Machining Tool Path Research Articles

Research on Speed Planning in the Constant Speed Interval and Quality Prediction on the Transition Surface

Aiming at the particularity on the transition surface, this paper carried out research on adaptive speed planning, local optimization of machining toolpaths to improve the surface quality of the transition surface, and visualization of motion parameters to predict the surface quality of the transition surface. Constant speed interval planning and trajectory optimization were carried out on the transition surface between the bottom of a Cola bottle and the curved surface with variable curvature, respectively, and the visualization maps before and after optimization were obtained. The comparison showed that the motion parameters of the optimized visualization map had better smoothness. Further, the effectiveness of the estimated surface quality was verified through the actual machining of the variable curvature transition surface and Wuzhi mountain parts. The consistency of the improvement of the processed surface quality and the quality of the visualization were verified.

Research and Application of CNC Machining Method Based on CAD/CAM/Robot Integration

In order to improve the effect of intelligent CNC machining, this paper combines the CAD/CAM/Robot integration method to improve the CNC machining method and analyzes the tool path planning method and the path generation algorithm of the five-axis CNC machining machine. Through the tool processing calculation of the representative curved surface, this paper studies the basic theory, process planning, and tool parameter selection of the blade of the representative curved surface in the five-axis CNC machining and generates the blade CNC machining tool path through the simulation software. In addition, this paper analyzes the trajectory of the workpiece through the intelligent processing process and builds an intelligent processing system. Through the statistics of simulation test data, it can be seen that the CNC machining method based on CAD/CAM/Robot integration can effectively improve the intelligence of modern CNC machining and improve the effect of intelligent machining.

Integrated Interface System of STEP Data Models for the Tool Path Generation

The STEP (STandard for the Exchange of Product model data) is a worldwide standard for exchanging products between diverse computer systems and industrial applications. STEP files (ISO 10303) contain 3D data in the universal data format with a boundary representation (B-rep) that allows the exchange of data models between CAD, CAM, and CNC systems. Traditionally, G-code generation relies on CAM software as an add-on, which incurs significant installation costs. The purpose of this paper is to describe the development of an Integrated Interface System (I2S) for Tool Path Generation (TPG) for the CNC milling operations utilizing neutral STEP files.The algorithm was interpreted in Hypertext Preprocessor (PHP) programming and produced a computer interface system that is capable to convert STEP file geometric data to G-code format.The geometric features of the sample block were modeled using a 3D CAD model. The result was validated using machining simulation, and the machining is performed on a three-axis CNC milling machine with a PC-based controller.In modern manufacturing systems based on Open Architecture Controller (OAC), the development of the I2S provides an alternative to generating machining tool paths and G-code by intercepting CAM software.

Linear interpolation algorithm of machining tool path with curvature smoothing

This paper presents a novel corner smoothing local method for computer numerical control machine. Under normal circumstances, most tool path is made up of hundreds or thousands of tiny straight segments called G01. Then, local smoothing is achieved by interpolation through splines or curves that are well-known to us. In this study, a new technique for corner smoothing is realized directly under kinematic limits and geometric constraints. Instead of utilizing the familiar local corner smoothing that are acquainted with the academic research of predecessors and accumulated experience in practice, employing this novel algorithm accurately gains smoother cornering trajectory, acceleration, and stabilized velocity such that delivers an optimal motion. Experimental validation explicitly demonstrates effectiveness of reducing cycle time and interpolate precisely for micro-line trajectory in machining.

