5-axis Flank Milling Research Articles

Towards [formula omitted]-Continuous Multi-Strip Path-Planning for 5-Axis Flank CNC Machining of Free-Form Surfaces Using Conical Cutting Tools

Existing flank milling path-planning methods typically lead to tiny gaps or overlaps between neighboring paths, which causes artifacts and imperfections in the workpiece. We propose a new multi-strip path-planning method for 5-axis flank milling of free-form surfaces which targets G1 (tangent-plane) continuity of the neighboring strips along shared boundaries. While for some geometries one cannot achieve G1 continuity and high approximation quality at the same time, our optimization framework offers a good trade-off between machining accuracy in terms of distance error and the G1 connection of neighboring strips. We demonstrate our algorithm on synthetic free-form surfaces as well as on industrial benchmark datasets, showing that we are able to meet fine industrial tolerances and simultaneously significantly reduce the kink angle of adjacent strips, and consequently to improve the surface finish in terms of smoothness.

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.

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.

An efficient prediction method for the dynamic deformation of thin-walled parts in flank milling

Severe deformation may occur in the flank milling of thin-walled parts due to their low rigidity. Considering the varying stiffness resulting from the moving cutting force and the material removal effect, finite element-based methods have been developed to compute the deformation and generate compensated tool paths. However, they are time-consuming since they require solving the full-scale deformation equation at each cutting location. Therefore, an efficient deformation prediction method is firstly proposed in this study, in which the workpiece stiffness matrix is reduced and dynamically modified to avoid re-meshing meanwhile decreasing the computational scales of the solving process. Then, considering the coupling effect between the compensation value and the deformation error, a compensation strategy without the iteration process is developed to obtain the compensation value with high accuracy and efficiency. The flank milling of four comparison sets of thin-walled aluminum alloy blocks was conducted to validate the proposed method. The experiment results revealed that the proposed method obtained similar accuracy to the finite element methods, but cost less than 62.0% of their computational time. And the machining error ranges of four comparison sets were reduced by more than 58.7% after compensation. The proposed method shows great potential for efficiency and accuracy improvement in the 5-axis flank milling of thin-walled freeform surface parts. • A novel deformation prediction method for the milling of thin-walled parts is proposed to improve computational efficiency. • Compared with other FEM-based methods, the proposed method obtains similar accuracy but greatly decreases computation time. • Considering the coupling effect between the compensation values, a compensation strategy without iterations is developed. • The proposed method is validated through milling experiments, in which the machining errors were greatly reduced.

A High-Accuracy Tool Path Generation (HATPG) Method for 5-Axis Flank Milling of Ruled Surfaces with a Conical Cutter Based on Instantaneous Envelope Surface Modelling

In this paper, a novel framework of generating high-accuracy tool path for 5-axis flank milling of ruled surfaces with a conical cutter is developed by designing the instantaneous envelope surface of each planned cutter location (CL). Based on the analysis of the envelope theory, the instantaneous envelope profile of a selected cutter is only affected by the first-order derivation of the cutter’s motion, i.e. tangent vectors of the tool path. This property reveals an interesting fact that characteristic points on an envelope surface can be controlled via path tangents, thus laying the foundation for accurately evaluating the machining error at a single cutter location. On this basis, a simple yet robust method, called rotations for three-point offset (RTPO) method is first proposed to position a conical cutter to have at least three contact points with a ruled surface. Path tangents optimization is then performed to minimize the geometric deviation between the characteristic points and the ruled surface, followed by fine-tuning of the tool axis with a differential rigid motion. Both path tangent optimization and tool axis tuning are formulated as linear program problems, and the optimal cutter location with path tangents is determined by solving them repetitively. Finally, accurate tool path for conical cutter flank milling is generated with curve registration algorithms that interpolate the planned points and tangents. Examples are provided to validate the proposed method, and one can see high-accuracy flank milling paths can be planned point-by-point without subsequent optimization.

Curve-guided 5-axis CNC flank milling of free-form surfaces using custom-shaped tools

A new method for 5-axis flank milling of free-form surfaces is proposed. Existing flank milling path-planning methods typically use on-market milling tools whose shape is cylindrical or conical, and is therefore not well-suited for meeting fine tolerances for manufacturing of benchmark free-form surfaces like turbine blades, gears, or blisks. In contrast, our optimization-based framework incorporates the shape of the tool into the optimization cycle and looks not only for the milling paths, but also for the shape of the tool itself. Given a free-form reference surface and a guiding path that roughly indicates the motion of the milling tool, tangential movability of quadruplets of spheres centered along a straight line is analyzed to indicate possible shapes and their motions. This results in G1 Hermite data in the space of rigid body motions that are interpolated and further optimized, both in terms of the motion and the shape of the milling tool itself. We demonstrate our algorithm on synthetic free-form surfaces and industrial benchmark datasets, showing that the use of custom-shaped tools is capable of meeting fine industrial tolerances and outperforms the use of classical, on-market tools.

