Evaluation and Visualization of Surface Defects a Numerical and Experimental Study on Sheet-Metal Parts

Transcription

1 Evaluation and Visualization of Surface Defects a Numerical and Experimental Study on Sheet-Metal Parts A. Andersson Volvo Car Corporation, Body Components, Olofström, Sweden Abstract. The ability to predict surface defects in outer panels is of vital importance in the automotive industry, especially for brands in the premium car segment. Today, measures to prevent these defects can not be taken until a test part has been manufactured, which requires a great deal of time and expense. The decision as to whether a certain surface is of acceptable quality or not is based on subjective evaluation. It is quite possible to detect a defect by measurement, but it is not possible to correlate measured defects and the subjective evaluation. If all results could be based on the same criteria, it would be possible to compare a surface by both FE simulations, experiments and subjective evaluation with the same result. In order to find a solution concerning the prediction of surface defects, a laboratory tool was manufactured and analysed both experimentally and numerically. The tool represents the area around a fuel filler lid and the aim was to recreate surface defects, so-called "teddy bear ears". A major problem with the evaluation of such defects is that the panels are evaluated manually and to a great extent subjectivity is involved in the classification and judgement of the defects. In this study the same computer software was used for the evaluation of both the experimental and the numerical results. In this software the surface defects were indicated by a change in the curvature of the panel. The results showed good agreement between numerical and experimental results. Furthermore, the evaluation software gave a good indication of the appearance of the surface defects compared to an analysis done in existing tools for surface quality measurements. Since the agreement between numerical and experimental results was good, this indicates that these tools can be used for an early verification of surface defects in outer panels. Key words: Surface defects, Sheet metal forming, Simulation, Finite element method INTRODUCTION The ability to predict surface defects in outer panels is of vital importance in the automotive industry, particularly for cars in the upper segment of the market. Today, measures to prevent these defects can not be taken until a test part has been manufactured, which involves the expenditure of much time and money. of sheet-metal-forming simulations in the automotive industry. Today it is possible to predict thinning, strain distribution and forces to a high accuracy, but there are still challenges to be overcome. One challenge is the prediction of surface defects. Surface defects are small deviations from the nominal surface of a panel, and can be of varying size and depth. The defects can appear as: If these defects could be predicted at an early stage in the development process, the time and cost reduction would be significant. A means for achieving this is to use sheet-metal-forming simulation. The use of this type of simulations has become more common in the automotive industry over the past decade and are efficient tools in many applications. Makinouchi [1] and Makinouchi et al. [2] have described various uses 113

2 Depressions Elevations Bimps Orange peel-like Local thinning Defects with relatively large depths (wrinkles) are visible by an optical check, while small defects are detected by a method in which a specialist manually examines the panel. Surface defects often appear on relatively flat panels with some kind of embossment, e.g. on doors in the area of the door handle, and on rear fenders with a fuel filler lid. The areas around the corners of the embossments will be subjected to compressive stresses. Since the panels usually have low stiffness in these areas, and the plastic strains are insignificant, they are very sensitive to springback which results in surface defects. Today there are methods to detect small defects on auto-body panels by using interference of light [3]. These methods are able to visualise the defects, but are limited in efficiency, and the interpretation of the results is difficult. This work shows a method where experimental and numerical assessment of surface defects is done with a common software. The advantage with this is that the assessment of the surface will be based on the same scale, independent of if it is assessed by experimental or numerical procedures. METHOD At Volvo Car Corporation, manual inspection is used in the assessment of surface defects. The evaluation is done either by stroking the hand over the surface or by application of a gloss and inspection of the surface in a ramp of directed light sources. The inspector uses a scale from 1 to 10, where 1 is worst and 10 is best. Both the geometry and location of the defects are regarded in the assessment. This method of assessment is based on subjective judgement and is difficult to use when comparison to numerical results is to be performed. It is possible to compare experimental and numerical results qualitatively but not quantitatively, since different evaluation scales are used. In order to have the same evaluation scale in numerical and experimental assessment of surface defects, it is necessary to have the same evaluation methodology or software. Figure 1 describes how such a methodology can be reached Simulation Comparison of result (e.g. draw-in) Experiments Manufacturing of part OBJECTIVE The objective of this study is to investigate whether simulation of forming can be used in the prediction of surface defects. It includes a proposal of a method for comparing simulation results and experimental results using the same software. By using the same analysing instrument for the evaluation of numerical and experimental results, the ability to compare experimental and simulation results will increase. This also simplifies the dialog between pre-production and production, since the same criteria are used. Transform point cloud into mesh* *The transformation of the point cloud into a mesh was done in TEBIS [4]. FIGURE 1. Methodology for surface evaluation. 114

