Parametric toolpath design in metal spinning

Toolpaths in metal spinning are still designed by human operators, largely by intuition: a scientific basis remains elusive. In this paper, a parameterised toolpath is proposed based on a quadratic Bezier curve. Experiments are performed varying each of four design parameters in turn, to investigate how tool force, part geometry and various failure modes evolve with key features of the tool path. Analysis of these experimental results reveals some new features of process mechanics and leads to a proposal for a set of rules that may become useful for automatic toolpath generation.The first author is funded by the EPSRC Doctoral Training Account and Primetals Technologies Limited (contract number RG64379)– a joint venture company of Siemens, Mitsubishi Heavy Industries and Partners; the second author by EPSRC Grant EP/K018108/1.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.cirp.2015.04.07

The mechanics and control of flexible asymmetric spinning

Metal spinning is a sheet forming process to produce axisymmetric products, but its commercial operation still depends on a dedicated mandrel which determines the shape of the product, and skilled craftsmen to control the working tool. In Flexible Asymmetric Spinning (FAS) the mandrel is replaced with three numerically controlled internal rollers, thereby removing the setup time and cost associated with producing the dedicated mandrel. However, if FAS could also be automated, the setup time and cost could be reduced further. This thesis focuses on three elements which need to be in place for the automation of FAS: the automation of the internal rollers; compensation for springback; and toolpath design to prevent failure.Typically, automation requires a process model. To automate the internal rollers, a process model which predicts the effect of the internal roller position on the workpiece shape would be required – but as FAS is a novel process, no such models exist. To compensate for springback, a model of workpiece shape is required. To prevent failure, a model of the two modes of failure – wrinkling and tearing – is needed. For offline automation, these should be accurate models – but accurate models of both workpiece shape and failure are too slow to make this feasible. For online automation, fast, approximate models can be used – measurements of the product can be fed back in order to compensate for the model errors. However, a literature review showed that no models exist for workpiece shape or failure which are both fast enough for online use, and detailed enough to give information on how tool actions should be changed. This is why FAS has not yet been automated.In previous work, the internal rollers were positioned through trial-and-error and only a straightwalled cup was successfully produced. In this work, a laser line scanner is installed to measure the workpiece shape online, and one of the internal rollers is positioned at the point where the workpiece just begins to diverge from the target shape. This prevents overlap with the target shape, and allows a greater range of products to be made.Springback is typically prevented in conventional spinning by pressing the material hard against the mandrel. This is not possible in FAS due to the force limits on the internal tools. However, in FAS it is possible to move the working roller inside the target shape to compensate for springback. The laser line scanner is used to measure springback and calibrate a simple elastic cantilever model of springback online. By using this model to calculate how far to move the tool inside the target shape, springback errors are reduced by 75%.Two approaches to toolpath design to avoid failure are investigated: Firstly, a finite horizon control system – where failure is checked for only for a short time into the future – is tentatively demonstrated using a slow but accurate finite element (FE) model, but this is too slow for industrial use. However, with a faster, linear-elastic model, the control system is too conservative and fails to produce the final product. Secondly, an empirical approach is investigated: a series of trials are carried out with a parameterised toolpath. The result is a tentative set of rules for toolpath design which may provide the basis for a future control system.Overall, this thesis makes steps towards the automation of internal rollers, compensation of springback, and design of toolpaths to prevent failure in FAS. With further work to extend the control system developed here to automate all three internal rollers and to verify the robustness of the springback compensation system, any conventional spinning machine could potentially be replaced by an FAS machine – with the toolpath of the working roller designed manually, as it currently is in conventional spinning. Yet the tentative sets of rules on toolpath design also open the door to a potential automatic toolpath generation system, and further work should begin by testing the robustness of these rules with changes in material and geometry. Then, with some likely extensions, they could be embedded into a working control system to fully automate FAS