Optimized tool path planning for five-axis flank milling of ruled surfaces using geometric decomposition strategy and multi-population harmony search algorithm

Tool path planning is a key to ensure high machining quality and productivity in 5-axis flank milling of ruled surfaces. Previous studies have shown that optimization-driven tool path planning can effectively reduce the geometrical errors on the finished surface. However, to solve the corresponding optimization problem is a challenging task involving a large number of decision variables. This paper proposes a novel approach to generating optimized tool path for 5-axis flank finishing cut based on a geometric decomposition strategy and multi-population harmony search algorithm. The proposed approach geometrically divides the surface to be machined into a number of segments. The tool paths on those sub-surfaces are independently optimized by the multi-population harmony search algorithm. Individual tool paths are then combined together to form a complete one. The test results of representative surfaces show that the proposed approach produces higher machining precision with less computational time than compared previous methods. And the computational time is further reduced by Message passing interface based parallel computing techniques. A detailed analysis is conducted to characterize how the number of divisions affects the optimization results. And the proposed approach also shows good scalability with the increasing number of cutter locations.

A solid-analytical-based model for extracting cutter-workpiece engagement in 5-axis flank machining

5-axis flank milling is applied extensively in aerospace, die-molds, and automotive industries because of high efficient material removal rate. Commercial CAM software can only simulate the tool path and collision at present, but cannot handle with cutting force during cutting process due to the variable geometrical cutter workpiece engagement (CWE) region of 5-axis milling. This paper presents a novel solid analytical model for extracting the CWE maps. The CWE is obtained analytically by performing Boolean operations between the cutter and in-process-workpiece (IPW) at any given cutter location (CL) point, instead of using the cutter and the removal volume. The proposed process simulation method could identify the CWE efficiently and precisely for general cutting tools. Finally, the CWE boundaries are mapped from a 3D space into a 2D plane defined by the immersion angle and the axial depth of a given cutter. The proposed solution can be easily integrated into the CAM software for predicting milling force and optimizing parameters in 5-axis milling.

Initial Tool Orientation Set-up for 5-Axis Flank Milling Based on Faceted Models

One of the factors affecting the effectiveness of machining time of 5-axis miling is the method being used. By using flank milling method, as one of the optimized processes to make a workpiece, the time required for the process becomes shorter.This research is aimed at developing the method for determining the initial orientation of the tool for a sculptured surface on the basis of faceted model. By determining cc-point as the basis for positioning the tool on the surface of the workpiece, the cutting direction is formed from the nearest cc-point in the XY flat plane direction of the faceted model at the spatial coordinate. The positioning of the tool is initially based on the Local Coordinate System developed by the cross product between the normal vector n at each cc-point and cutting direction vector F from one cc-point to the other. The cross product resulted is a tangent vector T of the plane formed from the normal vector and cutting direction. The orientation of the tool is formed and defined by an inclination angle ( α ) and a screw angle ( β ). Maximizing the cutting volume and avoiding gouging at each cc-point during the flank milling are carried out through optimal adjustment of these two rotational angles. Furthermore, when the adjustment of rotational angles cannot resolve the gouging, appropriate tool lifting along the normal vector is conductedhis method is very much applicable for flank milling having the basis of data in the form of faceted models.

Iterative optimization of tool path planning in 5-axis flank milling of ruled surfaces by integrating sampling techniques

Simultaneous adjustment of all cutter locations in a tool path using meta-heuristic algorithms provides a systematic approach to reducing machining errors in 5-axis flank machining of ruled surfaces. However, these algorithms experienced unsatisfactory quality of optimal solutions and lengthy search time in high-dimensional search space. To solve these problems, we propose an iterative optimization scheme that progressively simplifies solution space by sampling techniques. Akaike information criterion (AIC) is used to screen significant factors from sampling data. An electromagnetism-like mechanism (EM) algorithm searches through a simplified solution space constructed only using these factors. An iteration process consisting of such sampling, screening, and searching steps repeats several times until final optimal solutions are obtained. Test results of representative surfaces validate the effectiveness of the proposed scheme. Both solution quality and search efficiency are improved comparing to those produced by previous studies. This work enhances the practicality of optimization-driven tool path planning in 5-axis flank machining.

