Computer Numerical Control Machine Research Articles

"Man vs. Machine: 3D Milling of Auricular Frameworks".

Autologous rib harvest with manual framework production is the current gold standard for microtia reconstruction. Recent clinical success with implantation of cadaveric costal cartilage grafts opens the possibility of point of care auricular framework production. This paper assesses the feasibility and efficiency of 3D milling of cadaveric costal cartilage for auricular framework production. A Nagata/Firmin style auricular framework was manually carved en bloc out of soap and 3D scanned to design a milling toolpath on a desktop 3-axis computer numerical control (CNC) machine. An en bloc framework was then milled from cadaveric costal cartilage. Time to mill a complete framework was recorded. The dimensional/volumetric analyses were performed. The main outcome measures were total time to mill a complete auricular framework out of cadaveric cartilage and dimensional/volumetric comparisons to the model ear. Total milling time for the cartilage framework was approximately 7 min. Finalizing steps took an extra 20 min. Total time to produce a final framework ready for implantation was approximately 27 min, compared to the traditional 1-2 h by manual carving. All dimensional comparisons were within 2 mm to the manually carved model. Volumetric analysis showed 71% similarity. En bloc cadaveric costal cartilage framework milling is both feasible and efficient. 3D milling significantly reduces framework production time and allows for accurate reconstruction of the complex ear geometry, which can translate to cost savings, optimized patient safety, and potential for patient-specific reconstruction. The next step toward achieving clinical application is ensuring framework sterility.

Improvement of NC Program Quality based on Shape Generation Motions and Feed Drives for Five-Axis CNC Machine Tools

Five-axis Computer Numerical Control (CNC) machine tools, integrated with Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems, are used to machine complex parts and reduce trials and errors. However, these machine tools still rely on Numerical Control (NC) programs and often lack accuracy and precision due to poor quality when implemented in the machine. This research aims to enhance the quality of NC programs for five-axis CNC machine tools by focusing on shape generation motions and a closed-loop feed drive system with Proportional-Integral-Derivative (PID) control. The individual motions were mathematically described using 4x4 transformation matrices, incorporating kinematic motion deviations, end mill geometry, machining parameters, and cutting forces derived from virtual machining. Additionally, a closed-loop feed drive system with PID control was integrated with the new position and angular data of each axis from the shape generation motions model. The new NC programs were validated by machining an S-shaped part and measuring dimensional errors at 64 points before and after using a Coordinate Measuring Machine (CMM). The results indicate a substantial reduction in the standard deviations of form and angular errors within the NC program quality, totaling approximately 80.73%. Reductions are demonstrated in the standard deviations for the X, Y, A, and B axes, with decreases of 76.83%, 95%, 82.40%, and 68.72%, respectively indicating a significant improvement in the overall quality of the NC program.

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.

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

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.

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

Implementation and Evaluation of a Smart Machine Monitoring System under Industry 4.0 Concept

Production planning and control is essential in industrial manufacturing, ensuring efficient resource allocation and process management. Industry 4.0 introduces advanced technologies like cyber physical systems (CPS), artificial intelligence (AI), and internet of things (IoT) to effectively manage and monitor manufacturing operations. However, integrating these technologies into existing machinery, particularly for small and medium-sized enterprises (SMEs), poses challenges due to complexity and cost. The present study addresses this gap by designing and implementing a Smart Machine Monitoring System (SMMS) compatible with existing machinery such as computer numerical control and special purpose machines. The SMMS integrates IoT-based systems with AI algorithms to enhance machine tool utilization through effective planning, scheduling, and real-time monitoring. Through a nine-month case study in the shackle bolt manufacturing section, it was tested and compared to an Enterprise Resource Planning (ERP)-based system to assess its performance. Results showed significant improvements in production output, machine utilization rates, labor efficiency, and overall manufacturing costs. In conclusion, this study contributes to the body of knowledge on practical Industry 4.0 implementations for SMEs, offering insights into cost-effective solutions for enhancing operational efficiency and resource utilization in manufacturing environments.

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.

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.

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.

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.

Development of automatic CNC machine with versatile applications in art, design, and engineering

The area of computer numerical control (CNC) machines has grown fast, and their use has risen significantly in recent years. This article presents the design and development of a CNC writing machine that uses an Arduino, a motor driver, a stepper motor, and a servo motor. The machine is meant to create 2D designs and write in numerous input languages using 3-axis simultaneous interpolated operations. The suggested machine is low-cost, simple to build, and can be operated with merely G codes. The performance of the CNC writing machine was assessed by testing it on a range of solid surfaces, including paper, cardboard, and wood. The results reveal that the machine can generate high-quality text and images with great accuracy and consistency. The proposed machine's ability to write in several input languages makes it appropriate for various applications, including art, design, and engineering.

A Method for Generating Toolpaths in the Manufacturing of Orthosis Molds with a Five-Axis Computer Numerical Control Machine

This paper proposes a new algorithm for the automatic generation of toolpaths for machining complex geometric positions, such as molds used in orthosis production. The production of individualized orthoses often requires the use of multi-axis machining systems, such as five-axis machines or industrial robots. Typically, complex and expensive CAD/CAM systems are used to generate toolpaths for these machines, requiring the definition of a machining strategy for each surface. While this approach can achieve a reliable and high-quality machining process, it is very time-consuming and makes it challenging to meet the criteria for rapid production of orthopedic aids. Given that their production is a custom-made process using individual shapes as inputs, the toolpath generation process becomes even more demanding. To address these challenges, this paper proposes an algorithm suitable for the automatic generation of toolpaths for such complex positions. The proposed algorithm has been tested and has proven to be robust and applicable.

