Computer Numerical Control Research Articles

Laser Powder Bed Fusion Manufactured Hydrostatic Journal Bearings for Turbomachinery: Design and Measurements of Static Load Testing With Air, Water, and Liquid Nitrogen

Abstract Modern turbomachinery demands simplified components and compact shaft support systems. This study introduces novel hydrostatic journal bearings incorporating multiple tilting pads and fluid feeding features, which are manufactured with Direct Metal Laser Melting (DMLM) technology, an advanced laser powder bed fusion manufacturing process. Two test bearings, fabricated by fusing extremely thin layers of Inconel 718 powder, incorporate fluid external feed pressurization features without the need for recesses. One test bearing features unique internal feeding hole configurations, which combine multiple holes with an angled injection feature, while the other test bearing includes distinctive porous layers on the bearing pad surfaces. This paper provides a comprehensive overview of the design, fabrication process, and static load characteristic measurements of these innovative bearings. A simple static load test rig is used to measure the flow rate, temperature, and stiffnesses of the test bearings while supplying compressed air, water, and liquid nitrogen with increasing static loads. The performance of these bearings is compared with counterparts produced using computer numerical control (CNC) machining, a conventional subtractive manufacturing process. In general, the bearings lubricated with liquid nitrogen exhibit a higher load capacity compared to those lubricated with air. This study confirms the static load performance of metal three-dimensional printed hydrostatic journal bearings, marking a significant advancement in the application of additive manufacturing for turbomachinery bearings. The findings offer valuable insights into the potential of additive manufacturing in producing bearings for extreme operating conditions and various lubricants.

Optimizing CNC milling parameters for manufacturing of ultra-sharp tip microneedle with various tip angles.

Microneedle technology has emerged as an advanced method for transdermal drug delivery, which focuses on diverse fabrication techniques to develop microneedles with various models and geometries. This study explores the application of Computer Numerical Control (CNC) milling technology to create microneedle master molds with extremely sharp tips. We examined the effects of two key machining parameters, feed rate and ramp angle, on the tip sharpness of the microneedles. Our results showed that increasing both the feed rate and ramp angle could significantly reduce machining time. However, a higher feed rate also led to larger tip diameters and notable tip defects. Conversely, changes in the ramp angle at a constant feed rate had minimal impact on tip size. We identified an optimal condition balancing cutting time and tip sharpness at a feed rate of 100mm/min and a ramp angle of 1.5°. Additionally, we assessed the CNC's capability to produce needles with different tip angles. The findings confirm that needles with varying tip angles maintained tip diameters below 10μm, with needles having a 50° tip angle exhibiting the sharpest tips at approximately 3.3μm. Further compression, insertion and diffusion tests were conducted to evaluate the performance of needles with different geometries.

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

Identification of optimal cutting parameters regarding lacquer wettability of CNC processed MDF panels by artificial neural network

ABSTRACT The primary objective of this study was to evaluate the surface roughness and lacquer wettability of medium-density fiberboard (MDF) panels processed on computer numerical control (CNC) machine. Then, it is aimed to determine the optimal CNC cutting parameters by modeling the data obtained from the experiments with ANN. For these purposes, two cutting tool types, two toolpath strategies, three spindle speed and four cutting depth values were used as CNC cutting parameters. The roughness and lacquer wettability tests were performed on the surfaces of MDF specimens after CNC machining. Using the obtained experimental data, the ANN models with the highest predictive ability were determined and the optimum CNC cutting parameters were defined according to surface roughness and lacquer wettability. The smoothest surfaces were obtained for the spiral router bit with offset toolpath strategy, 22,500 rpm spindle speed and 1.6 mm cutting depth, and for the straight router bit with raster toolpath strategy, 21,500 rpm spindle speed and 1.7 mm cutting depth. The optimal cutting parameters that gave the best lacquer wettability were an offset toolpath strategy, 20,500 rpm spindle speed and 1.5 mm cutting depth for spiral router, and a raster toolpath strategy, 20,500 rpm spindle speed and 3.1 mm cutting depth for straight router.