Tool Path Generation Algorithm Based on Rough Machining of Jade Carving Surface

To improve the quality of tool paths in surface machining, different machining requirements are considered in the tool path generation algorithm. In the traditional tool path generation algorithm, due to the lack of a unified mathematical calculation framework, these requirements often need to be considered separately, but they often compete with each other, so that different requirements cannot be satisfied at the same time and the tool path cannot achieve the optimal. To resolve this issue, an extensive tool path generation algorithm framework for arbitrary surfaces was proposed. The proposed algorithm transforms the tool path calculation framework into a constrained functional optimization problem by establishing an optimization function based on the potential energy field and an inequality function based on the gradient field in the machining area. By establishing finite element approximation, the functional optimization problem is transformed into a numerical optimization problem, which reduces the difficulty of solving. According to the machining requirements of die surface such as tool path smoothness, line width constraint and cutting direction constraints were transformed into the constraints of potential energy field isopotential line, and the method of generating reciprocating cutter path and cutter contact path isosection cutter path was proposed by optimizing the method. It is evident from the simulation and machining experiments results that continuous and smooth tool paths can be generated by using this algorithm, and machining quality and machining efficiency can be improved. By adding different machining requirements into the framework, a tool path with different optimization objectives can be generated.

Online interpolation of 5-axis machining toolpaths with global blending

Modern high-speed 5-axis machining toolpaths consist of densely discretized tool center points (TCP) and tool orientation vectors (TOV). This paper presents a global interpolation technique that can blend very densely discretized 5-axis toolpaths within user defined blending tolerance and interpolate them in real-time using minimal computational expense. Instead of geometric splines, Finite Impulse Response (FIR) low-pass filtering is used to blend TCP and TOV and interpolate them smoothly for synchronized 5-axis motion generation. Global blending errors of TCP and TOV are modeled based on path geometry, tool motion kinematics and dynamics of the FIR filter. These global blending errors are confined by modulating the machining feedrate. In other words, machining feedrate is adjusted, i.e. reduced and increased, to control the global blending accuracy along the 5-axis machining toolpath. A windowing scheme is proposed to solve this new feedrate scheduling problem. Since the proposed interpolation method is based on digital filtering (convolution), it enables online (real-time) interpolation of densely discretized 5-axis machining toolpaths in a real-time and at the same time provides control over the frequency spectrum of interpolated trajectories. The proposed global blending strategy delivers significant reduction in machining cycle-time as compared to conventional local blending techniques and generates smoother, frequency-controlled trajectories with a fraction of the computational effort required as compared to spline-based interpolation. Illustrative examples and experimental results are provided to showcase functionality and validate effectiveness of the proposed technique.

Accurate prediction of machining cycle times by data-driven modelling of NC system's interpolation dynamics

Accurate prediction of cycle times of machining part programs plays a crucial role in process planning and part flow optimization on shop floors. This paper presents a data-driven approach to model the trajectory generation (interpolation) strategy embedded in the Numerical Control (NC) system of CNC machine tools to accurately predict their machining cycle times. Artificial Neural Networks (ANN) are trained to learn and accurately mimic how the CNC plans its feedrate profile as it accelerates, decelerates, and interpolates along complex part programs. Proposed approach is validated experimentally and shown to predict machining cycle times with >95% accuracy along tested complex machining toolpaths.

Hybrid Line-Arc Toolpath Machining with Corner Transition and Grouping Lookahead Scheme

Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD data mining, CAD and the internet, CAD education, genetic algorithms and CAD engines. The journal is aimed at all developers and users of CAD technology to ptovide CAD solutions for various stages of design and manufacturing. The journal publishes all about Computer-Aided Design and Computer-Aided technologies.

Coupling between inherent and machining-induced residual stresses in aluminum components

