Tool Path Correction Research Articles

A Melt Electrowriting Toolbox for Automated G‐Code Generation and Toolpath Correction of Flat and Tubular Constructs

A Melt Electrowriting Toolbox for Automated G‐Code Generation and Toolpath Correction of Flat and Tubular Constructs

Springback prediction using point series and deep learning

One of the main challenges that prevent wide adoption of Single Point Incremental Forming (SPIF) is the geometric accuracy of the process resulting primarily from the effect of springback. There are various expedients that can be adopted to address this, but one of the most common is tool path correction. The challenge is then how best to predict springback so as to implement tool path correction. It is established that springback, to a large extent, is related to the geometry of the part to be manufactured. The proposed mechanism uses a novel point series representation to capture local geometries that then form a global bank of geometries for general use. Each point series can then be associated with a predicted springback value generated using deep or machine learning. Experiments are reported using a Long Short Term Memory (LSTM) model coupled with a Multilayer Perception Network (MLP), and a Support Vector Machine (SVM) regression model. A best R2, “Coefficient of Determination”, of 0.9181 was obtained indicating that the proposed approach provided a realistic solution to the current limitations of SPIF.

On-machine measurement and compensation of thin-walled surface

On-machine measurement technology is considered as a key technology for realizing closed-loop feedback control in intelligent manufacturing due to the reduction of the transfer process. However, the complexity of the machine tool process system introduces some uncertainty into the accuracy of on-machine measurement, which severely limits the application in the actual industrial field. To overcome the shortcomings of the existing uncertainty, an inspection framework for on-machine measurement of thin-walled surface is proposed. Firstly, a low-cost wireless on-machine measurement system based on potential signals is established and integrated into a manufacturing process line for automatic sampling. Then, the similarity of momentum conservation is introduced into sampling planning, and an adaptive sampling model based on momentum conservation and multi-objective particle swarm optimizer is proposed. Finally, a stacked deep learning model under the vertical inspection direction is proposed to improve the inspection accuracy by correcting the sampling data. Compared with existing sampling methods, the proposed model is similar to an attention mechanism that enables adaptive enhancement of profile features. The inspection performance by data correction is improved by about 16.14% in the mean inspection error. Simulations and experiments show that the proposed method has great advantages in terms of efficiency and robustness, which can provide a theoretical reference for adaptive toolpath correction for thin-walled surfaces.

An accuracy evolution method applied to five-axis machining of curved surfaces

Currently, some high-value-added applications involve the manufacturing of curved surfaces, where it is challenging to achieve surface accuracy, repeatability, and productivity simultaneously. Among free-form surfaces, curved surfaces are commonly used in blades and airfoils (with a teardrop-shaped cross-section) and optical systems (with axial symmetry). In both cases, multi-axis milling accuracy directly affects the subsequent process step. Therefore, reducing even insignificant errors during machining can improve the accuracy in the final production stages. This study proposes an “evolution” method to improve the machining accuracy of curved surfaces. The key is to include compensation for the machining error after the first part through profile error measurement. Thus, correction can be applied directly after the manufacturing programming is fully developed, achieving the product with the minimum number of iterations. Accordingly, this method measures the machining error and changes only one key parameter after the process. This study considered two cases. First, an airfoil in which the clamping force was corrected; the results were quite good with only one modification in the blade machining case. Second is an aspherical surface where tool path correction in the Z-axis was applied; the error was effectively compensated along the normal vector of the workpiece surface. The experimental results showed that the surface accuracy increased from 44.4 to 4.5 μm, and the error was reduced by 89.9%, confirming that the accuracy of the machine tool and process had achieved “evolution.” This technical study is expected to help improve the quality and productivity of manufacturing highly accurate curved surfaces.