Tool Path Generation Method for Five-axis Flank Milling of Corner by Considering Dynamic Characteristics of Machine Tool

During the corner machining process of 5-axis flank milling, the sharp change of tool path and tool orientation may lead to a dramatic increase of the milling force and tool vibration, which gravely impacts the machining quality. In order to address this issue, a 5-axis flank milling tool path generation method for corners by considering the dynamic characteristics of machine tool is presented in this paper. To be specific, firstly, the allowance information model of corner is built according to the part model and roughing information. Secondly, the tool trajectory based on clothoid curve and milling force constraint is optimized. And then, the tool orientation based on tool trajectories is optimized. Finally, the 5-axis flank milling tool path is generated by considering the dynamic characteristics of machine tool and the milling force constraint. The remaining materials of corner can be removed uniformly using the proposed tool path, and the curvature of the tool path is continuous. Simulation results show that the machined surface of corner is smooth, and the proposed tool path is suitable for corner machining.

An accurate prediction method of cutting forces in 5-axis flank milling of sculptured surface

The instantaneous uncut chip thickness and entry/exit angle of cutter/workpiece engagement continuously vary with tool path and workpiece geometry in 5-axis flank milling of sculptured surface, which results in the obvious time-varying characteristic for consecutive cutting forces. An accurate prediction method for cutting force in 5-axis flank milling of sculptured surface is proposed in this paper. Comprehensively considering curved tool path and actual tool motion process with cutter runout (offset and inclination) effects, an accurate representation model for instantaneous uncut chip thickness during cutter/workpiece engaging in 5-axis flank milling is presented firstly, which can reach a higher accuracy and efficiency with the aid of linear iteration process than the methods published. Then, based on the thin plate milling experiments, an efficient calibration procedure for cutter runout parameters and specific cutting force coefficients is given and further verified in practice. Finally, a series of validation experiments are conducted under different cutting conditions, and the results reveal that there is a very good agreement between the experimental and simulation data both in shape and magnitude and prove the effectiveness and accuracy of the proposed method.

5-Axis adaptive flank milling of flexible thin-walled parts based on the on-machine measurement

Deformation of the part and cutter caused by cutting forces immediately affects the dimensional accuracy of manufactured parts. This paper presents an integrated machining deviation compensation strategy based on on-machine measurement (OMM) inspection system. Previous research attempts on this topic deal with deformation compensation in machining of geometries in 3-axis machine tools only. This paper is the first time that concerned with 5-axis flank milling of flexible thin-walled parts. To capture the machined surface precision dimensions, OMM with a touch-trigger probe installed on machine׳s spindle is utilized. Probe path is planned to obtain the coordinate of the sampling points on machined surface. The machined surface can then be reconstructed. Meanwhile, the cutter׳s envelope surface is calculated based on nominal cutter location source file (CLSF). Subsequently, the machining error caused by part and cutter deflection is calibrated by comparing the deviation between the machined surface and the envelope surface. An iteration toolpath compensation algorithm is designed to decrease machining errors and avoid unwanted interference by modifying the toolpath. Experiment of machining the impeller blade is carried out to validate the methodology developed in this paper. The results demonstrate the effectiveness of the proposed method in machining error compensation.

The research of surface waviness control method for 5-axis flank milling

This paper presents a comprehensive surface waviness control technology for 5-axis flank milling. Through constructing dual NURBS curves to describe toolpath, the feedrate and rotary axis optimization method is proposed. Through controling milling area rate, the proposed method could improve the 5-axis flank milling state under the constrains of cutting force, machining dynamics conditions and driver physical limits. In addition, it could improve the rotary axis unstable movement such as discontinuous and reciprocating rotating in minor angle to alleviate the unstable of rotary axis. Finally, a series experiments were conducted. The results show that the control technology is effective and applicable.

Improving optimization of tool path planning in 5-axis flank milling using advanced PSO algorithms

This paper studies optimization of tool path planning in 5-axis flank milling of ruled surfaces using advanced Particle Swarm Optimization (PSO) methods with machining error as an objective. We enlarge the solution space in the optimization by relaxing the constraint imposed by previous studies that the cutter must make contact with the boundary curves. Advanced Particle Swarm Optimization (APSO) and Fully Informed Particle Swarm Optimization (FIPS) algorithms are applied to improve the quality of optimal solutions and search efficiency. Test surfaces are constructed by systematic variations of three surface properties, cutter radius, and the number of cutter locations comprising a tool path. Test results show that FIPS is most effective in reducing the error in all the trials, while PSO performs best when the number of cutter locations is very low. This research improves tool path planning in 5-axis flank milling by producing smaller machining errors compared to past works. It also provides insightful findings in PSO based optimization of the tool path planning.

