undesired effect of machining. The most common and simplest variant is the structural modification of the supporting parts of the machine in order to increase the dynamic stiffness and damping. In most cases, manufacturers of the machining centers use traditional metallic materials (steel, cast iron) for construction of the machine supporting system. However, these materials have some limitations. In order to improve the dynamic parameters of the machine during machining process it is appropriate to combine these materials with others to create hybrid, composite structures. Authors of this article have performed the real experiment in order to test the real dynamic properties of the vertical multitasking machining center with the turning operation prevailing. The individual segments of the supporting structure are made of the composite material – a combination of a steel welded structure filled with high-strength cement concrete.

Study on the spindle axial thermal error of a five-axis machining center considering the thermal bending effect

Spindle axial thermal error is one of the main sources affecting the accuracy of a machine tool. It is important to study this error with respect to thermal optimization design and thermal error compensation. The column thermal bending effect mainly caused by spindle rotating is an important factor affecting the spindle axial thermal error, but it is often ignored in current research. In this paper, a novel modeling approach to studying the spindle axial thermal error of a five-axis machining center that considers the thermal bending effect was proposed. Experiments with different thermal boundary conditions were conducted to decouple this error. The thermal deformation coefficients of the column were effectively identified by using both the axial and radial thermal error data. Then, a physically-based model including the error component caused by the thermal bending effect was established. The complicated evolution process of the measured spindle axial thermal error can be explained by the proposed model. The thermal bending angles can be also effectively predicted to quantify the thermal bending behaviors. Furthermore, compared with three typical data-driven models, the proposed model shows better performance in predicting the axial thermal error. The proposed modeling method helps in better revealing the formation mechanism of the spindle axial thermal error. And the proposed model shows a good application prospect for error compensation because of its generalization ability and simplicity.

Deep-Learning Method Based on 1D Convolutional Neural Network for Intelligent Fault Diagnosis of Rotating Machines

Fault diagnosis in high-speed machining centers (HSM) is critical in manufacturing systems, since early detection saves a substantial amount of time and money. It is known that 42% of failures in these centers occur in rotatory machineries, such as spindles, in which, the bearings are fundamental elements for effective operation. Nowadays, there are several machine- and deep-learning methods to diagnose the faults. To improve the performance of those traditional machine-learning tools, a deep-learning network that works on raw signals, which do not require previous analysis, has been proposed. The 1D Convolutional Neural Network (CNN) proposed model showed great capacity of adapting to three types of configurations and three different databases, despite a training set with a smaller number of categories. The network still detected faults at early damage stages. Additionally, the low computational cost shows the Deep-Learning Neural Network’s (DLNN) suitability for real-time applications in industry. The proposed structure reached a precision of 99%; real-time processing was around 8 ms per signal, and standard deviation of repeatability was 0.25%.

Investigation of Hadfield Steel Machinability in Milling Operations

Hadfield steel is widely used in the manufacture of machines and mechanisms operating in harsh conditions. When machining Hadfield steel parts, problems are due to the strain hardening. The article studies the influence of cutting modes on steel hardness, tool thrust and surface roughness when milling Hadfield steel using cutters with replaceable inserts. The experiments were conducted on a milling machining center using high-productivity cutting tools. The optical roughness measuring method was applied. Hardness was measured with a portable hardness tester before and after milling. The article describes experimental results that show the dependence of the output machining parameters on the cutting speed and feed per tooth. The influence of cutting data on tool life in a finish milling operation was identified. The results will help to improve the quality and productivity and increase the tool life in roughing and finishing Hadfield steel parts.

Research and Analysis Based on Three-dimensional Precision Inspection Process Planning Technology

Three-dimensional precision inspection has the characteristics of digitization, completeness, and timeliness. The manufacturing industry needs to research and improve the existing inspection process planning technology. Carried out research on the key technology of three-dimensional inspection process planning, including inspection information extraction, inspection point planning, path planning, etc., compared and analyzed the offline inspection technology represented by the coordinate measuring machine and the online inspection technology represented by the machining center. Studied and analyzed the system architecture, main functional modules of process planning software tools for these two types of inspections; finally, it looks forward to the future development trend.

Machine shops invest to meet growth targets

Smaller 5-axis machining centre nearly doubles productivity at PRV Engineering; new multi-tasking lathe turns MRN Engineering into a one-stop-shop; and Volz Engineering Ltd invests as it looks to ensure its meet ambitious growth plans