Closed-loop control of product properties in metal forming

Metal forming processes operate in conditions of uncertainty due to parameter variation and imperfect understanding. This uncertainty leads to a degradation of product properties from customer specifications, which can be reduced by the use of closed-loop control. A framework of analysis is presented for understanding closed-loop control in metal forming, allowing an assessment of current and future developments in actuators, sensors and models. This leads to a survey of current and emerging applications across a broad spectrum of metal forming processes, and a discussion of likely developments.Engineering and Physical Sciences Research Council (Grant ID: EP/K018108/1)This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cirp.2016.06.00

Parametric toolpath design in metal spinning

Toolpaths in metal spinning are still designed by human operators, largely by intuition: a scientific basis remains elusive. In this paper, a parameterised toolpath is proposed based on a quadratic Bezier curve. Experiments are performed varying each of four design parameters in turn, to investigate how tool force, part geometry and various failure modes evolve with key features of the tool path. Analysis of these experimental results reveals some new features of process mechanics and leads to a proposal for a set of rules that may become useful for automatic toolpath generation.The first author is funded by the EPSRC Doctoral Training Account and Primetals Technologies Limited (contract number RG64379)– a joint venture company of Siemens, Mitsubishi Heavy Industries and Partners; the second author by EPSRC Grant EP/K018108/1.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.cirp.2015.04.07

Parametric toolpath design in metal spinning

Toolpaths in metal spinning are still designed by human operators, largely by intuition: a scientific basis remains elusive. In this paper, a parameterised toolpath is proposed based on a quadratic Bezier curve. Experiments are performed varying each of four design parameters in turn, to investigate how tool force, part geometry and various failure modes evolve with key features of the tool path. Analysis of these experimental results reveals some new features of process mechanics and leads to a proposal for a set of rules that may become useful for automatic toolpath generation

Support roller control and springback compensation in flexible Spinning

Flexible spinning with three internal support rollers can allow the economic production of very low-volume or one-off prototypes by removing the need for a mandrel. However, to produce a range of shallow products accurately, it is necessary to position the internal support rollers correctly and to compensate for springback. This paper demonstrates the use of a laser scanner to monitor the current workpiece, position the internal rollers correctly, and compensate for springback. The approach is demonstrated by producing a 316 mm cup with a 50 mm corner radius with a geometric error of just 1.5 mm

Research data supporting "Parametric toolpath design in metal spinning"

