5-axis Milling Research Articles

Topography prediction at boundaries between sub-regions in the 5-axis milling of Plexiglas based on dimension reduction method

Sub-regional milling has become an important machining method in the production of free-form surface parts. However, due to complex tool paths, irregular surface topography can occur at the region boundaries, which in turn affects the performance of the part such as the light transmission, optical distortion and mechanical strength of non-metallic transparent material etc. It is vital for manufacturers and researchers to study the forming mechanism of topography at boundaries and then to control it to get the high quality of the machined surface. Therefore, this paper thoroughly investigates the formation of surface topography at the boundary of sub-regions in the five-axis machining process. First, the boundaries of sub-regions are classified. Simultaneously, swept surfaces of the cutting edge, taking into account the process parameters and tool path, are constructed. Then, the surface topography is calculated using an improved model based on dimension reduction theory. Furthermore, through simulation and experiments, the predicted surface topographies agree well with the measured ones. Finally, some conclusions are listed and the method in this paper can provide a reliable basis for manufacturing high-quality parts.

Exploration of Materials for Three-Dimensional NMR Microcoil Production via CNC Micromilling and Laser Etching.

The excellent versatility of 5-axis computer numerical control (CNC) micromilling has led to its application for prototyping NMR microcoils tailored to mass-limited samples (reducing development time and cost). However, vibrations during 5-axis milling can hinder the creation of complex 3D volume microcoils (i.e., solenoids and saddle coils). To address these limitations, a high-resolution NSCNC ELARA 4-axis milling machine was developed with the extra precision required for making complex 3D volume microcoils. Upon investigating the performance of resonators made with various copper-coated dielectrics, resonators with poly(methyl methacrylate) (PMMA) provided the best SNR/line shape. Thus, complex 1.7 mm microcoil designs were machined from Cu-coated PMMA. A milled 6.4 mm solenoid also provided 6.6× the total carbon signal for a 13C-labeled broccoli seed compared to a commercial inverse 5 mm NMR probe (demonstrating potential for larger coil designs). However, the manufacture of coils <1.7 mm with copper-coated PMMA rods was challenging as ∼0.5 mm of remaining PMMA was needed to retain their structural integrity. To manufacture smaller microcoils, both a solenoid and saddle coil (both with 1 mm O.D., 0.1 mm thick walls) were etched from Cu-coated glass capillaries using a UV picosecond laser that was mounted onto an NSCNC 5-axis MiRA7L. Both resonators showed excellent signal and identified a wide range of metabolites in a 13C-labeled algae extract, while the solenoid was further tested on two copepod egg sacs (∼4 μg of total sample). In summary, the flexibility to prototype complex microcoils in-house allows laboratories to tailor microcoils to specific mass-limited samples while avoiding the costs of cleanrooms.

Generation of cubic Hermite spline-based trochoidal milling toolpath by introducing a coefficient factor in machining curved slots

Trochoidal milling has become popular in high-speed milling due to its ability to reduce cutting force, enhance thermal dissipation, and prolong tool life. Among other toolpath patterns, the cubic Hermite spline offers significant advantages in generating trochoidal milling toolpath in machining complex and curved slots. However, determining those two different relation coefficients in the polynomial function of cubic Hermite spline remains complicated and empirical. This paper introduces a coefficient factor to simplify the determination process, which only requires the position and tangent vector parameters of each endpoint pair. The coefficient factor combines an instantaneous in-process slot width (IISW)-related width factor and a tangent vector direction-related direction factor. Two complex-curved slots are used to validate the performance of the proposed method. The results show that this method is straightforward and effective in generating trochoidal milling toolpaths for machining complex-curved slots while matching the slot geometry. Additionally, compared with a direct 5-axis trochoidal milling (one-step slotting strategy) in trochoidal milling of 3D slots on both serial and hybrid machining tools, a two-step slotting strategy (3-axis trochoidal milling and a successive 5-axis perpetual milling) is preferable in improving machining efficiency.