This work investigates the coupling of inherent residual stress (IRS) and machining-induced residual stress (MIRS) on the final-state of residual stress (FRS) and distortion when high-speed machining (HSM) high aspect-ratio aluminum components. Motivation for this work stems from the simplifications in related numerical investigations that give rise to two limitations: First, the mapping of incompatible, incomplete, and/or spatially scarce IRS profiles generates unrealistic distortions and incorrect stress fields during static equilibration. Second, the simulation of machining via element deletion, inactive elements approach, or Boolean subtraction (removal) of material either ignores thermal and MIRS effects, or implements them based on simplified analytical/empirical models. Such practices therefore prevent a thorough understanding of how IRS and MIRS are coupled. Accordingly, two wrought aluminum 7050 blocks having different IRS profiles (based on stress relief) are considered in this work. An iterative stress reconstruction algorithm is implemented to numerically model a spatially-complete and fully-compatible IRS field in each aluminum block using limited data from slitting measurements documented in the literature. A 2D orthogonal cutting model is used to validate the material and damage models employed, as well as to elucidate the influences of IRS and MIRS on FRS. A 3D end milling model, which adopts the validated material and damage definitions, is then applied with different tool paths to reveal the coupled effects of IRS and MIRS on the distortion when HSM a C-channel featuring high aspect-ratio walls. The results reveal that the interaction between IRS and MIRS is nonlinear in nature, thus contrasting assumptions allowing for their superposition, as are widely reported and adopted in the literature. The results also show that the nonlinear coupling between IRS and MIRS varies according to both the component and location of stress within the machined part. Moreover, the findings reveal that the final part distortion is significantly influenced by the nonlinear coupling, as well as the specific machine tool path implemented.

Contour error modeling and compensation of CNC machining based on deep learning and reinforcement learning

Contour error compensation of the computer numerical control (CNC) machine tool is a vital technology that can improve machining accuracy and quality. To achieve this goal, the tracking error of a feeding axis, which is a dominant issue incurring the contour error, should be firstly modeled and then a proper compensation strategy should be determined. However, building the precise tracking error prediction model is a challenging task because of the nonlinear issues like backlash and friction involved in the feeding axis; besides, the optimal compensation parameter is also difficult to determine because it is sensitive to the machining tool path. In this paper, a set of novel approaches for contour error prediction and compensation is presented based on the technologies of deep learning and reinforcement learning. By utilizing the internal data of the CNC system, the tracking error of the feeding axis is modeled as a Nonlinear Auto-Regressive Long-Short-Term Memory (NAR-LSTM) network, considering all the nonlinear issues of the feeding axis. Given the contour error as calculated based on the predicted tracking error of each feeding axis, a compensation strategy is presented with its parameters identified efficiently by a Time-Series Deep Q-Network (TS-DQN) as designed in our work. To validate the feasibility and advantage of the proposed approaches, extensive experiments are conducted, testifying that our approaches can predict the tracking error and contour error with very good precision (better than about 99% and 90% respectively), and the contour error compensated based on the predicted results and our compensation strategy is significantly reduced (about 60~85% reduction) with the machining quality improved drastically (machining error reduced about 50%).

Interactive Learning and Application of Virtual Simulation Machining of CNC Machine Tools based on VERICUT

As a powerful numerical simulation software, VERICUT set processing, precision testing and simulation of machine Settings, process optimization, the cutting and residual contrast functions in one, can let the user experience to the machining tool path and the occurrence of various collision, can be a change in time, avoid to cause unnecessary loss. In this paper, the existing vertical machining machine VMC850, processing a convex table parts, and further introduce the specific functions of VERICUT.

STEP-NC Compliant Intelligent CNC Milling Machine with an Open Architecture Controller

A STEP-NC or ISO 14649 compliant machine controller is developed, using Open Architecture Control technology for a three-axis Computer Numerical Control milling machine in this research. The controller is developed on a Raspberry Pi single-board computer, using C++ language. This new development is proposed as a low-cost alternative to ISO6983 standard, ensuring continuous integration in the CAD/CAM/CNC chain in machining; thus, it broadens the spectrum of problems handled by conventional CNC systems. The new machine controller is intelligent enough to extract geometrical and manufacturing parameters, cutting tool data, and material data from the STEP-NC file. Accordingly, tool paths for machining can be generated in the controller itself. The shop floor level modification of parameters and the possibility of regeneration of new toolpaths is an added advantage of this new controller. The modified or improved version of the STEP-NC file can be sent back to the CAD/CAM system to close the CAD/CAM/CNC chain. Machine condition monitoring can be achieved by connecting sensors through an available slave I/O board. In the present development, the current drawn by each servo motor is fed back to the controller for cutting condition monitoring. A laboratory scale three-axis CNC milling machine is developed to test the performance of the newly developed controller. The accuracy of positioning, perpendicularity of axes and linearity of this machine are experimentally verified through standard tests. The STEP-NC compliance of the controller is tested and verified, using a STEP-NC program derived based on a sample program given in ISO 14649 standard.

