Search Results (19)

The manufacturing of freeform optical lenses, essential for advanced applications such as Earth observation and laser fusion, demands exceptional surface accuracy and lightweight designs. However, their complex, non-symmetrical geometries present significant manufacturing challenges. Conventional CNC machining strategies, which rely on fixed Cartesian step sizes, are inherently inefficient for surfaces with rapidly varying curvature. This inadequacy results in non-uniform material removal, prolonged machining times, and substandard surface quality. This study presents a novel curvature-adaptive machining strategy based on dynamic tangential toolpath optimization. The method continuously aligns the toolpath with the local surface geometry to maintain uniform cutting conditions. A dedicated computer-aided manufacturing (CAM) software environment was developed to generate the optimized toolpaths and corresponding G-code. Experimental validation on representative freeform optics demonstrated a substantial improvement in precision: a single error-compensation iteration achieved a reduction in peak-to-valley form error of up to 48.4%. The results confirm that the proposed strategy significantly outperforms conventional fixed-step methods, delivering superior surface finish, reduced machining time, and enhanced process flexibility without requiring specialized hardware. This work establishes a practical and high-precision advancement for the manufacture of high-performance freeform optical systems. Full article

This study tackles the challenge of achieving high-precision robotic machining of elastic materials, where elastic recovery and overcutting often impair accuracy. To address this, a novel milling strategy, RAPSO, is introduced by combining an adaptive particle swarm optimization (APSO) algorithm with a reinforcement learning (RL)-based compensation mechanism. The method builds a material-specific milling model through residual error characterization, incorporates a dynamic inertia weight adjustment strategy into APSO for optimized toolpath generation, and integrates a Proximal Policy Optimization (PPO)-based RL module to refine trajectories iteratively. Experiments show that RAPSO reduces residual material by $33.51\%$ compared with standard PSO and APSO methods, while offering faster convergence and greater stability. The proposed framework provides a practical solution for precision machining of elastic materials, offering improved accuracy, reduced post-processing requirements, and higher efficiency, while also contributing to the theoretical modeling of elastic recovery and advanced toolpath planning. Full article

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths. Full article

Additive manufacturing (AM) methods have been gaining momentum because they provide vast design and fabrication possibilities, increasing the accessibility of state-of-the-art hardware through recent developments in user-friendly computer-aided drawing/engineering/manufacturing (CAD/CAE/CAM) tools. However, in comparison to the conventional manufacturing methods, AM processes have some disadvantages, including the machining precision and fabrication process times. The first issue has been mostly resolved through the recent advances in manufacturing hardware, sensors, and controller systems. However, the latter has been widely investigated by researchers with different toolpath planning perspectives. As a contribution to these investigations, the present study proposes a toolpath planning method for AM, which aims to provide highly continuous yet distance-optimized solutions. The approach is based on the utilization of the signed distance field (SDF), clustering, and minimization of toolpath distances among cluster centroids. The method was tested on various geometries with simple closed curves to complex geometries with holes, which provides effective toolpaths, e.g., with relative distance reduction percentages up to 16.5% in comparison to conventional rectilinear infill patterns. Full article

From an industrial point of view, the milling of $2.5D$ cavities is a frequent operation, consuming time and presenting optimization potential, especially through a judicious choice of the tool trajectory. Among the different types of trajectories, some have a general spiral-like aspect and can potentially offer a reduced machining time. They are called curvilinear trajectories and are obtained by interpolation between structure curves, which are the numerical solutions of a partial differential equation. In this case, the machine tool will connect points, and the trajectory will be made up of small segments. While these trajectories exhibit all the necessary qualities on a macroscopic level for rapid tool movement, the tangential discontinuities at a microscopic scale, inherent in the discretization, significantly increase the machining time. This article proposes a method to reparameterize the structure curves of the curvilinear spiral with a set of $C^2$ connected Hermit quartic spline patches. This creates a smooth toolpath that can be machined at an average feedrate closer to the programmed one and will, de facto, reduce the machining time. This article shows that the proposed method increases on two representative geometries of cavities and toolpath quality indicators, and reduces the milling time from $10\%$ to $18\%$ as compared to the PDE curvilinear spiral generation method proposed by Bieterman and Sandström. In addition, the proposed method is suitable for any non-convex pocket, with or without island(s). Full article