Optimization of CNC milling parameters using the response surface method for aluminum 6061

The manufacturing sector is constantly seeking ways to optimize the machining process, specifically for 3-axis CNC machines. This study aims to identify the optimal parameter values that result in the lowest roughness and the highest process capability in 3-axis CNC milling. The roughness level (Ra) of the product is primarily influenced by factors such as feed rate, spindle speed, and depth of cut. Additionally, the reliability of the machining process was analyzed to evaluate its ability to consistently achieve low roughness values and to validate the process capability of the VH850L3 series 3-axis CNC milling machine. The suggested approach for this analysis was the RSM central composite design method, which involved conducting experiments under various input conditions. The results indicated that the feed rate had the most significant impact on roughness, followed by the spindle speed, while the depth of cut had no effect. The parameters that resulted in the lowest roughness response were a spindle speed of 2589.76 rpm, a depth of cut of 0.159 mm, and a feed rate of 247.731 mm/min. These parameter values were tested on a 3-axis CNC machine, and the resulting data exhibited variations. Data processing revealed that the machine still performed optimally in the machining process, as indicated by the value of . However, the milling process deviates from the standard target, as the response value shows significant variation with a Cpk value 1.

Influence of Tool Inclination and Effective Cutting Speed on Roughness Parameters of Machined Shaped Surfaces

Free-form surfaces in the automotive or aviation industry where the future shape of the product will contain complex surfaces raises the question of how to achieve the necessary shape of the required quality in the milling process. One of the methods of their production is the use of 5-axis milling, in which it is necessary to consider not only the input data of the process itself, but also the methodology for evaluating the desired results. Correctly answered questions can thus facilitate the choice of the inclination of the tool when machining parts of the surfaces defined in the experiment. The primary goal of the paper was to monitor the influence of tool inclination on the quality of the machined surface and effective cutting speed by evaluating surface roughness and surface topography. The experiment was designed to show the effect of different tool positions while the feed per tooth fz for the finishing operation remained constant. The best result in terms of surface quality was achieved with a tool inclination of 15° in the cutting process. The most unfavorable result was obtained with a tool axis inclination of zero degrees due to unfavorable cutting conditions.

Towards Zero-Defect Manufacturing Based on Artificial Intelligence through the Correlation of Forces in 5-Axis Milling Process

Zero-Defect Manufacturing (ZDM) is a promising strategy for reducing errors in industrial processes, aligned with Industry 4.0 and digitalization, aiming to carry out processes correctly the first time. ZDM relies on digital tools, notably Artificial Intelligence (AI), to predict and prevent issues at both product and process levels. This study’s goal is to significantly reduce errors in machining large parts. It utilizes data from process models and in situ monitoring for AI-driven predictions. AI algorithms anticipate part deformation based on manufacturing data. Mechanistic models simulate milling processes, calculating tool deflection from cutting forces and assessing geometric and dimensional errors. Process monitoring provides real-time data to the models during execution. The research focuses on a high-value component from the oil and gas industry, serving as a test piece to predict geometric errors in machining based on the deviation of cutting forces using AI techniques. Specifically, an AISI 1095 steel forged flange, intentionally misaligned to introduce error, undergoes multiple milling operations, including 3-axis roughing and 5-axis finishing, with 3D scans after each stage to monitor progress and deviations. The work concludes that Support Vector Machine algorithms provide accurate results for the estimation of geometric errors from the machining forces.

Intuitive toolpath planning in computer-aided manufacturing systems using artificial intelligence in a virtual reality environment

CAM systems are widely used in many key industries and are essential for many machining processes such as 5-axis milling. For toolpath planning, state-of-the-art CAM systems require the user to enter many abstract parameters, making these systems difficult to use. This paper presents a more intuitive approach to toolpath planning. The approach uses convolutional neural networks to interpret user gestures in a virtual reality environment and predicts the values of the aforementioned parameters. The results show that many of these parameters can be extracted from user gestures with high accuracy, which can be used to greatly simplify toolpath planning.

Integrating Cloud Computing, Bayesian Optimization, and Neural-Additive Modeling for Enhanced CAM Systems in 5-Axis Milling

This publication introduces the development and application of an advanced CAD/CAM/CAE system that leverages the computational capabilities of an edge-cloud infrastructure. The developed system consists of containerized technology models for various complex process planning simulation tasks in 5-axis-milling, such as toolpath calculation, cutter-workpiece-engagement, uncut chip geometry or cutting force simulations. Moreover, a Bayesian optimization (BO) algorithm is coupled with the system enabling multi-objective optimizations of the considered machining operations by varying predefined CAM-parameters. The result of the optimization consists of a set of Pareto-efficient solutions. Each solution realizes a different tradeoff between the technological objectives of the process planner. Since mastering the complexity of the design space is a major challenge in today’s CAM programming workflow, a Neural-Additive Model (NAM) is coupled with the system improving guided search through the configuration/result space. This reduces the convergence time to an optimal CAM parameter set. The coupling of the cloud computing, multi-objective optimization and artificial intelligence method with a CAM-kernel is demonstrated based on the process design of 5-axis milling operations for a blade-integrated disk (blisk).