Electrostatic Distortion of Melt‐Electrowritten Patterns by 3D Objects: Quantification, Modeling, and Toolpath Correction

AbstractMelt electrowriting (MEW) is an electrohydrodynamic process capable of producing organized patterns of micrometer‐scale polymer fibers. Integrating MEW with other additive manufacturing technologies, such as extrusion‐printing or bioprinting, offers tantalizing possibilities for multi‐scale biofabrication of anatomically shaped scaffolds. However, introducing 3D structures onto the conventionally flat collector plate significantly complicates the MEW process because these objects perturb the electrostatic field. Here, the systematic investigation of how simple 3D objects (hemispheres) distort MEW patterns printed in their vicinity is reported. The authors assess the influence of a series of parameters on fiber deflection including: distance from the hemisphere, hemisphere size and material composition, height of the nozzle, translation speed, applied voltage, and applied pressure. In light of these data, a model which captures the basic physics behind the deflection phenomenon is derived. An optimization algorithm to calculate tool‐paths which pre‐emptively account for these deviations is also introduced. Finally, the authors validate how G‐code produced by this algorithm effectively corrects the distortion effect, restoring the ability to create well‐defined MEW patterns in the vicinity of 3D objects. This study suggests a foundation for understanding the complexities of MEW on non‐planar collectors, and towards multitechnology biofabrication.

Projekt oraz oprogramowanie zrobotyzowanego stanowiska do gratowania felg samochodowych

More and more often, production processes use solutions in which robots cooperate with vision systems. This is related to the implementation of "pick and place" tasks or tool path correction during the machining process. Vision systems exchange information with robot controllers, which enables the detection of a specific object, obtaining information about its location and orientation. As part of the article, it was decided to design and build a robotic station in the RobotStudio environment for deburring car rims. The process of designing the algorithm in the MATLAB environment that allows to determine the position and orientation of the processed detail was presented. Both MATLAB and RobotStudio environments communicate via the TCP/IP protocol. The verification of operation and simulation of the constructed station were presented.

Continuous Eulerian tool path strategies for wire-arc additive manufacturing of rib-web structures with machine-learning-based adaptive void filling

Rib-web structures are used for lightweight design in various applications. The most prominent cases are found in aerospace engineering, where intricate structures are produced by forging and subsequent machining or by machining from solid blocks of material. Due to the large scrap rate involved in conventional manufacturing, rib-web structures are suitable applications for additive manufacturing (AM) processes. Among the AM processes, wire-arc additive manufacturing (WAAM) is highly suitable for rib-web structures due to its high deposition rate and the potential to manufacture large-size parts. In WAAM, the welding strategy greatly influences the properties and quality of deposited parts. With an increasing number of starts and stops, the danger of uneven material build-up and welding defects increases. Unfortunately, most rib-web structures do not represent Eulerian paths, i.e. they cannot be manufactured with a continuous welding motion, in which every edge is visited only once. This study presents a novel strategy for generating optimal tool paths for WAAM of lightweight rib-web structures, mitigating the disadvantages of discontinuous welding paths such as welding defects and uneven build-up. It is shown that doubling the number of welding passes on each edge of the rib-web structure turns non-Eulerian paths into Eulerian paths, which can be welded continuously. When two or more weld beads are deposited on each edge, the vertices of the rib-web structure may suffer from underfilling. It is shown that this can be avoided by a correction strategy, which consists in manufacturing the part once, evaluating the size of voids in the junctions, and computing a correction to deposit the required amount of material into the center of the junction. While this strategy may be used if a single part is considered, it is shown that the tool path correction to be applied to arbitrary junction geometries can be represented by a neural network that is derived from an experimental database consisting of representative junction types. With this approach, paths for any rib-web geometry can be generated, which saves lead time in variant-rich production. The paths proposed in this work avoid non-welding moves and may hence outperform even single weld-bed strategies in terms of welding efficiency.