Optimization of tool path planning in 5-axis flank milling of ruled surfaces with improved PSO

Previous studies have shown that machining error in 5-axis flank milling can be systematically reduced by optimization of tool path planning. However, the solution quality of the optimization methods adopted by those studies was not satisfactory, due to the constraint that the cutter must contact the boundary curves of the ruled surface to be machined. This work proposes an improved tool path planning method based on Particle Swarm Optimization (PSO) algorithms without this constraint. The method enlarges the feasible region in the optimization by allowing cutter location to deviate the boundary curves along the normal, tangent, and bi-normal directions. Design of experiment techniques are applied to determine better parameter setting in the PSO. A new objective function is formulated as the weighted sum of the errors induced by overcut and undercut. We can choose to minimize the total machining error, the overcut, or the undercut by properly adjusting the weight value. Compared to previous methods, the improved path planning method produces smaller machining error and offers better planning flexibility.

Particle swarm optimisation (PSO)-based tool path planning for 5-axis flank milling accelerated by graphics processing unit (GPU)

Multi-axis machining offers higher machining efficiency and superior shaping capability compared to 3-axis machining. Machining error control is a critical issue in 5-axis flank milling of complex geometries and there is still a lack of solutions. Previous studies have shown that optimisation-based tool path planning is a feasible approach to reduction of machining error. However, the error estimation is time-consuming in the optimisation process, thus limiting the practicality of this approach. In this work, we apply graphics processing unit (GPU) computing technology to solve this problem. A particle swarm optimisation (PSO)-based optimisation scheme is developed to generate a series of cutter locations (CLs) that produce a minimised error on the machined surface. The error amount induced by each CL is simultaneously calculated by the parallel processing units of GPU. The PSO search process driven by the aggregated result is effectively accelerated. Test results show that our approach outperforms previous optimisation methods in both solution quality and computation efficiency. This work demonstrates a novel application of GPU on Computer Aided Manufacturing/Computer Numerical Control.

5-Axis Flank Milling Tool Path Smoothing Based on Kinematical Behaviour Analysis

In the context of 5-axis flank milling, the machining of non-developable ruled surfaces may lead to complex tool paths to minimize undercut and overcut. The curvature characteristics of these tool paths generate slowdowns affecting the machining time and the quality of the machined surface. The tool path has to be as smooth as possible while respecting the maximum allowed tolerance. In this paper, an iterative approach is proposed to smooth an initial tool path. An indicator of the maximum feedrate is computed using the kinematical constraints of the considered machine tool, especially the maximum velocity, acceleration and jerk. Then, joint coordinates of the tool path are locally smoothed in order to raise the effective feedrate in the area of interest. Machining simulation based on a N-buffer algorithm is used to control undercut and overcut. This method has been tested in flank milling of an impeller and can be applied in 3 to 5-axis machining.

Efficient tool path planning for 5-axis flank milling of ruled surfaces using ant colony system algorithms

Five-axis CNC flank milling has recently received much attention in industry. The flank milling operation is efficient in shaping ruled geometry, but introduces a challenging task in machining error control. Previous work proposed a dynamic-programming based scheme for generating optimal tool path by minimising the machining error. However, to compute the tool path takes a considerable amount of time. This paper presents a new scheme using meta-heuristics, ant colony system (ACS), for tool path planning in 5-axis flank milling, with a focus on improving the computation efficiency. The path planning problem is first formulated as mapping two boundary curves of a ruled surface. An ACS-based optimisation algorithm is then applied to search for the mapping that minimises the machining error. The solution is nearly as good as using dynamic programming but takes only half of the computational time. The results from machining experiment and 3D measurement validate the effectiveness of the proposed scheme.

Generation of reciprocating tool motion in 5-axis flank milling based on particle swarm optimization

This paper proposes a novel method for generation of optimized tool path in 5-axis flank milling of ruled surfaces based on Particle Swarm Optimization (PSO). The 3D geometric problem, tool path generation, is transformed into a mathematical programming task with the machined surface error as the objective function in the optimization. This approach overcomes the limitation of greedy planning methods employed by most previous studies. By allowing the cutter to move backforward, reciprocating tool path produces smaller machining error compared with the traditional one consisting of only forward cutter movement. A cutting experiment is conducted with different tool paths and the CMM measurement verifies the effectiveness of the proposed method.