Improving dynamic process stability in finishing of thin-walled workpieces by optimal selection of stock shape

In 5-axis milling of thin-wall parts, flexibility of the in-process-workpiece (IPW) governs static and dynamic deflections, especially at the semi-finishing and finishing stages. Thus, the near net shape preform, i.e. the stock shape left for semi/finishing is crucial for chatter stability. In this study, a methodology is presented to design the stock shape for improved stability. Coupled process simulation, which includes material removal, finite element analysis (FEA) and process stability simulations, is used to show the effect of stock shape on chatter stability. Spindle speed is optimized along the toolpath based on the varying process dynamic behavior for selected cutter locations (CL). The proposed method is experimentally demonstrated on case studies.

Experimental characterization of energy consumption in 5-axis milling machine and developing optimization strategy

The optimization of machining processes is of paramount significance because of its pivotal role in modern manufacturing. Efficient machining techniques not only enhance product quality but also reduce costs and environmental impacts. This study focuses on the experimental characterization of energy consumption in a 5-axis milling machine and the simulation of possible solutions to reduce it. The first step is to understand the key drivers of energy consumption which is crucial for enhancing energy management and optimization. This was achieved by developing a mathematical model that uses the most common machining parameters as input using a Response Surface Methodology experimental test plan and an analysis of the contributions of the auxiliary systems to the overall energy consumption. As a second step, the effectiveness of different solutions was simulated considering different application scenario, like the type of operations. Such solutions include the introduction of duty cycle strategies for some auxiliary systems and the optimization of process parameters.

Innovative Refrigeration Technology for Machine Tools with Sustainable Refrigerants and Digital Twins

This article investigates the trend of assessing energy efficiency, sustainability and greenhouse gas emissions in the operation of 5- axis milling machine tools. This research aims to predict the cooling load by thermal models control within the main spindle system to ensure that cooling devices are dimensioned adequately and to keep it running under optimal conditions leading to improve the overall efficiency. In order to achieve this goal, a digital twin approach is currently being developed utilizing commercial software which consists of four primary models. A simulation model for material removal is used to predict the mechanical load required for the milling process to finish the CAD model. The second model is the spindle control model to determine the electric currents needed to operate the induction motor at the specified mechanical power. This model provides the electric current data to the lumped-parameter thermal networks (LPTN) model, which is proposed to accurately represent the heat dissipation from the motor and spindle systems towards the cooling channel in the main spindle system. Subsequently, the task at hand involves making an estimate of the necessary outlet temperature derived from the refrigeration unit model, which is essential for effectively covering the thermal energy produced by the spindle system.

Marginal Adaptation of Different Monolithic Zirconia Crowns with Horizontal and Vertical Finishing Lines: A Comparative in Vitro Study

Background: A tooth preparation design determines marginal accuracy, which is crucial to the durability of all-ceramic restorations. Objective: An evaluation of marginal adaptation to different tooth preparation techniques and zirconia materials was conducted in this study. Materials and Methods: Based on the preparation design, 48 human maxillary first premolars in good health were divided into two main groups. Group A (chamfer) and Group B (vertical). Within each main group were three subgroups, comprising eight teeth each, distinguished by the type of zirconia material employed (Zircad LT, MT, and Prime by Ivoclar Vivadent). All samples were prepared by the same operator using a dental surveyor. Intra-oral scanning was performed on the prepared teeth. SironaInLab CAD 20.0 software was used to design crowns, which were subsequently generated using a 5-axis milling machine. Crowns were bonded to their corresponding teeth using self-adhesive resin cement. Marginal gap measurements were taken in micrometers ( m) before and after cementation at sixteen sites per sample using a digital microscope at 230x magnification. The collected data were evaluated using statistical analysis using the independent t-test, paired t-test, and ANOVA, with a 0.05 significance level. Results: The vertical preparation group exhibited the smallest marginal gap, while the chamfer group displayed the largest. This disparity was statistically significant across all materials for both pre-and post-cementation measures. The differences between monolithic zirconia crowns were not statistically significant. Conclusion: The vertical preparation design illustrated significantly better marginal adaptation than the chamfer preparation design; materials comparisons showed a comparable marginal gap. The mean value of the marginal gap after cementation significantly increased in all groups.