Generation Method of Cutting Tool Paths for High-Speed and High-Quality Machining of Free-Form Surfaces

In general, NC programs for machining free-form surfaces using a computer numerical control (CNC) machine tool are generated using a computer-aided manufacturing (CAM) system. The tool paths (CL data) generated by a CAM system are approximated straight-line segments based on tolerance (allowable error). As a result, the tolerance affects the machining accuracy and time. If the tolerance is set to a small value, the lengths of the segments are shortened, and the machining accuracy is improved. The process in which a CNC machine tool reads and analyzes an NC program and controls the motors requires a minimum processing time of an NC program block (block-processing time). Therefore, if the lengths of the approximated straight-line segments are too small, it will be impossible to reach the indicated feed speed, and the machining time will be longer. In this study, by identifying the block-processing time of a CNC controller and deriving the appropriate length of the approximated straight-line segment based on the block-processing time, a CL data creation method that is capable of high-speed and high-accuracy free-form surface machining is proposed. In addition, experimental verification tests of the method are conducted.

Accurate prediction of machining feedrate and cycle times considering interpolator dynamics

This paper presents an accurate machining feedrate prediction technique by modelling the trajectory generation behaviour of modern CNC machine tools. Typically, CAM systems simulate machines’ motion based on the commanded feedrate and the path geometry. Such approach does not consider the feed planning and interpolation strategy of the machine’s numerical control (NC) system. In this study, trajectory generation behaviour of the NC system is modelled and accurate cycle time prediction for complex machining toolpaths is realised. NC system’s linear interpolation dynamics and commanded axis kinematic profiles are predicted by using finite impulse response (FIR)–based low-pass filters. The corner blending behaviour during non-stop interpolation of linear segments is modelled, and for the first time, the minimum cornering feedrate that satisfies both the tolerance and machining constraints has been calculated analytically for 3-axis toolpaths of any geometry. The proposed method is applied to 4 different case studies including complex machining toolpaths. Experimental validations show actual cycle times can be estimated with > 90% accuracy, greatly outperforming CAM-based predictions. It is expected that the proposed approach will help improve the accuracy of virtual machining models and support businesses’ decision-making when costing machining processes.

Adaptive spiral tool path generation for computer numerical control machining using point cloud

This paper reports a novel method to generate adaptive spiral tool path for the CNC machining of complex sculptured surface represented in the form of cloud of points without the need for surface fitting. The algorithm initially uses uniform 2 D circular mesh-grid to compute the cutter location (CL) points by applying the tool inverse offset method (IOM). These CL points are refined adaptively till the surface form errors converge below the prescribed tolerance limits in both circumferential and radial directions. They are further refined to eliminate the redundancy in machining and generate optimum region wise tool path to minimize the tool lifts. The NC part programs generated by our algorithm were widely tested for different case studies using the commercial CNC simulator as well as by the actual machining trial. Finally, a comparative study was done between our developed system and the commercial CAM software. The results showed that our system is more efficient and robust in terms of the obtained surface quality, productivity, and memory requirement.

Optimization of Tool Path for Surface Machining Based on Accuracy

Surface machining is the key technology in numerical control (NC) machining, and the planning of tool path is the basis and key of NC programming. Based on the improvement of the precision and efficiency of surface machining, this work analyzes the approximation machining error of NC machining of multi-coordinate surface. The tool step and calculation of cutting distance for tool path are discussed. The principle of tool path planning during surface NC machining programming is proposed, and the track verification is carried out with examples.