Informatization model of Guqin based on grasshopper and CNC machining

ABSTRACT The integration of Computer-Aided Design (CAD) and Computer Numerical Control (CNC) machining has brought modern manufacturing techniques into the craft of Guqin crafting, introducing the concept of Industrialized Standardized Guqin Crafting (ISGC). This study proposes the concept of Guqin Information Modeling (GIM), on the basis of which, the parametric modeling method of Guqin is proposed to realize the parameter control of the key position of Guqin; combined with the CNC machining technology, it verifies the production of Guqin of different materials and shapes, summarizes the method of selecting the tools for CNC machining of Guqin and the machining parameters of each process, and puts forward the Industrialized Standard of Guqin Carving (ISGC). The proposal of GIM and ISGC provides information technology support for the research of the sound quality of Guqin and the protection of Guqin.

Design and building CNC engraving router machine using Arduino Uno with GRBL control system

Computer Numerical Control Machines are one of the advances in automatically operated machining technology that can meet the need for complex and high-precision products. CNC machine parts generally have a mechanical and electrical system, also called a machine controller, that uses a Human Machine Interface at a high price. One of the software used to control the CNC machine is Arduino Uno, a PC-based GRBL System with a low price and the same function. This software is not far from the advantages of the HMI panel. Operating the machine with this software is also not that difficult. In this research, we intend to make a CNC machine using the Arduino Uno control system and software with a PC-based GRBL System, making it easier for operators to operate it. The results of the research that has been carried out show that the CNC has a size of 800x600x50mm with a system that is operated well and precisely

A Reconfigurable Architecture for Industrial Control Systems: Overview and Challenges

The closed architecture and stand-alone operation model of traditional industrial control systems limit their ability to leverage ubiquitous infrastructure resources for more flexible and intelligent development. This restriction hinders their ability to rapidly, economically, and sustainably respond to mass customization demands. Existing proposals for open and networked architectures have failed to break the vicious cycle of closed architectures and stand-alone operation models because they do not address the core issue: the tight coupling among the control, infrastructure, and actuator domains. This paper proposes a reconfigurable architecture that decouples these domains, structuring the control system across three planes: control, infrastructure, and actuator. The computer numerical control (CNC) system serves as a primary example to illustrate this reconfigurable architecture. After reviewing open and networked architectures and discussing the characteristics of this reconfigurable architecture, this paper identifies three key challenges: deterministic control functionality, the decoupling of control modules from infrastructures, and the management of control modules, infrastructures, and actuators. Each challenge is examined in detail, and potential solutions are proposed based on emerging technologies.

Investigation of cutting forces of glass sphere reinforced polymer composites

AbstractIn this study, the effects of reinforcement ratio, drill bit material, and drilling process parameters on the cutting forces generated during the drilling of glass sphere‐reinforced polypropylene composites were investigated experimentally. Test specimens were produced by conventional injection‐moulding of glass sphere reinforced polypropylene composite materials at 5 %, 10 % and 20 % wt. ratios. High speed steel, titanium‐coated high‐speed steel, and carbide drill bits with 4 mm diameter were preferred for drilling. In addition, the drilling process was carried out on a 3‐axis computer numeric control milling machine. Three different feed rates of 0.05 mm/rev, 0.10 mm/rev, and 0.15 mm/rev and cutting speeds of 12 m⋅min−1, 16 m⋅min−1, and 20 m⋅min−1 were determined for the drilling process. In addition, Taguchi experimental optimization method, analysis of variance and scanning electron microscopy were used to investigate the morphology of the drilled surface and the wear mechanisms occurring on the drill bit due to the drilling process. The test findings showed that the maximum torque value was 54.64 N⋅mm and the maximum thrust force was 100.43 N. The optimum test parameter for cutting forces was observed as C1D3FR1CS3. Drill parameter had an effect of 40.96 % on thrust force and 36.11 % on torque.

Research Progress towards the Machining of Titanium Alloy Using CNC Milling: A Technical Review

Because of their extraordinary qualities, titanium alloys are very sought-after materials that can be applied to a wide range of sectors. Excellent mechanical and chemical qualities, including a high strength-to-weight ratio and resistance to corrosion, are present in it. The special properties of these alloys make machining them extremely difficult. As frequent tool wear occurs throughout the machining process, Computer Numerical Control (CNC) milling has become a potential method for machining titanium alloys due to its precision and versatility. This review article provides a comprehensive overview of the development of titanium alloy CNC milling, with an emphasis on the effects of cutting tool geometries and materials on machining efficiency. The process examines several aspects of cutting circumstances, including depth of cut, speed, feed rate, and lubrication techniques, and optimizes machining parameters and procedures to achieve the best results. Surface integrity and quality, surface roughness, residual stresses, and microstructural changes brought about by CNC milling are the main points of evaluation.