3 It is important that an accurate prediction of the springback is reached. In order to investigate if surface defects could be detected and evaluated, a test model, a double curved panel, was evaluated. This was a part of the IMS-project 3DS (contract G1RD-CT ) [5]. For confirmation of the applicability in a real production process an automotive part, a Volvo S40 door, was analysed. The study was limited to experimental evaluation, and the part was measured in the WMS-system/NXT post processor and in the D- Sight system. The results were then compared. MEASUREMENT SYSTEM, WMS AND EVALUATION PROGRAM, NXT POST PROCESSOR In this study a system called WMS was used for surface measurement of the experimental parts. The system is described by Max [6]. The accuracy in height is 0.01mm on a surface of 1m 2. As an evaluation program the NXT post processor was used. This program was developed during the 3DS-project and is developed from a method described by Kase et al [7]. In the NXT post processor it is possible to detect changes in curvature. These changes indicate a change in geometry. If the change in geometry is not a design feature, it is regarded as a defect. With this software both experimental and numerical results can be evaluated. Since the software evaluates both kinds of results with the same method, the results can be compared in the same scale. The surface quality from both experiments and FE simulations can therefore be analysed both quantitatively and qualitatively in this software. It is also possible to compare numerical and experimental results in the same scale. TABLE 1. Material characteristics. Material t R p0.2 R0 R45 R90 n [mm] [MPa] DP600 0, EXPERIMENTAL EVALUATION OF A DOUBLE-CURVED PANEL As a test model a double curved test panel with an embossment was used. This model resembles the area around the fuel filler lid on an automotive body side. In order to have a uniform and well conditioned blank holder pressure, gas springs were mounted around the punch and were internally connected. Furthermore, the depth of the embossment was adjustable by applying/removing distance plates under the embossment punch. The punch force, draw-in, amount of lubrication, deflection after springback and surface quality was measured. The position of the evaluated draw-in and sections can be seen in figure 2. y Dx1 x Dy1 Dy2 Dx2 Section A Section B FIGURE 2. Measurement of draw-in and evaluated sections. Section A corresponds to y=-58 and section B to y=-130. In order to see the variation in the experiments, eight panels were manufactured. In the current report results for panel #4-8 are presented. MATERIAL CHARACTERISTICS For the double-curved panel, DP600 was analysed. The material characteristics can be found in table 1. In the S40 door, mild steel (V-1158) was used. 115

4 SIMULATION OF A DOUBLE-CURVED PANEL The simulations were performed in the dynamic explicit code LS-DYNA [8, 9]. LS-DYNA's fully integrated elements [8] with 5 integration points through the thickness were used for both forming and springback simulation. Adaptive mesh was used with element size from 8 to 1 mm [10]. The coefficient of friction, was fitted to the punch force and the draw in. Convergent results was found for =0.1.Two material models were compared, the Hill 48 [11] and the Barlat 89 [12] models. For Barlat s model stress exponent m=6 was used. The kinematic hardening was only implemented and evaluated with the Hill 48-model. made with results from a system, which is used for detection of surface defects, D-Sight [14]. RESULTS Double-Curved Panel The predicted results were good, and the surface defects detected in the experiments could be predicted in the simulations. A comparison of the numerical and experimental results can be seen below. Springback The springback was measured in two different sections. The analysed sections can be found in figure 2. The results from the simulations can be seen in figure 4. The detailed material characterisation of the material, as well as the selection and identification of appropriate material models, was done within the 3DS-project [13]. EXPERIMENTAL EVALUATION OF THE S40 DOOR In order to have a real automotive part as a test model, a section of a door panel, was analysed. The door which was used is the Volvo S40 rear door. This part was analysed after the first forming step and can be seen in figure 3. The area which was analysed is marked with a rectangle. Z-coordinate Z-coordinate DP600, section A X-coordinate DP600, section B X-coordinate Experiment #4-8 Hill, isotropic Barlat, isotropic Hill, mixed Reference Experiment #4-8 Hill, isotropic Barlat, isotropic Hill, mixed Reference Analysed area FIGURE 3. Volvo S40 rear door after the first forming step. FIGURE 4. Springback in evaluated sections, material DP600. The different hardening- and material models showed similar results which are in good agreement with the experimental results regarding the small amount of springback. The door was analysed with the WMSsystem/NXT post processor, and comparisons were 116

