Tool Path Generation Research Articles

A novel approach for adaptive skeleton toolpath generation

Industry 4.0 is revolutionizing manufacturing through the integration of automation and real-time data sharing in cyber-physical systems. At the forefront of this revolution is large-format additive manufacturing. In large-format printing, parts are often designed to be an even number of beads wide to produce a completely dense part. However, voids can still arise. This is often due to the part not being an even number of bead widths wide in some areas, or in geometry containing acute angles, as the process of generating closed contours cannot completely fill the space. Voids can be tolerated in smaller models, but in large-format additive manufacturing they may cause mechanical defects. To fill these voids, open loop paths called skeletons are often used, but they are typically limited by the physical constraints defined in the slicing software. To address this, researchers at Oak Ridge National Laboratory have extended skeleton toolpaths via an adaptive methodology. These adaptive skeletons were found to better fill void spaces through manipulation of physical parameters of the build process and were calculated as part of the slicing process.

An iso-scallop tool path generation method for three-axis machining freeform surface

An iso-scallop tool path generation method for three-axis machining freeform surface

An adaptive singularity avoidance method for five-axis toolpath generation with invariant cutter-contact points and bounded tool orientation variation based on the reduction of Jacobian condition number

To enhance the five-axis machine-tool performance, it is significant to avoid the singular configuration where the kinematic and dynamic performances degrade dramatically. Most existing methods aim at solving this issue by avoiding the singularity posture in the geometric manner. Different from them, this paper aims at avoiding the singular phenomenon by reducing the Jacobian-matrix condition number, and proposes an adaptive singularity avoidance toolpath generation method. This method adds a damping diagonal matrix into the computation of the pseudo-inverse Jacobian matrix to reduce its ill-condition extent during axial path generation, thus solving the singularity phenomenon. However, the adding of damping matrix gives arise to the toolpath error. To ensure the accuracy meanwhile, an adaptive law for determination of the damping matrix is presented to balance the singularity-avoiding effect and the path error, under the constraints of condition number and tool-orientation error-tolerance thresholds, as well as invariant cutter-contact points. Simulation and experimental tests verify that the proposed method can not only realize the singular avoidance without preliminary adjustment of the original toolpath, thus can be realized in real-time NC system, but also has better singular-avoiding performance and lower toolpath error when comparing with typical methods.

Computing smooth preferred feed direction fields with high material removal rates for efficient CNC tool paths

We propose a novel method to compute smooth preferred feed direction fields with high material removal rates to construct CNC tool paths for five-axis machining with ball-end mills. At the core of our method are three new facts about the local maximum feed directions of the material removal rate to facilitate feed direction field optimization. According to these new facts, we develop a practical method to generate desired fields for surfaces with smooth normal directions. Then, the preferred feed direction fields are used to generate tool paths via the existing iso-level method. The experimental results demonstrate the feasibility and advantages of our method. Compared to the state-of-the-art methods, the proposed method achieves a higher efficiency (up to 20.7%).

Effects of Toolpath Parameters on Engagement Angle and Cutting Force in Ellipse-Based Trochoidal Milling of Titanium Alloy Ti-6Al-4V

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.

A Simple Point-based Iso-Scallop Tool Path Planning Method for Noisy Point Clouds with High Robustness and Controlled Errors

With the rapid advances in 3D scanning and vision technologies, point clouds have seen a significant increase in their application to CNC machining. As an important way to generate tool paths from point clouds, point-based direct planning methods are, however, now restricted to high-quality point clouds. Most existing methods would have robustness issues if a noisy point cloud is given due to their reliance on the noise-sensitive estimation of differential properties from point clouds. Error control under noisy point clouds is also rarely considered. This paper presents a robust and error-controlled point-based iso-scallop tool path planning method for CNC machining with ball-nosed cutters. It casts the problem of searching for scallop/CL points to another problem of finding circle-sphere intersection points and the maximum/minimum among them. Both circle-sphere intersections and max/min comparisons are easy to implement and robust. It has also been theoretically proved that the intersections and comparisons can ensure an error bound of 2ϵ on the final results if two conditions called ϵ-sampling and ϵ-covering are met. The effectiveness of the method has been demonstrated by a series of examples and comparisons.