Study on the analytical verification method of geometric error models

Abstract Geometric error compensation is a widely used and effective approach for enhancing the accuracy of Coordinate Measuring Machines (CMMs) and Computer Numerical Control (CNC) machines. The research in this field primarily focuses on the challenging task of developing geometric error modelling techniques. Currently, there are several well-established methods for modelling geometric errors. However, there is scarce availability of methods that can validate the established geometric error models. Therefore, this article proposes an analytical validation method for geometric error models based on the error transformation equation. The principle of the method is elaborately explained, and its correctness is verified through specific model verification example. The method proposed in this article enables rapid and accurate model correction and iteration, effectively reducing the economic and time costs of model validation in the current geometric error compensation process. Therefore, the method provides guidance for standardising the modelling process and could be widely applied to various structural forms of measurement and machining systems.

Positioning errors and accuracy of CNC machine tools

Abstract Computerized numerically controlled (CNC) machine tools are a solid foundation for modern industrial manufacturing. These machines provide linear and angular displacements in three or five axes. The accuracy of moving and positioning the tooltip relative to the work part’s surface determines the final product’s accuracy. Errors due to machine positioning can be linear or angular or both. This work studies the positioning errors of a vertical turning center CNC machine type. This machine has three axes, two linear X (horizontal) and Z (vertical), and one rotation axis ‘C’. The travel of the spindle carrying the cutting tool along the X-axis is 1400 mm, and the travel of the carriage holding the spindle along the Z-axis is 1300 mm divided into six latches. The machine rotary table which carries the work part can rotate 360°. A highly precise laser interferometer system determines the linear positioning errors in both the X and Z axes. The angular positioning errors for the ‘C’ rotation axis are determined accurately by an autocollimator system. The positioning error measurements are carried out based on ISO 230–2 as a measurement standard of positioning deviation, accuracy, and repeatability. The collected error measurements in linear displacements and angular rotation are analyzed, interpreted, and compared with manufacturer specifications and ISO 13041–4 allowable tolerances.

Fault diagnosis of computer numerical control machine tools table feed system based on digital twin and machine learning

Fault diagnosis of computer numerical control machine tools table feed system based on digital twin and machine learning

Machining error compensation of free-form surfaces by combination of ordinary kriging method and mirror compensation method

ABSTRACT Improving the accuracy and efficiency of free-form surface machining is a common goal of modern manufacturing. In this study, a compensation method combining the ordinary kriging method based on sequential quadratic programming method optimization (SQP-OK) and the mirror compensation method for machining errors of free-form workpieces was applied, with the aim of significantly improving the workpiece machining accuracy. Machining errors on the surface of the workpiece were predicted utilizing the SQP-OK after the workpieces were completed with semi-finishing machining based on the on-machine measurement (OMM) results of the workpiece. Based on the prediction result, the mirror compensation method was applied to calculate the compensation points. Free-form workpieces were compensated for by modifying the NC code for semi-finishing. To verify the effectiveness of the proposed method, two free-form workpieces were machined with computer numerical control (CNC) compensation, applying the proposed method and the method modifying the overall machining allowance. The experimental results revealed that the compensation method proposed in this paper reduced the average value of the machining errors decreased by 28.6% in absolute value, 31.1% in maximum undercut, and 28.8% in maximum overcut for the free-form workpiece, respectively, compared with the compensation method of modifying the overall machining allowance.