The control of machining errors of tool path for unequal diameter flank milling of globoidal cam

The profile error is inevitable in the machining process of globoid cam. In order to tackle the problem of normal vector anisotropy in unequal diameter machining, the offset point optimization algorithm is served to optimize the tool position according to the error transfer relationship of equidistant surfaces and the characteristics of unequal diameter tool path generation. In this paper, a bidirectional search algorithm is devised to minimize the deviation between unequal diameter machining tool path surface and fitting ruled surface. The optimal numerical solution with high accuracy is obtained by genetic algorithm. And then the end points of the tool axis are regarded as the initial data. Inverse interpolation of the NURBS (Non-Uniform Rational B-Spline) interpolation is utilized to reconstruct the ruled surface of the flank milling tool path. The simulation results verify the effectiveness of the proposed approach. Compared with the existing methods, the presented one reduces the machining error greatly.

Simulation of manufacturing strategy of an orthotic boots shoe insole product with a Computer-Aided Manufacturing for club foot patient

In this paper, the design of orthotic boots in the club foot patient is investigated concerning the optimum condition of cutting parameters using computer-aided manufacturing. 3D CAD model insole is obtained from the scanning process until the design phase using reverse innovative design method. 3D CAD Model insole is designed using curve Base Modeling. From this design, simulated optimization can be obtained from Computer-Aided Manufacturing (CAM). Optimal manufacturing time optimization is simulated on the CNC Milling machine with the Taguchi approach. Six selected parameters containing toolpath machining, feed rate, spindle speed, depth of cut, Cutter selection, and insole dimension size are of particular interest. It is found that the design layout L2736 gives the most optimal simulation manufacturing using toolpath strategy tep and shallow finishing with spindle speed 1500 rpm, STEPD down 3 mm, Step over 2 mm, and 2mm Cutter diameter, on the model tolerance size 0.75 mm.

Geodesic Distance Field-Based Process Planning for Five-Axis Machining of Complicated Parts

Abstract A critical task in multi-pass process planning for the five-axis machining of complicated parts is to determine the intermediate surfaces for rough machining. Traditionally, the intermediate surfaces are simply parallel Z-level planes, and the machining is of the simplest three-axis type. However, for complicated parts, this so-called Z-level method lacks flexibility and causes isolated islands on layers, which require extraneous air movements by the tool. Moreover, the in-process workpiece machined according to the Z-level method suffers from the staircase effect, which often induces unstable dynamic problems on the tool-spindle system. In this paper, we propose a new method of planning a five-axis machining process for a complicated freeform solid part. In our method, the intermediate surfaces are no longer planar but curved, and they are intrinsically influenced by the convex hull of the part. The powerful algebraic tool of geodesic distance field is utilized to generate the desired intermediate surfaces, for which collision-free five-axis machining tool paths are then planned. In addition, we propose a novel idea of alternating between the roughing and finishing machining operations, which helps improve the stiffness of the in-process workpiece. Ample physical cutting experiments are performed, and the experimental results convincingly confirm the advantages of our method.

Research on Subpixel Algorithm of Fixed-Point Tool Path Measurement.

Tool safety is an important part of machining and machine tool safety, and machine tool path image detection can effectively obtain the in-machine condition of a tool. To obtain an accurate image edge and improve image processing accuracy, a novel subpixel edge detection method is proposed in this study. The precontour is segmented by binarization, the second derivative in the neighborhood of the demand point is calculated, and the obtained value is sampled according to the specified rules for curve fitting. The point whose curve ordinate is 0 is the subpixel position. The experiment proves that an improved subpixel edge can be obtained. Results show that the proposed method can extract a satisfactory subpixel contour, which is more accurate and reliable than the edge results obtained by several current pixel-level operators, such as the Canny operator, and can be used in edge detection with high-accuracy requirements, such as the contour detection of online tools.