Less interference tool-path correction model for half revolution penetration and retraction trajectories in internal straight thread side milling

Unreasonable tool-path generation in the penetration and retraction processes of the internal thread milling can easily result in severe interference errors, therefore, this study proposes a less interference tool-path correction model for the half revolution penetration and retraction trajectories to further reduce the tool-path interference errors. Firstly, the parametric equations of the initial penetration and retraction trajectories are derived from the half revolution penetration and retraction angle α. Then, an offsetting coefficient e is defined to adjust the X-coordinate components of the starting point of the penetration trajectory and the end point of the retraction trajectory, the Z-coordinate components of the penetration and retraction trajectories are calculated by substitute the angle α with the cutter spiral rotation angle θ. As a result, the correction parametric equations for adjusting the penetration and retraction trajectories with the e are established. Finally, according to the influence of e on the interference errors, the appropriate value of the e is determined to control the interference errors within the allowable tolerance range. Taking the milling of M16 × 1.5 thread hole with M8 × 1.5 thread milling cutter as an experimental example, the experimental results show that the maximum interference error of the proposed correction model (e = 0.9) can be reduced by 73.6% and 33.82% compared with the initial uncorrection model and the existing optimization method, respectively. This study indicates the proposed model can significantly decrease the interference occurred in internal thread milling and smoothly achieve the demands of more precision threaded connections.

Haptic metal spinning

Sheet metal spinning is an incremental forming technique practiced for a long time only by experienced, skilled craftsmen. Over the last sixty years, attempts have been made to automate the process, but today the industrial practice still relies heavily on the skill of experienced operators. Complete analytical solutions to predict workpiece failure based on the path of the tool are not available, and finite element simulations of the process are too time-intensive to be of practical use for online toolpath correction. Therefore, today the design of toolpaths to avoid failure in spinning remains an art acquired by practice. In this paper, we approach the issue by designing an enhanced teach-in/playback system. We connect a haptic device to a CNC spinning machine; this device allows a human operator to control the working roller manually while feeling the force applied to the workpiece. Position, force and workpiece shape sensors allow collecting information on the toolpath followed by the operator and on its influence over the mechanics of the process. The opportunities offered by this system to derive rules for toolpath design are explored in two case studies on force control and wrinkling recovery, with new insights on the relationship between toolpaths and failure. A research agenda is outlined to exploit the full potential of haptic metal spinning.

Design and Implementation of a Stereo Vision System on an Innovative 6DOF Single-Edge Machining Device for Tool Tip Localization and Path Correction

In the current meso cutting technology industry, the demand for more advanced, accurate and cheaper devices capable of creating a wide range surfaces and geometries is rising. To fulfill this demand, an alternative single point cutting device with 6 degrees of freedom (6DOF) was developed. Its main advantage compared to milling has been the need for simpler cutting tools that require an easier development. To obtain accurate and precise geometries, the tool tip must be monitored to compensate its position and make the proper corrections on the computer numerical control (CNC). For this, a stereo vision system was carried out as a different approach to the modern available technologies in the industry. In this paper, the artificial intelligence technologies required for implementing such vision system are explored and discussed. The vision system was compared with commercial measurement software Dino Capture, and a dedicated metrological microscope system TESA V-200GL. Experimental analysis were carried out and results were measured in terms of accuracy. The proposed vision system yielded an error equal to ±3 µm in the measurement.

Part accuracy improvement in two point incremental forming with a partial die using a model predictive control algorithm

As a flexible forming technology, Incremental Sheet Forming (ISF) is a promising alternative to traditional sheet forming processes in small-batch or customised production but suffers from low part accuracy in terms of its application in the industry. The ISF toolpath has direct influences on the geometric accuracy of the formed part since the part is formed by a simple tool following the toolpath. Based on the basic structure of a simple Model Predictive Control (MPC) algorithm designed for Single Point Incremental Forming (SPIF) in our previous work Lu et al. (2015) [1] that only dealt with the toolpath correction in the vertical direction, an enhanced MPC algorithm has been developed specially for Two Point Incremental Forming (TPIF) with a partial die in this work. The enhanced control algorithm is able to correct the toolpath in both the vertical and horizontal directions. In the newly-added horizontal control module, intensive profile points in the evenly distributed radial directions of the horizontal section were used to estimate the horizontal error distribution along the horizontal sectional profile during the forming process. The toolpath correction was performed through properly adjusting the toolpath in two directions based on the optimised toolpath parameters at each step. A case study for forming a non-axisymmetric shape was conducted to experimentally validate the developed toolpath correction strategy. Experiment results indicate that the two-directional toolpath correction approach contributes to part accuracy improvement in TPIF compared with the typical TPIF process that is without toolpath correction.