AI-based spatially resolved parameter prediction in laser metal deposition for increased process stability

In the additive manufacturing of components using powder-based laser metal deposition (LMD), the heating of the volume during buildup is a decisive factor for process stability and contour accuracy. If the process parameters remain constant, this intrinsic heating leads to deviations in the deposited layer thickness during the process because of changes in the melt pool volume. This leads to contour deviations and potentially causes the process to fail if the process parameters are no longer within the suitable range. Particularly in the case of complex geometries, this previously required time-consuming process development for adapted process parameters and buildup strategies. This paper examines the potential of data-driven approaches to enhance the stability and precision of LMD processes. To this end, a machine learning (ML) model is employed to optimize laser power settings. The objective of the study is to reduce the thermally induced geometric deviations that often occur during the LMD process by utilizing experimental data. The methodology employs the use of the alloy Inconel 718, renowned for its high strength and temperature resistance, in conjunction with the utilization of computer numerical control machines equipped with laser and imaging systems. The ML model is trained to predict the optimal laser power required to obtain consistent melt pool properties. The results demonstrate that the ML approach is an effective means of reducing geometric deviations.

Development of a Microparticle Blasting Device Capable of Simultaneous Three-axis Computer Numeric Control

Development of a Microparticle Blasting Device Capable of Simultaneous Three-axis Computer Numeric Control

Toward a digital twin of a robot workcell: standards and methods

Digital twins are poised to improve the engineering, operation, and management of manufacturing facilities. However, implementing digital twins has been a challenge primarily due to a lack of resources and the absence of standardized digital twin frameworks and methods. This paper describes creating a digital twin of a robot workcell using available standards, tools, and methods. The workcell comprises collaborative robot arms, a computer numeric control (CNC) machine tool, and a coordinate measuring machine (CMM). The ISO 23247 standard provides a guideline for building the digital twin. Data are collected from physical devices and the MTConnect standard provides a format for communicating the data between the physical equipment and their digital counterparts. The machine components in the workcell are represented as models in the virtual world. This research shows that the above standards and methods support building a digital twin of a robot workcell. The data collected and communicated can be used to improve workcell functions such as quality management and predictive maintenance.

Evaluation of the accuracy of digital impressions with different scanning strategies: An in vitro study

ObjectivesTo evaluate the effects of three different scanning strategies on the trueness and precision of optical impressions obtained with four intraoral scanners (IOSs). MethodsThe reference maxillary dental arch model was fabricated using Telio CAD, and the reference digital reference cast was obtained using a computer numerical control machine and an optical scanner (E4, 3Shape, Copenhagen, Denmark). Test scans were performed with four different IOSs (TRIOS3, MEDIT i700, CS 3600, and iTero Element 5D) by an experienced operator and three different scanning strategies (S1: manufacturer-recommended, S2: optimal per previous literature, and S3: experimental). The scan duration was recorded for each scan. All scans were converted to standard tessellation language format and imported into Geomagic Control X. The accuracy was measured by absolute deviation/distance between aligned surfaces. Data of trueness and precision of each IOS and scan duration were statistically compared using analysis of variance for repeated measures and Bonferroni post-hoc test (p < .05). ResultsNo significant differences in trueness were found among strategies (S1: 9.98 µm, S2: 11.93 µm, S3: 8.84 µm; p = .388) in Trios 3 and iTero Element 5D (S1: 12.24 µm, S2: 11.53 µm, S3: 10.71 µm; p = p = .279). Scanning strategy S3 with MEDIT i700 achieved greater trueness (7.33 µm) than S2 (16.33 µm, p < .05), while no significant difference was noted between S1 (10.44 µm) and S3 (p = .291). S3 showed the highest trueness (16.28 µm) compared to S2 (24.05 µm) and S1 (24.78 µm, p < .001) for CS 3600, with no difference between S1 and S2 (p = .457). Trios 3 had higher precision with S2 (22.46 µm) than S3 (31.69 µm, p < .05), and no significant differences between S1 (25.67 µm) and S2/S3 (p > .05). MEDIT i700 with S3 (29.52 µm) was more precise than both S1 (39.52 µm) and S2 (46.24 µm) (p < .001) with no difference between the last two (p = .302). S2 yielded the highest precision (44.93 µm) compared to S3 (61.81 µm) and S1 (76.53 µm) (p < .001) for CS 3600, with S3 more precise than S1 (p < .001). Similarly, iTero Element 5D showed S2 as the most precise (30.19 µm) compared to S3 (42.80 µm) and S1 (44.45 µm) (p < .05), with no difference between S1 and S3 (p = .472).Scan durations were shorter for S3 and S1 compared to S2 in Trios 3 (p < .001), and S3 was faster than S1 and S2 for MEDIT i700 (p < .001). CS 3600 scans with S1 were quicker than S2 and S3 (p < .001). For iTero Element 5D, no significant differences were found between S1 and S3 (p = .511), but S2 was slower than both (p < .001). ConclusionsScanning strategies significantly affect the accuracy and scan duration of optical impressions. Specifically, S3 provided the best trueness with both the MEDIT i700 and the CS 3600 while the S2 strategy demonstrated the highest precision for most scanners. Overall, the S1 and S3 strategies resulted faster than S2 among the devices evaluated. Clinical SignificanceThe results suggest that the experimental scan strategy may optimize the use of intraoral scanners in clinical practice, potentially leading to more accurate and time-efficient dental impressions.