Marginal adaptation of different monolithic zirconia crowns with horizontal and vertical finish lines: A comparative in vitro study.

This study evaluated the influence of different tooth preparation techniques and zirconia materials on marginal adaptation. Forty-eight healthy human maxillary first premolars were divided into two primary groups based on preparation design: group A (chamfer) and group B (vertical). Within each main group, there were three subgroups, comprising eight teeth each, distinguished by the type of zirconia material employed (Zircad LT, MT, and Prime by Ivoclar Vivadent). All the samples were prepared by the same operator using a dental surveyor. Intraoral scanning was performed on the prepared teeth. SironaInLab CAD 20.0 software was used to design crowns, which were subsequently generated using a 5-axis milling machine. The crowns were cemented to their respective teeth with self-adhesive resin cement. Marginal gap measurements were taken in micrometers (μm) before and after cementation at 16 sites per sample using a digital microscope at×230 magnification. The collected data were evaluated using statistical analysis using the independent t-test, paired t-test, and ANOVA at an 0.05 significance level. The vertical preparation group exhibited the smallest marginal gap, while the chamfer group displayed the largest. This disparity was statistically significant (P<0.05) for pre- and post-cementation measurements across all materials. There were no significant differences between the different monolithic zirconia crowns. The vertical preparation design illustrated significantly better marginal adaptation than the chamfer preparation design. Comparisons between materials showed comparable marginal gaps. The mean values of the marginal gaps in all groups increased significantly after cementation.

A comparative analysis of the passivity of fit of complete arch implant-supported frameworks fabricated using different acquisition techniques

Statement of problemThe accuracy of intraoral scanners (IOSs) in recording edentulous jaws has improved recently. However, improvement in accuracy does not necessarily imply the clinical validity of the scans, and limited information is available regarding the manufacture of passively fitting prostheses. PurposeThe purpose of this in vitro study was to analyze the passivity of complete arch screw-retained frameworks fabricated using different acquisition techniques. Material and methodsA 3-dimensional maxillary edentulous model to receive all-on-4 screw-retained frameworks was prototyped. Eighteen polymethylmethacrylate (PMMA) frameworks were fabricated with a 5-axis milling machine and divided into 3 groups according to the acquisition technique (n=6): scanned by using an IOS (CEREC Primescan; Dentsply Sirona), scanned with the aid of an auxiliary device by using the same IOS, and by using a conventional impression and then scanning the stone cast with an extraoral scanner (EOS). The passivity of fit of the frameworks was tested with the 1-screw test, the terminal screw of the framework assembly was tightened on the multiunit abutment (MUA), and the vertical marginal gap (µm) was measured at the other 3 framework-to-abutment interfaces by using a digital microscope at ×40 magnification. A modification to the 1-screw test was analyzed by tightening all screws and then unscrewing all except 1 of the anterior abutments. Data were explored for normality by using the theoretical quantile-quantile (Q-Q) plots and the Shapiro-Wilk test of normality. The Friedman test compared data between the different acquisition techniques; the tightening methods and locations (buccal and palatal) were used as the block variable. The post hoc Dunn test was used when the Friedman test was significant. The Kruksal-Wallis test compared the data from the 2 groups of the tightening methods and the 2 location groups. The aligned rank transformation (ART) ANOVA test was used for the interaction effects among the 3 variables. A multiway ANOVA was applied to the ranked data. (α=.05 for all tests). ResultsSignificant differences were found among all groups (P<.001). Regarding the passivity of fit, the mean vertical marginal gap was 50 µm for frameworks fabricated from an intraoral scan with the aid of an auxiliary device, 62 µm for frameworks fabricated by using an IOS, and 140 µm for frameworks fabricated by using an EOS. No significant difference was found among all groups regarding the tightening method (P=.355) or location measured (P=.175). ConclusionsDigital scanning with the aid of an auxiliary device resulted in the best fit; however, digital approaches with or without the auxiliary device resulted in a more accurate fit with a smaller marginal gap than with the conventional impression.