The file /data/experiments.csv contains the parameters used in each experiment. In /data/ there is a folder for each experiment, named after the ID of that experiment (it therefore corresponds to the first column of /data/experiments.csv ). Each of these folders contains the following files: forcePosLog.txt Contains the tool positions and force log. Each row contains contains the following data separated by commas (all in mm and mm/s unless stated): 1. Number of rotations of spindle 2. Working roller axial position (centre of 15mm nose radius) 3. Working roller radial position (centre of 15mm nose radius) 4. Blending roller axial (centre of 15mm nose radius) 5. Blending roller radial (centre of 15mm nose radius). 6. Support roller axial (Note that support rollers aren’t used so 6-8 are irrelevant). 7. Support roller top radial 8. Support roller bottom radial 9. Working roller axial velocity (commanded, rather than measured) 10. Working roller radial velocity (commanded, rather than measured) 11. Working roller axial force (in kN) 12. Working roller radial force (in kN) 13. Laser power (Off:0; full power: 31) 14. Laser exposure (micro seconds) 15. Wrinkle amplitude – measured online and I found it not to be very reliable; not used in paper. 16. Wrinkle frequency – number of wrinkles around circumference, not very reliable and not used in paper 17. Time (in ms) taken to measure the wrinkles 18. The ID of the 3D shape data used to measure wrinkes – note that every 5 3D shape measurements is saved as shape3D_[ID].txt scanShapes.txt Contains a series of measurements taken as the workpiece rotates. If there are n rows in total, the first n/2 rows contain X coordinates, the second half are Y coordinates. Each row corresponds to one profile. You will need to process these into R-Z coordinates using the scanParams.txt files. scanAngles.txt Contains the angle (in rotations of spindle) at which the measurements in X are taken. Element i contains the angle at which the profile on row I and i+n/2 are measured in scanShapes.txt scanParams.txt Contain the laser calibration data at the time the scan is taken in the following order: 1. Rotation of the data (rotate measured X-Y data by this to get to Z-R coordinates). 2. Axial displacement (add this to Z coordinates) 3. Radial displacement (add this to R coordinates) 4. Axial scale (multiple axial coordinates by this 5. Radial scale (multiply radial coordinates by this) Shape3D_X.txt is the same format as scanShapes.txt but taken mid process. X gives the ID of the measurement, which can be used to correspond to the online wrinkle measurement ID in column 18 of forcePosLog.txt Shape.txt contains a log of the shape, taken more frequently than shape3D_X.txt files, but only the mean profile. It also contains the tool positions etc. at the time the shape measurement is taken. It contains groups of three rows, the first of which contains data in the same form as each row of forcePosLog.txt. The second row contains the Z coordinates and the third contains R coordinates along the profile (they are already rotated, so no need to worry about laser parameters). Thickness.txt contains the thickness measurements. The top row of this file should be headers: Point, Parallel and Perpendicular. The next row contains the data: -1, the value the dial guage read with no sheet in between (i.e. the zero value), the distance between measurement points. The subsequent rows contain the data: measurement point number, thickness when measuring along direction parallel to rolling direction, same in perpendicular direction. The measurement point number is 0 at the very centre, and is a distance s from the centre, where s is given by measurement point number x distance between measurement points. Toolpath.txt contains the toolpath that the tool was meant to follow. Each row is one command with each element separated by commas in the following order (all in mm) 1. Number of rotations of spindle 2. Working roller axial position (centre of 15mm nose radius) 3. Working roller radial position (centre of 15mm nose radius) 4. Blending roller axial (centre of 15mm nose radius) 5. Blending roller radial (centre of 15mm nose radius). 6. Support roller axial (Note that support rollers aren’t used so 6-8 are irrelevant). 7. Support roller top radial 8. Support roller bottom radial 9. Total velocity (units/s) – The distance “units” are given by the square root of the sum of squares of the velocity of all the tools, including the spindle, in either mm/s or rotations/s.This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/K018108/1] and the Engineering Department grant [grant number RG64379 ENG dept. project number: NMZL/064]. EPSR

Closed-loop control of product properties in metal forming: A review and prospectus

Metal forming processes today operate with astounding productivity, repeatably creating precise parts in high volumes out of the stock sheet and bar products of the upstream metals industries. This achievement has come through decades of development of ever stiffer and more precise tooling used in fast-acting tightly controlled equipment, and yet in the wider context of manufacturing, metal forming processes seem to be less effective: tooling costs are high, and can only be justified by large batch production; the parts made by metal forming are usually not as required for assembly, and must be processed in further downstream machining operations; current processes do not respond well to process disturbances such as tool wear or unanticipated variation in material properties; twenty years of laboratory development of new flexible forming processes has led to little industrial take-up, due to a lack of precision. The missing ingredient in forming which gives rise to these problems is the absence of effective closed-loop control of product properties. The normal practice for blacksmiths and craft workers in former times - using their personal senses to adjust processing in response to evolving conditions - has been forgotten in the pursuit of process rigidity. This paper therefore aims to motivate a new wave of interest in applying closed-loop control of product properties to metal forming processes. A novel framework is developed to show metal forming processes at the heart of an outer control loop, and existing applications are reviewed. Surveys of sensors, actuators and modelling techniques reveal a rich seam of opportunities for new developments, and the paper concludes with some suggestions about near term opportunities for applying closed-loop control of properties to metal forming processes. © 2014 The Authors