Robot-assisted conformal additive manufacturing for continuous fibre-reinforced grid-stiffened shell structures

ABSTRACT The advents in continuous fibre-reinforced polymer additive manufacturing (CFRP-AM) present unprecedented opportunities for the rapid development of next-generation high-performance composites with selectively and spatially distributed reinforcement. However, the widely adopted 3-degree-of-freedom motion configuration in current CFRP-AM systems hinders the exploration of composite structures with non-planar fibre layouts. This work presents a novel conformal CFRP-AM system to fabricate grid-stiffened shell structures leveraging its multi-DoF motion to pattern spatial features. The system integrates a 6-axis robot with an optimally designed co-extrusion module and operates through a design-to-manufacturing workflow. The proposed workflow includes three steps: system calibration, conformal toolpath generation, and process implementation. The conformal toolpath generation is a surface-mapping-based method that allows a simultaneous exploration of various geometric designs and their toolpaths. Experimental comparisons were made between parts fabricated by different processes, i.e., planar and conformal based, with different toolpaths, i.e., shells filled with zigzag and arc-offset patterns, and with various geometric designs, i.e., stiffener ribs with different crossline angles. The results manifest that the proposed system can significantly improve the compression strength and stiffness of grid-stiffened shell structures. Meanwhile, the additional design freedom on process and structure opens up a new possibility to customise their mechanical performance.

Constructing continuous curves on point-cloud surfaces with Directed Projection Operator

With the development of 3D acquisition technology, the points based representation of complex objects and environment clouds has been widely applied in tool path generation, robot path planning and other fields. A new challenge is to construct continuous curves on point-cloud. We firstly proposed a new energy function to implement directed projection. Most importantly, we transformed the complex energy optimization relative to directed projection into simple numerical iteration named Directed Projection Operator(DPO). Then, by means of the DPO and its approximating surface, we provided two different approaches to construct G2 continuous curves over the point-cloud surface. The constructed curve can not only be embedded into the point-cloud surface, but also be modified locally. A large number of experimental cases have verified the effectiveness and practicability of the proposed algorithms.

Enhancing three-dimensional convolutional neural network-based geometric feature recognition for adaptive additive manufacturing: a signed distance field data approach

Abstract In the context of additive manufacturing, the adjustment of process data to individual geometric features offers the potential to further increase manufacturing speed and quality, while being widely underestimated in recent research. Unfortunately, the current non-uniform data handling in the CAD-CAM-Link results in a downstream data loss, that prevents the availability of geometric knowledge from being present at any time to apply the more advanced approaches of adaptive slicing and tool path generation. Automatic detection of various geometric entities would be beneficial for classifying partial surfaces and volumetric ranges to gain customized informational insights of geometric parameterization. In this work, an enhanced approach of geometric deep learning for the analysis of voxelized engineering parts will be presented to align the inference representations to modeling paradigms for complex design models like architected materials. Although the baseline voxel representation offers distinct advantages in detection accuracy, it comes with an adversely large memory footprint. The geometry discretization leads to high resolutions needed to capture various detail levels that prevent the analysis of fine-grained objects. To achieve efficient usage of three-dimensional (3D) deep learning techniques, we propose a 3D-convolutional neural network-based feature recognition approach using signed distance field data to limit the needed resolution. These implicit geometric data leverage the advantages of volumetric convolution while alleviating their disadvantages through the use of the continuous signed distance function. When analyzing computer-aided design data for geometric primitive features, a common application task in surface reconstruction of reverse engineering the proposed methodology, achieves a detection accuracy that is in line with the accuracy values achieved by comparable algorithms. This enables the recognition of fine-grained surface instances. The unambiguous shape information extracted could be used in subsequent adaptive slicing algorithms to achieve individual geometry-based hatch generation.

Tool path generation for 5-axis flank milling of ruled surfaces with optimal cutter locations considering multiple geometric constraints

Ruled surfaces found in engineering parts are often blended with a constraint surface, like the blade surface and hub surface of a centrifugal impeller. It is significant to accurately machine these ruled surfaces in flank milling with interference-free and fairing tool path, while current models in fulfilling these goals are complex and rare. In this paper, a tool path planning method with optimal cutter locations (CLs) is proposed for 5-axis flank milling of ruled surfaces under multiple geometric constraints. To be specific, a concise three-point contact tool positioning model is firstly developed for a cylindrical cutter. Different tool orientations arise when varying the three contact positions and a tool orientation pool with acceptable cutter-surface deviation is constructed using a meta-heuristic algorithm. Fairing angular curves are derived from candidates in this pool, and then curve registration for cutter tip point on each determined tool axis is performed in respect of interference avoidance and geometric smoothness. On this basis, an adaptive interval determination model is developed for deviation control of interpolated cutter locations. This model is designed to be independent of the CL optimization process so that multiple CLs can be planned simultaneously with parallel computing technique. Finally, tests are performed on representative surfaces and the results show the method has advantages over previous meta-heuristic tool path planning approaches in both machining accuracy and computation time, and receives the best comprehensive performance compared to other multi-constrained methods when machining an impeller.