A case study of hybrid manufacturing of a Ti-6Al-4V titanium alloy hip prosthesis

Hybrid manufacturing (HM) is a process that combines additive manufacturing (AM) and subtractive manufacturing (SM). It is becoming increasingly recognized as a solution capable of producing components of high geometric complexity, while at the same time ensuring the quality of the surface finish, rigour and geometric tolerance on functional surfaces. This work aims to study the surface finish quality of an orthopaedic hip resurfacing prosthesis obtained by HM. For this purpose, test samples of titanium alloy Ti-6Al-4V using two Power Bed Fusion (PBF) processes were manufactured, which were finished by turning and 5-axis milling. It was verified that, upon the machining tests, no differences in Ra and Rt were found between the various types of AM. Regarding the type of SM used, 5-axis milling provided lower roughness results with a consistent value of Ra = 0.6 µm. The use of segmented circle mills in 5-axis milling proved to be an asset in achieving a good surface finish. This work successfully validated the concept of HM to produce a medical device, namely, an orthopaedic hip prosthesis.As far as surface quality is concerned, it could be concluded that the optimal solution for this case study is 5-axis milling.

Analytical method to extract tool workpiece engagement from CAM data for five-axis machining stability prediction

Ball end milling cutters are commonly used for precision machining of complex curved parts in five axis CNC systems. To solve the problem of difficulty in adjusting the spindle speed to achieve stable milling during the five axis milling process of ball end cutters, this paper presents an analytical method for extracting the tool-workpiece engagement (TWE) from computer-aided manufacturing (CAM) data. This method extracts the TWE between the end portion of the ball-end mill and the surface of the workpiece during the processing of free-form surfaces, including slotting, first cutting, and following cutting. Further, the TWE extracted by this method is applied for constructing the cutting force model. The entry and exit angles for each of the micro-element cutting edges under different tool postures are obtained through the conversion matrix, and an efficient full discretization method is used for predicting the stability of the five-axis machining in the slotting mode. Finally, the accuracy and efficiency of the analytical method are verified through simulation and experimentation. The experimental results show that the efficiency of the proposed method increases by about 69% when compared to the arc-surface intersection method and that the predicted value of the five-axis machining stability shows good agreement with the experimental results.

A real-time intelligent method to identify mechanistic cutting force coefficients in 3-axis ball-end milling process using stochastic gradient decent: the mechanistic network

A real-time intelligent method to identify mechanistic cutting force coefficients in 3-axis ball-end milling process using stochastic gradient decent: the mechanistic network

Circular, zero waste formwork - Sustainable and reusable systems for complex concrete elements

The construction sector contributes significantly to global carbon emissions, leading to a new need and demand for sustainable and material-efficient construction technologies. Digital form-finding, simulation, and optimization methods are advancing, resulting in highly efficient, but often geometrically complex components. Concrete construction, which is currently dominant worldwide and crucial for sustainable material savings due to its large market volume, still faces challenges in implementing complex geometries. The significant requirements for formwork material and limitations in feasibility and cost at the current state of the art contribute to these challenges. This research presents a zero waste process using recyclable and reusable digitally fabricated formwork made from waste ingredients that can be immediately implemented in the construction industry. Residual sands (quartz and ceramics) were investigated as a basic moulding material in combination with biogenic binders (bentonite, eco-resin, sodium silicate, starch) for the production of stable formwork composites. The material compound were shaped into precise complex forms using 5-axis milling, and the removed material was recycled in a closed material cycle. Testing and characterization methods for evaluating mechanical properties such as compressive forces (20.1 N/mm2), surface roughness (Ra 9.1 μm), tolerances (0), and moulding processes indicate that the presented procedure conforms to common industry standards. Demonstrating feasibility, complex ultra-thin 1:1 concrete prototypes were designed and manufactured under industrial conditions using prefabricated formworks made of researched bio composite. The resulting high-resolution formwork surfaces and exposed concrete precast elements correspond to the highest fair-faced concrete class (SB04), with line roughness values of Ra 14.4 μm. The developed circulation concept allows reproducibility of different geometries and repeated concreting of formwork moulds. The formwork process is free from harmful additives, enabling recycling through grinding and reintegration into a closed material cycle. Sustainability has been continuously monitored and evaluated through a life cycle assessment. This system utilizes standard machines and offers an accessible and easily integrated approach for a holistic zero waste solution, suitable for efficient industrial applications.

A new geometric approach for real-time cutting force simulation in 3-axis ball-end milling compatible with graphical game engines

A new geometric approach for real-time cutting force simulation in 3-axis ball-end milling compatible with graphical game engines

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.