Path planning (PP) is fundamental in the decision-making and control processes of computer numerical control (CNC) machines, playing a critical role in smart manufacturing research. Apart from improving optimization in PP, enhancing efficiency while decreasing CNC machine cycle time is important in manufacturing. Many methods have been offered in the literature to improve the cycle time for obtaining optimal trajectories in toolpath optimization, but these methods are mostly considered for improvements in path length or machining time in optimal PP. This study demonstrates a method for creating a smoothing path. It aims to minimize both cycle time and toolpath length, while demonstrating that the non-dominated sorting genetic algorithm (NSGA-II) is efficient in addressing the multi-objective PP problems within static situations. Pareto optimality for performance comparisons with multi-objective genetic algorithms (MOGAs) is presented in order to highlight the positive features of the non-dominant solving generated by the NSGA-II. According to the comprehensive analysis results, the optimization of the path carried out with the NSGA-II emphasizes its shorter and smoother attributes, with the optimal trajectory achieving approximately 30% and 7% reductions in path length and machining cycle time, respectively. Full article

Trochoidal milling is an efficient strategy for the rough machining of difficult-to-cut materials. The true trochoidal toolpath has C² continuity and avoids sharp changes in engagement angle and cutting load, resulting in smooth machine tool movement. However, its total length is too long, and its engagement angle is uneven. These factors limit further improvements in the material removal rate. Based on the true trochoidal toolpath model, this paper develops an ellipse-based trochoidal toolpath generation method by introducing a compression ratio in the trochoidal step direction. The analytical model of engagement angle and the mechanistic model of the cutting force are proposed. A series of simulations and milling experiments were conducted to analyze the effects of toolpath parameters on the engagement angle and the cutting force. The results show that the compression ratio has the most significant effects. A compression ratio of 50% is optimal, using which the total toolpath length is reduced by 34.0%, and the variance of the engagement angle is reduced by 31.2% compared with that of the true trochoidal toolpath. The profile of the total cutting force corresponds to that of the engagement angle. Full article

The present work focusses on the research of the plastic deformation accumulated effect obtained after two different plastic deformation treatments, over the fatigue life of AISI 304 austenitic stainless steel. The research is focused on ball burnishing as a finishing process to form specific, so-called “regular micro-reliefs” (RMRs) on a pre-rolled stainless-steel sheet. RMRs are formed using a CNC (Computerized Numerically Controlled) milling machine and toolpaths with the shortest unfolded length, generated by an improved algorithm, based on the Euclidean Distance calculation. The effect of the predominant tool trajectory direction during the ball burnishing process (which can be coinciding or transverse with the rolling direction), the magnitude of applied deforming force, and feed-rate is subjected to evaluation using Bayesian rule analyses of experimentally obtained results for the fatigue life of AISI 304 steel. The obtained results give us reason to conclude that the fatigue life of researched steel is increased when directions of pre-rolled plastic deformation and the tool movement during ball burnishing are coincident. It also been found that the magnitude of deforming force has a stronger impact over the fatigue life, than the feed-rate of the ball tool. Full article

The envisaged flexibility of Single Point Incremental Forming is contradicted by its highly complex deformation behavior, making the process easy to implement but difficult to fully control. This paper describes a regression method that uses Gradient Tree Boosting to predict the deviations for a given input geometry, which can replace the physical part production needed for the optimization of generating toolpaths. This paper elaborates on the calculation of the geometric features used by the regressor and the selection of an appropriate training dataset. The method is validated using a generated dataset of fully freeform ellipsoid workpiece geometries. Full article

Robot manufacturing involves continuous path control, which is now available for both robotic controllers and CAM software packages. However, CAM solutions are focused on generating the code for the robotic structure to follow the toolpath, without taking into consideration the dynamics and energy consumption. In this study, robot incremental forming was considered as the manufacturing process, and a simulation model, based upon Matlab-Simulink Simscape Multibody technology, was developed. The proposed model was fed with the trajectory information generated by the CAM program, and using an inverse kinematics function, it was able to generate the commands to drive the robotic structure on the technological toolpaths. The model was also used to study the dynamic behavior of the robot; external experimental data from a 3D force sensor were fed to the model to include the influence of the technological forces which appeared during the incremental forming process. Thus, using the proposed model in conjunction with the external CAM software, the influence of the workpiece position upon the joint torques could be estimated, opening the way for future optimization. The shortcomings of the model, mainly involving inaccurate information with regard to the physical properties of the robotic structure, were addressed by subtracting the dry-run joint torques from those obtained from the technological process. Full article

The three-dimensional (3D) printing technique for cement-based materials has been actively investigated and utilized in civil engineering. However, there is no systematic review of the fabricating devices. This paper reviews the software and hardware for extrusion-based 3D concrete printing. Firstly, a dedicated tool path generating software is urgently needed to meet the cementitious printing applications and to improve printing quality with toolpath optimizations. Secondly, the existing printing equipment was summarized and discussed, concluding the pros and cons of various 3D motion systems, material systems, and nozzle units. Suitable choices for scientific research and engineering applications were recommended. The reinforcing techniques were categorized and concluded with the existing drawbacks and the research trend. A hybrid manufacturing system of 3D printing and the reinforcing technique was then proposed with a system diagram and flowchart. Full article