Two-directional toolpath correction in single-point incremental forming using model predictive control

Incremental sheet forming (ISF) is an emerging forming technology that promises high flexibility and formability. These properties make it suited for small-scale and customised production. However, the poor geometric accuracy of ISF limits the wide application of this flexible forming technology. This paper presents a two-directional toolpath correction approach to enhance ISF forming accuracy using a model predictive control (MPC) algorithm. A toolpath optimisation method for vertical toolpath correction has been validated in our previous work (Lu et al., Int J Adv Manuf Technol 72:1–14, 2015), and it helps to reduce errors in the base of the test shapes to a suitable level while its major limitation is that horizontal geometric errors are relatively large. This paper extends our previous work (Lu et al., Int J Adv Manuf Technol 72:1–14, 2015) by augmenting the vertical control module with a new control module for horizontal toolpath correction. The proposed control algorithm was experimentally validated in single-point incremental sheet forming (SPIF) using two forming case studies. In the first case study (a truncated pyramid), two control approaches with different assumptions for the horizontal springback distribution along the horizontal cross-sectional profile were tested and compared. Then, the developed MPC control algorithm was applied to form a more complex asymmetric shape. The results show that the developed strategy can reduce the forming errors in the wall and base of the formed shape compared to the existing works. The ISF process with MPC control leads to significant accuracy improvement in comparison with the typical ISF process that is without toolpath control.

Development of Tool Path Correction Algorithm in Incremental Sheet Forming

The problem of obtaining sound parts by Incremental Sheet Forming is still a relevant issue, despite the numerous efforts spent in improving the toolpath planning of the deforming punch in order to compensate for the dimensional and geometrical part errors related to springback and punch movement. Usually, the toolpath generation strategy takes into account the variation of the toolpath itself for obtaining the desired final part with reduced geometrical errors. In the present paper, a correction algorithm is used to iteratively correct the part geometry on the basis of the measured parts and on the calculation of the error defined as the difference between the actual and the nominal part geometries. In practice, the part geometry is used to generate a first trial toolpath, and the form error distribution of the resulting part is used for modifying the nominal part geometry and, then, generating a new, improved toolpath. This procedure gets iterated until the error distribution becomes less than a specified value, corresponding to the desired part tolerance. The correction algorithm was implemented in software and used with the results of FEM simulations. In particular, with few iterations it was possible to reduce the geometrical error to less than 0.4 mm in the Incremental Sheet Forming process of an Al asymmetric part, with a resulting accuracy good enough for both prototyping and production processes.

A Process/Machine coupling approach: Application to Robotized Incremental Sheet Forming

In this paper, a Process/Machine coupling approach applied to Robotized Incremental Sheet Forming (RISF) is presented. This approach consists in coupling a Finite Element Analysis (FEA) of the process with an elastic modelling of the robot structure to improve the geometrical accuracy of the formed part. The FEA, assuming a rigid machine, is used to evaluate the forces at the interface between the tool and the sheet during the forming stage. These forces are used as input data for the elastic model, to predict and correct the tool path deviations. In order to make the tool path correction more effective, the weight of three numerical and material parameters of the FEA on the predicted forces is investigated. Finally, the proposed method is validated by the comparison of the numerical and experimental tool paths and geometries obtained with or without correction of the tool path.

A tool path correction and compression algorithm for five-axis CNC machining

A novel approach is proposed for correcting command points and compressing discrete axis commands into a C2 continuous curve. The relationship between values of rotation angles and tool posture errors is firstly analyzed. A segmentation method based on values of rotation angles and lengths of adjacent points is then used to subdivide these command points into accuracy regions and smoothness regions. Since tool center points generated by CAD/CAM system are usually lying in the space that is apart from the desired curve within a tolerance distance, and the corresponding tool orientation vector may change a lot while the trajectory length of the tool center point is quite small, directly machining with such points will lead to problems of coarse working shape and long machining time. A correction method for command points is implemented so that good processing effectiveness can be achieved. Also, the quintic spline is used for compressing discrete command points into a C2 continuous smooth curve. The machining experiment is finally conducted to demonstrate the effectiveness of the proposed algorithm.