A Study on Tool Path Generation in 2D Contour Milling of Cycloidal Discs and Rings Used in Cycloidal Reducers

A Study on Tool Path Generation in 2D Contour Milling of Cycloidal Discs and Rings Used in Cycloidal Reducers

Non-planar multinozzle additive manufacturing of thermoset composite microscaffold networks

Material extrusion-based non-planar additive manufacturing (AM) using 6-axis industrial robot arms shows great promise for three-dimensional (3D) printing of non-planar parts, despite its typical use of a single large coarse nozzle and high printing time. Here, a non-planar multinozzle AM method capable of achieving high resolution large-scale 3D printing with short printing time using 6-axis robots is reported. A custom Multinozzle Toolpath Generator (MTG), based on non-planar parameterized surface projection, is used to compute the orientation of a multinozzle extrusion array along the curvature of a 3D scanned substrate. The method is demonstrated by the fast 3D printing of large periodic structures (up to an area of ∼5.2 × 104 mm2 within 20 min) consisting of interconnected epoxy composite microscaffolds on a single curvature sinusoidal surface and a double curvature surface of an actual aircraft casing, with an error of 15 μm. The method could be used for AM in various fields such as tissue engineering, microfluidic channels, and porous acoustic coatings of aircraft components.

Smoothing and compressing algorithm of toolpath with complex contour in NC machining

The continuous short line segment processing method in CNC machining has the defect of frequent fluctuation of feedrate, which affects the quality and efficiency. For this problem, the local and global methods are common solutions. The local method is to insert transition curves at the corners to obtain a smooth toolpath, but this method does not essentially reduce the number of accelerations and decelerations, and it is difficult to insert transition curves between tiny straight sections. Although the global method can obtain smooth tool trajectories, the parametric interpolation method is not suitable for middle- and low-end CNC machine tools. The article proposes an adaptive tool path generation method with the original part contour as the research object and discretizes the NURBS curves into smooth trajectories consisting of large segments of straight lines and circular arcs. The article mimics the crawling characteristics of snakes and designs a double-headed snake algorithm based on the least squares method to implement this process. First, given the start and end points of the curve, two snakeheads search for the maximum linear and circular segments that satisfy the error constraint in the curve direction. The winner will then be selected as the candidate track segment through a competition mechanism. Finally, all trajectory segments are connected to obtain a smooth tool path. Experiments show that the toolpath data of the method in this paper are reduced by 75.56% compared with commercial CAM software when the contour error threshold is the same, and the contour error is reduced by more than one order of magnitude when the number of toolpath segments is equal. In addition, the method in this paper can obtain a smoother machining surface and more stable cutting force, thus achieving a win‒win situation of quality and efficiency.

Automatic Generation of Interference-Free and Posture-Smooth Toolpath for Robotic Belt Grinding of Complex Workpieces

Robotic belt grinding has shown great potential to achieve automatic machining of high-precision parts. However, its productivity in machining complex parts has been greatly limited by the problem that interference-free and posture-smooth toolpath planning is still a time-consuming and labor-intensive job. Therefore, this work presents a fully automatic and practical approach to facilitate interference-free and posture-smooth toolpath planning for robotic belt grinding of complex parts. With this approach, the interference correction spaces in two common belt grinding modes, namely, wheel face grinding and wheel edge grinding, are first established, where various types of interferences and their corresponding correction strategies are modeled. Then, two B-spline posture curves, which represent the rotational motion and translational motion of the workpiece for correcting interference throughout the entire cutter contact curve, are presented. With the two B-spline curves, a toolpath planning algorithm for robotic belt grinding of complex parts is further developed based on surface partitioning and iteratively correcting interference and smoothing grinding postures. The effectiveness and practicability of the proposed approach are validated by simulations and experimental studies, which demonstrates that the authors’ approach can significantly improve the toolpath planning efficiency and ground surface quality for complex parts as compared with the leading commercial computer-aided manufacturing (CAM) software.

Adaptive toolpath generation for distortion reduction in laser powder bed fusion process

Adaptive toolpath generation for distortion reduction in laser powder bed fusion process

Novel Tool Path Generation Method for Pocket Machining Using Sound Field Synthesis Theory

Contour parallel tool paths have been proved to be a preferred machining strategy for their advantage of less tool retractions and less sharp turns. The traditional geometrical algorithm-based tool path generation method often makes it hard to simply and simultaneously solve the problems of self-intersection, no residual, and smoothness at the same time due to their contradictions. To address this issue, a contoured parallel tool path generation method for pocket machining is developed in this study. It is based on sound field synthesis theory inspired by the phenomenon of sound wave propagation. Firstly, the simplified medial axis (SMA) tree of the pocket is extracted and the propagation direction of each SMA segment is calculated on account of the geometric characteristics of the pocket boundary. Secondly, the final tool path is obtained through the synthesis of the sound field. Finally, the novel method is verified on five different pockets to generate a contoured parallel milling tool path. After machining these pockets and measuring the machining time, roughness, and cutting force, the experimental results demonstrate that the tool path obtained by the novel method has advantages in improving machining quality and efficiency.