Most aerospace parts are thin walled and made of aluminum or titanium alloy that is machined to the required shape and dimensions. Deformation is a common issue. Although the reduced cutting forces used in high-speed milling generate low residual stress, the problem of deformation cannot be completely resolved. In this work, we emphasized that choosing the correct cutting parameters and machining techniques could increase the cutting performance and surface quality and reduce the deformation of thin plates. In this study, a part made of a thin 6061 aluminum alloy plate was machined by high-speed milling (HSM), and a Taguchi L16 orthogonal array was used to optimize the following parameters: linear velocity, feed per tooth, cutting depth, cutting width, and toolpath. The impact of cutting parameters on the degree of deformation, surface roughness, as well as the cutting force on the thin plate were all investigated. The results showed that the experimental parameters for the optimal degree of deformation were A1 (linear velocity 450 mm/min), B1 (feed per tooth 0.06 mm/tooth), C1 (cutting depth 0.3 mm), D4 (cutting width 70%), and E4 (rough zigzag). Feed per tooth was the most significant control factor, with a contribution as high as 63.5%. It should also be mentioned that, according to the factor response of deformation, there was a lower value of feed per tooth and less deformation. Furthermore, the feed per tooth and the cutting depth decreased and the surface roughness increased. The cutting force rose or fell with an increase or decrease of cutting depth. Full article

Deburring is recognized as an ideal technology for robotic automation. However, since the low stiffness of the robot can affect the deburring quality and the performance of an industrial robot is generally inhomogeneous over its workspace, a cell setup must be found that allows the robot to track the toolpath with the desired performance. In this work, the problems of robotic deburring are addressed by integrating components commonly used in the machining industry. A rotary table is integrated with the robotic deburring cell to increase the effective reach of the robot and enable it to machine a large workpiece. A genetic algorithm (GA) is used to optimize the placement of the workpiece based on the stiffness of the robot, and a local minimizer is used to maximize the stiffness of the robot along the deburring toolpath. During cutting motions, small table rotations are allowed so that the robot maintains high stiffness, and during non-cutting motions, large table rotations are allowed to reposition the workpiece. The stiffness of the robot is modeled by an artificial neural network (ANN). The results confirm the need to optimize the cell setup, since many optimizers cannot track the toolpath, while for the successful optimizers, a performance imbalance occurs along the toolpath. Full article

In numerical control (NC)-based machining, NC data-based tool paths affect both quality and productivity. NC data are generated according to cutting conditions. However, NC data causing excessive cutting load can accelerate tool wear and even result in tool damage. In the opposite case, increasing machining time can affect productivity. NC data can influence surface quality from the perspective of cutting dynamics according to machine tool–material–tool combination. There have been a lot of studies on tool-path optimization. However, it is impossible to perfectly predict cutting dynamics such as tool wear, material non-uniformity, chatter, and spindle deformation. In fact, such prediction-based tool-path optimization can cause errors. Therefore, this study attempts to synchronize spindle load and NC data and uniformize the machining load through the analysis of stored data using digital-twin technology, which stores and manages machining history. Uniformizing machining load can reduce rapid traverse in the event of no load, feed rate in an overload area, and shock on a tool when the tool and material are met by adding approach feed. Analyzing results of the attempts proposed in this paper, the chatter was completely removed in the machining with D100 and D16, although some chatter remained in the machining with D25 and D16R3 tools. In addition, the processing time could be reduced from a minimum of 7% to a maximum of 50% after optimization. Full article

Additive manufacturing (AM) is an arising production process due to the possibility to produce monolithic components with complex shapes with one single process and without the need for special tooling. AM-produced parts still often require a machining phase, since their surface finish is not compliant with the strict requirements of the most advanced markets, such as aerospace, energy, and defense. Since reduced weight is a key requirement for these parts, they feature thin walls and webs, usually characterized by low stiffness, requiring the usage of low productivity machining parameters. The idea of this paper is to set up an approach which is able to predict the dynamics of a thin-walled part produced using AM. The knowledge of the workpiece dynamics evolution throughout the machining process can be used to carry out cutting parameter optimization with different objectives (e.g., chatter avoidance, force vibrations reduction). The developed approach exploits finite element (FE) analysis to predict the workpiece dynamics during the machining process, updating its changing geometry. The developed solution can automatically optimize the toolpath for the machining operation, generated by any Computer Aided Manufacturing (CAM) software updating spindle speed in accordance with the selected optimization strategies. The developed approach was tested using as a test case an airfoil. Full article