Designing Ergonomic Standing Chair for Computer Numerical Control Machine Operators using TRIZ

In this research, the working hours and posture of CNC (Computer Numerical Control) machineoperators were investigated to determine the physical workload that they experienced during theirdaily work. Based on our observations, the operator works 8-hour regular shifts or 12-hour longshifts for 5 – 6 days a week. During these shifts, the operators work in front of the CNC machinewhile standing upright without any tools to rest. Preliminary research was conducted to evaluatethese conditions the results show 13 out of 20 CNC machine operators complained about physicalfatigue while working the CNC machines. It can also be concluded that the operators areexperiencing excessive workload based on a workload assessment using the Quick Exposure Check(QEC) method. To solve this problem, a standing chair is designed with ergonomics in mind. Thedimensions of the standing chair are based on the anthropometry of the CNC machine operators,which was never used before. The design process is conducted using the Theory of InventiveProblem Solving (TRIZ) methodology. Need statements from the CNC machine operators anddesign requirements from the stakeholders are converted into design specifications using TRIZmethodology. Parameters are determined to increase the capability of the existing design based onthe design specifications. The result of this research is a standing chair that is suitable for theoperator’s needs. Based on the analysis of the design result and the stress analysis simulation, it canbe concluded a functional standing chair can be ergonomically designed with the TRIZmethodology.

Robust feature design for early detection of ball screw preload loss

The ball screw is a critical device for precision linear motion control that has widespread applications in industrial robots, computer numerical control (CNC) machines, and high-precision leveling systems, among others. Because high-precision positioning is ensured by the addition of a preload to the ball screw system, it is crucial to detect and monitor the loss of preload at the earliest possible stage of degradation. The degradation process of the ball screw can be characterized in two stages: the initial reduction of preload without backlash, followed by a loss of preload with an emergence of backlash. To explore the change of the ball screw dynamics caused by degradation, a novel fixed cycle feature test (FCFT) is implemented in combination with multi-level mass experiments and a run-to-failure (RTF) test. The relationships of the ball screw dynamics with preload, worktable mass, and axis position are investigated, with a focus on the axial natural frequency as an indicator of preload loss. Experimental results validate the axial natural frequency’s role as a reliable early detector of preload loss for interventive use in a prognostic system.

Jerk limited continuous tool path generation for flexible systems in non-cartesian coordinate systems

Inspired by computer numerical control (CNC) technology and drastic changes in the world of electronics and microcontrollers, the idea of using non-cartesian coordinate system for CNC machines became a topic of interest. Non-cartesian coordinate systems provide freedom of movement in systems with large working spaces where high dimensional accuracy is not a prime concern. Applications of such systems can be found in murals, where a painting is applied to a large wall of any arbitrary build material. In the present paper, a new design was introduced to automate the process of drawing murals on large surfaces. The proposed mechanism utilized chain and sprocket to overcome the size limitations of traditionally available x-y tables. In addition to that, the developed mechanism does not utilize the common robust structures used in the conventional CNC systems and the tool motion is created using flexible arms that are not heavily constrained. The effect of systems unwanted vibration has been eliminated using continuous trajectory and kinematic profiles. Parametric curve interpolation algorithms for trajectory planning were implemented to increase the flexibility of drawing complex curves. Parametric curves such as B-spline and non-uniform rational B-spline (NURBS) were employed to generate a jerk limited trajectory for motion control and extraction of kinematic profiles. Such trajectory constrains the jerk of the system and guarantees a smooth motion free of feed-rate fluctuations. Compared to other methods available for extracting the kinematic profiles, jerk limited method decreases the travel time and trajectory error. Ultimately, motion commands were produced by using kinematic profiles and the second order Taylor interpolator. STM32746ZG card was used as the main processor and two stepper motors controlled by a Bit Pattern interpolation algorithm were utilized to drive the proposed mechanism. The input pulses of stepper motors were stored as binary bits and transmitted to drivers in real-time. The feedback was also evaluated by two rotary encoders, placed at the end of the motors’ shafts. Encoder data were acquired and transmitted using a TCP/IP protocol to guarantee zero data loss during the transmission.

Smart Temperature Monitoring System for Machining Process Using Internet of Things

Outer surface integrity must be maintained throughout the machining process during the production of metal parts, which need the ability to monitor temperatures in real time. Changes in temperature during the machining process lead to changes in the behavior of the product after work is completed.To achieve quality and productivity criteria, the metal parts manufacturing process requires a continuous and precise temperature measuring and monitoring system by using IOT. An intelligent temperature measurement can be used during machining processes on conventional, non-conventional, and computer numerical control (CNC) machines. This paper presents a performance analysis of a temperature measuring system for machining process applications via Arduino IDE. In this proposal, a temperature monitoring system based on Arduino is used. The system would utilize an: MLX90614 infrared thermometer sensor” to measure the temperature of the workpiece during machining processes. The methodology's aim is to use the smart manufacturing model to measure and monitor the arising temperatures throughout the machining process in order to build a new tool path rapidly and efficiently. The placement of a non-contact infrared “MLX90614” temperature sensor allowed measuring of the average cutting temperature as well as the maximum cutting temperature. The data acquisition process was carried out using the “Xampp” Control Panel software, which communicated with the ESP32 “microcontroller” board using the Arduino IDE program. Experiments were carried out, so that the temperature of the cutting, which was measured, was recorded, and the results of the experiments were analyzed. Index Terms: Smart Manufacturing, Internet of Things, MLX90614 Infrared Temperature Sensor, Machining Parameters.