A Normal Displacement Model and Compensation Method of Polishing Tool for Precision CNC Polishing of Aspheric Surface.

The position accuracy of the polishing tool affects the surface quality of the polished aspheric surface. The contact deformation among the polishing tool, abrasives, and aspheric part can cause a displacement, which, in turn, will cause a position error of the polishing tool, which will lead to a significant change in the polishing force. In order to resolve this error, this paper proposed a method of normal displacement compensation for a computer numerical controlled (CNC) polishing system by controlling the polishing force. Firstly, the coupling principle between the polishing force and the position of the polishing tool is expounded, and the relationship between normal displacement and deformation is analyzed. Based on Hertz's theory, a model of normal displacement is established. Then, on the basis of the decoupled polishing system developed, a normal displacement compensation method was proposed. Finally, a group of comparative experiments was carried out to verify the effectiveness of the proposed method. Compared with no displacement compensation, when the part was polished with the normal displacement compensation method, the value of roughness decreased from 0.4 µm to 0.21 µm, and the unevenness coefficient of surface roughness decreased from 112.5% to 19%. The experimental results show that the polishing quality is improved greatly, and the aspheric surfaces can be polished more uniformly with the method proposed in this paper.

Structural integrity assessment of pipe elbows: Burst test and finite element analysis

In this study, the failure pressures of pipe elbows were compared with those predicted using Level 3 numerical assessment method (Finite Element Method). Four 90-degree pipes elbows representing a pristine pipe, a pipe with a single corrosion defect, a pipe with longitudinally aligned interacting defects, and a pipe with a circumferentially aligned interacting defects, were subjected to internal pressure based on the ASME B31.3–2012 Burst Test standard until failure. The Sch-80 pipes were made of ASTM A234 WPB steel with a wall thickness and bending radius of 12.7 mm and 305 mm respectively. The corrosion defects were simulated on the exterior surface of the pipe elbows using computer numerical control (CNC) machine to generate a machined version of the corrosion defect. The results revealed that corrosion defects significantly reduce the burst pressure of pipe elbows, with longitudinally aligned interacting defects causing the largest reduction of 20.9 % compared to pristine pipe. The comparison between the Level 3 numerical assessment method and burst test showed close agreement with a maximum difference of 4.79 %, confirming the accuracy and reliability of the numerical method.

Methodology and Experimental Verification for Predicting the Remaining Useful Life of Milling Cutters Based on Hybrid CNN-LSTM-Attention-PSA

In modern manufacturing, the prediction of the remaining useful life (RUL) of computer numerical control (CNC) milling cutters is crucial for improving production efficiency and product quality. This study proposes a hybrid CNN-LSTM-Attention-PSA model that combines convolutional neural networks (CNN), long short-term memory (LSTM) networks, and attention mechanisms to predict the RUL of CNC milling cutters. The model integrates cutting force, vibration, and current signals for multi-channel feature extraction during cutter wear. The model’s hyperparameters are optimized using a PID-based search algorithm (PSA), and comparative experiments were conducted with different predictive models. The experimental results demonstrate the proposed model’s superior performance compared to CNN, LSTM, and hybrid CNN-LSTM models, achieving an R2 score of 99.42% and reducing MAE, RMSE, and MAPE by significant margins. The results validate that the proposed method has significant reference and practical value for RUL prediction research of CNC milling cutters.