Force Prediction for Correction of Robot Tool Path in Single Point Incremental Forming

In this work, an off-line compensation procedure, based on an elastic modelling of the machine structure coupled with a Finite Element Analysis (FEA) of the process is applied to Robotized Single Point Incremental Forming (RSPIF). Assuming an ideal stiff robot, the FEA evaluates the Tool Center Point (TCP) forces during the forming stage. These forces are then defined as an input data of the elastic robot model to predict and correct the tool path deviations. In order to make efficient the tool path correction, the weight of three numerical and material parameters of the FEA on the predicted forces is investigated. Finally, the efficiency of the proposed method is validated by the comparison between numerical and experimental geometries obtained with or without correction of the tool path.

Rapid Toolpath Correction for Five-Axis High Efficiency Machining Based on Image Analysis

Five-axis high speed machining can improve the efficiency and accuracy obviously, but the machining errors and tool interference are likely to happen due to the complexity of tool motion. So the collision detection and verification of tool path are very important and necessary before machining the part. Using a combination of process simulation and collision detection based on image analysis, a rapid detection approach is developed in this research. The geometric model provides the cut geometry for the collision detection and records a dynamic geometric information for in-process workpiece. For the precise collision detection, a strategy of image analysis method is developed in order to make the approach efficient and maintian a high detection precision. An example of five-axis machining propeller is studied to demonstrate the proposed approach.

Tool path correction algorithm for single-point incremental forming of sheet metal

There exists some error between the manufactured part shape and the designed target shape due to springback of this part after forming. To reduce the error, an iterative algorithm of closed-loop control for correcting tool path of the single-point incremental forming, based on Fast Fourier and wavelet transforms, has been developed. Moreover, the data of the springback shapes, after unloading, of the sheet metal parts formed with the trial and corrected tool paths, used for iterative correction of tool path in the algorithm, are obtained with finite element model (FEM) simulation. Then, a truncated pyramid-shaped workpiece, whose average errors are +0.183/−0.175 mm, was made with the corrected tool path after three iterations solved by the above algorithm and simulation data. The results show that the tool path correction algorithm with Fourier and wavelet transforms is reasonable and the means with FEM simulation are effective. It can be taken as a new approach for single-point incremental forming of sheet metal and tool path design.

An innovative subdivision-ICP registration method for tool-path correction applied to deformed aircraft parts machining

A new and fast registration algorithm has been proposed to update the tool-path of a deburring robot, intended to machining composite workpieces under gravity and clamping deformations. A Subdivision Iterative Closest Point algorithm, which considers different parts of the contour with respect to curvature, allows to obtain far better results than classical methods, without complicated assumptions or computations. The procedure has shown to be effective for porthole and nose-cone deburring. Experimental tests conducted on robotic milling workcell demonstrated the efficiency of the registration method.

Subdivision surface-based finish machining

Subdivision surfaces combine smooth spline surfaces and polygonal meshes together, therefore, a smooth design model and discrete machining models may be unified and subdivision surfaces may be used as a common representation for geometric design and machining. Motivated by the idea, this paper presents the study of finish machining of objects represented by subdivision surfaces with emphasis on geometric error control involved in tool-path generation. First, given a design model, chordal error is controlled during finishing model building. A chordal error-driven adaptive subdivision method is used to build finishing models with less data. Second, a surface decomposition machining strategy is used to control the cusp height error. A simple iso-slope curve tracing and surface decomposition algorithm is presented to partition the model into flat and steep regions. Contour-map tool-paths are generated in the steep regions while iso-planar tool-paths are generated in the flat regions. The gouge problem is easily handled through two-dimensional (2D) tool-path correction algorithms. The implementation results demonstrate that subdivision is capable of serving as a unified representation for both geometric modelling and machining.