A double-NURBS approach to the generation of trochoidal tool path

Trochoidal milling becomes a popular strategy in high-speed rough milling, thanks to its advantages in lowering cutting force (and tool wear) and increasing tool life. However, it also suffers from the disadvantages of low cutting efficiency and prolonged machining time due to its reduced cutter-workpiece engagement in the cutting area and the idle tool path in the non-cutting area. In this paper, a new trochoidal tool path generation method is proposed based on a double-NURBS curve. Unlike traditional circular trochoidal tool path that combines circular and linear paths to approximate the trochoidal path, the double-NURBS tool path can truly represent a trochoidal path with C2 continuity throughout the entire tool path. In the front cutting area, the control points of the NURBS are modified to increase the cutter-workpiece engagement angles; in the rear non-active area, the NURBS curve is modified to shorten the non-cutting distance and the machining time. Degree elevation of the NURBS circle from 2 to 3 maintains C2 continuity to ensure the machining is smooth throughout all transitions. Cutting force simulations and pocket machining experiments are carried out to validate that the proposed double-NURBS approach deliver the expected result and performance.

Toolpath planning method with the constraint of cutting force fluctuation in slow tool servo turning for complex curved surface parts

Parts with the complex curved surface are commonly used in high-end equipment. The machining quality of the curved surface parts is important for the property of high-end equipment. With position control of the main spindle, i.e., the C axis, the slow tool servo (STS) turning is a very promising technique to effectively machine complex curved surface parts. However, the turning machining quality is restricted by the cutting force fluctuation in finishing turning. Hence, the STS turning toolpath generation approach with the constraint of the cutting force fluctuation is proposed in this study. As the cutting force is proportionate to the cutting area, the cutting area for turning complex curved surfaces is analyzed and calculated. Then the functional relation between the cutting force fluctuation and the feed rate is derived. Based on the geometrical characteristic of the first revolution of the toolpath, the feed rate is optimized with small cutting force fluctuation to derive the cutter contact points (CCPs) in the cylindrical coordinate system. From the validation experiment results, it can be seen that the cutting force fluctuation, the profile tolerance, and the surface roughness of parts are effectively reduced, and the surface roughness of the part machined with the proposed toolpath planning method is 17.625 nm. Thus, this study provides guidance for toolpath generation with the constraint of the fluctuation of the cutting force in STS turning for a complex curved surface.

Computational approaches for improving machining precision in five-axis flank milling of spiral bevel gears

Spiral bevel gears are a critical component in mechanical systems that offers high power transmission efficiency between nonparallel axes. The current gear manufacturing, which normally requires specialized machines and cutting tools specific to one gear type, offers limited production flexibility. An effective alternative is to utilize 5-axis computer numerical control milling on general-purpose machine tools. This paper aims to improve the machining precision in the flank milling of spiral bevel gears, particularly the tooth surfaces, using computational approaches. First, a geometric method was developed to approximate the contact path of a gear pair without solving the complex equations in tooth contact analysis. A quantitative measure was introduced to evaluate the contact path deviation from the center curve of the tooth surface. Second, we proposed an optimization scheme for generating tool paths that induce minimal geometrical errors on the finished surface. It employs a metaheuristics-based search algorithm with the errors as an objective in tool path planning. Test results on real gears verified the effectiveness of the proposed scheme. Three measures of the meshing performance, namely the average sampling error, the contact path deviation, and the transmission error, were cross-compared on different gear pairs to examine whether they consistently distinguish the performance rank. This work provides feasible solutions for controlling machining errors in 5-axis flank milling of complex gears.

Ultra-precision manufacturing of microlens arrays using an optimum machining process chain.

There are still significant challenges in the accurate and uniform manufacturing of microlens arrays (MLAs) with advanced ultra-precision diamond cutting technologies due to increasingly stringent requirements and shape complexity. In this paper, an optimum machining process chain is proposed based on the integration of a micro-abrasive fluid jet polishing (MAFJP) process to improve the machining quality by single point diamond turning (SPDT). The MLAs were first machined and compensated by SPDT until the maximum possible surface quality was obtained. The MAFJP was used to correct the surface form error and reduce the nonuniformity for each lens. The polishing characterization was analyzed based on the computational fluid dynamics (CFD) method to enhance the polishing efficiency. To better polish the freeform surface, two-step tool path generation using a regional adaptive path and a raster and cross path was employed. Moreover, the compensation error map was also investigated by revealing the relationship between the material removal mechanism and the surface curvature and polishing parameters. A series of experiments were conducted to prove the reliability and capability of the proposed method. The results indicate that the two integrated machining processes are capable of improving the surface form accuracy with a decrease in PV value from 1.67 µm to 0.56 µm and also elimination of the nonuniform surface error for the lenses.