5 Surface Defects The surface defects are visualised in the NXT post processor and the results can be seen in figure 5. The results are taken in the x-direction. In these figures the scale was set to [1/m]. The original curvature of the punch is [1/m]. Blue indicates depression and red indicates elevation. The results were also compared to D-Sight results. In the D-Sight results the curvature is visualised by a change in darkness. This change corresponds to the blue and red areas in the WMS-results. Red corresponds to light and blue to dark areas. Evaluation in D-Sight S40 Door In order to test the NXT post processor as evaluation system, a door outer was analysed. The door was also analysed in the D-Sight system for comparison. The results are illustrated in figure 6. These defects are very small and by visual inspection the defect in the handle area was rated and got an 8 in the VCBC rating system. D-Sight Dents WMS Scale Convex Concave Increasing curvature Evaluation in WMS/NXT post processor FIGURE 6. Application of two systems for detecting surface effects to a production part (door outer). Areas marked with circles are dent areas. Experiments Hill, isotropic hardening FIGURE 5. Curvature evaluations with D-Sight and the WMS/NXT post processor. In figure 5 it can be seen that the surface defects mainly appears as large waves on the surface (shift in curvature value). The results achieved with the WMSmeasurement and NXT post processor shows good agreement with the results obtained with the D-Sight system for all materials. It can be concluded that the experimental results, obtained with the WMS/NXT post processor are reliable. It can also be seen that the results from the FE simulations also show good agreement with the experimental results. The appearance of teddy bear ears can not directly be seen, but the area around the embossment shows a dent around the whole embossment. DISCUSSION AND CONCLUSION Based on the results it can be concluded that the methodology used in this study can be used for predicting and verifying the appearance of surface defects. The strength in the used methodology is that the same evaluation software, the NXT post processor, is used for evaluation of both numerical and experimental results. In the study of the double-curved panel, both different hardening models and material models were tested. The results were similar. The results from the Volvo S40-door showed that the different systems, the D-Sight and the WMS/NXT post processor, indicated the same regions with defects. However, the distribution was slightly different. This can depend on differences in point density for the measurement points, differences in accuracy between D-Sight and WMS-system or errors introduced in the transformation process from point cloud into mesh (in TEBIS) for the WMSmeasurement. Still, it is very difficult to compare the results quantitatively, since different criteria are used. For this more comparisons need to be done. 117

6 ACKNOWLEDGMENTS The author is grateful to Fredrik Krantz (ProEngCo) for valuable help with the experimental part within this project. Furthermore Erland Max, Leo Gurmark, Ola Claesson (Volvo Corp resp. Volvo Cars, Body Components) have been very helpful with the surface measurements. Thanks are also due to Professor Kjell Mattiasson (Chalmers University of Technology) both with help of implementation of the hardening law and in the discussions during the project. Another big help has been Claes Magnusson (Volvo Cars, Body Components) and Professor Jan- Eric Ståhl (Division of Production and Materials Engineering, Lund University). 11. R. Hill, A Theory of the Yielding and Plastic Flow of Anisotropic Metals, Proceedings of the Royal Society of London, series A. 193, 1948, page F. Barlat and J. Lian, Plastic behaviour and stretchability of sheet metals, Part I, A yield function for orthotropic sheets under plane stress conditions, Int. Journal of Plasticity 5, 1989, pp C. Teodosiu and S. Bouvier, Selection and identification of Elastoplastic Models for the Materials used in the benchmarks, 18-months progress report, "3DS, Digital Die Design System", contract G1RD-CT (not yet published). 14. D-Sight: February (2004). REFERENCES 1. A. Makinouchi, Sheet Metal Forming Simulation In Industry. Journal of Materials Processing Technology, 60, 1996, pp A. Makinouchi, C. Teodosiu, and T. Nakagawa, Advances in FEM Simulation and its Related Technologies in Sheet Metal Forming. CIRP Annals - Manufacturing Technology 47(2), 1998, pp Kinell L., Optical Shape Measurements using Temporal Phase Unwrapping, Doctoral thesis, Luleå University of Technology, Sweden, (2003) 4. TEBIS: February (2004) 5. A. Col, Presentation of the 3DS research project", Numisheet 2002, Jeju Island, Korea (2002). 6. E. Max, P. H. Nilsson and P. Larsson, WMS, a new principle for measuring finish-related topography on sheet steel panels, Metrology and Properties of Engineering Surfaces 9 th Int. Conference, Halmstad, Sweden (2003). 7. K. Kase, A. Makinouchi, T.Nakagawa, H. Suzuki and F. Kimura, Shape error evaluation method of free-form surfaces. Computer-Aided Design. 31(8), 1999 pp J.O. Hallquist, LS-DYNA Keyword User s Manual, Livermore Software Tech. Corp. Livermore, (2003) 9. LS-DYNA: February (2004) 10. A. Andersson and F. Krantz, Report tool #6, Numerical and experimental evaluation, "3DS, Digital Die Design System", contract G1RD-CT (not yet published). 118