Interactive Quality Inspection of Measured Deviations in Sheet Metal Assemblies

Authors Felix Claus , Hans Hagen, Viktor Leonhardt , Heike Leitte, Bernd Hamann



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Author Details

Felix Claus
  • Computer Graphics & HCI Lab, Computer Science Department, Technische Universität Kaiserslautern, Germany
Hans Hagen
  • Computer Graphics & HCI Lab, Computer Science Department, Technische Universität Kaiserslautern, Germany
Viktor Leonhardt
  • Scientific Visualization Lab, Computer Science Department, Technische Universität Kaiserslautern, Germany
Heike Leitte
  • Visual Information Analysis, Computer Science Department, Technische Universität Kaiserslautern, Germany
Bernd Hamann
  • Department of Computer Science, University of California, Davis, CA 95616, USA

Acknowledgements

We thank Q-DAS GmbH for providing CAD models.

Cite AsGet BibTex

Felix Claus, Hans Hagen, Viktor Leonhardt, Heike Leitte, and Bernd Hamann. Interactive Quality Inspection of Measured Deviations in Sheet Metal Assemblies. In 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020). Open Access Series in Informatics (OASIcs), Volume 89, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.iPMVM.2020.6

Abstract

We present an exploratory data analysis approach for finite element (FE) simulations to interactively inspect measured deviations in sheet metals arising in automotive applications. Exterior car body parts consist of large visible surfaces, and strict tolerances must be met by them to satisfy both aesthetic requirements and quality performance requirements. To fulfill quality requirements like gap and flushness, exterior vehicle components have adjustable mechanical boundaries. These boundaries are used to influence the shape and position of a sheet metal part relative to its chassis. We introduce a method that supports an inspection engineer with an interactive framework that makes possible a detailed analysis of measured sheet metal deviation fields generated from 3D scans. An engineer can interactively change boundary conditions and obtains the resulting deviation field in real-time. Thus, it is possible to determine viable and desirable adjustments efficiently, leading to time and cost savings in the assembly process.

Subject Classification

ACM Subject Classification
  • Applied computing
Keywords
  • Data Analysis
  • Interactive Inspection
  • 3D-Metrology
  • Finite Element Simulation

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References

  1. OEIS Foundation Inc. (2020). The On-Line Encyclopedia of Integer Sequences, 2020. URL: https://oeis.org/A038207.
  2. Manoj Babu, Pasquale Franciosa, and Dariusz Ceglarek. Spatio-temporal adaptive sampling for effective coverage measurement planning during quality inspection of free form surfaces using robotic 3d optical scanner. Journal of Manufacturing Systems, 53:93-108, 2019. URL: https://doi.org/10.1016/j.jmsy.2019.08.003.
  3. Erin Santini Bell, Masoud Sanayei, Chitra N. Javdekar, and Eugene Slavsky. Multiresponse parameter estimation for finite-element model updating using nondestructive test data. Journal of Structural Engineering, 133(8):1067-1079, 2007. URL: https://doi.org/10.1061/(ASCE)0733-9445(2007)133:8(1067).
  4. T. Bui-Thanh, M. Damodaran, and K. Willcox. Aerodynamic data reconstruction and inverse design using proper orthogonal decomposition. AIAA Journal, 42(8):1505-1516, 2004. URL: https://doi.org/10.2514/1.2159.
  5. Jaime Camelio, S. Jack Hu, and Dariusz Ceglarek. Modeling Variation Propagation of Multi-Station Assembly Systems With Compliant Parts . Journal of Mechanical Design, 125(4):673-681, January 2004. URL: https://doi.org/10.1115/1.1631574.
  6. Jaime A. Camelio, S. Jack Hu, and Dariusz Ceglarek. Impact of fixture design on sheet metal assembly variation. Journal of Manufacturing Systems, 23(3):182-193, 2004. URL: https://doi.org/10.1016/S0278-6125(05)00006-3.
  7. Johan S. Carlson and Rikard Söderberg. Assembly root cause analysis: A way to reduce dimensional variation in assembled products. International Journal of Flexible Manufacturing Systems, 15(2):113-150, 2003. URL: https://doi.org/10.1023/A:1024453207632.
  8. F Claus, H Hagen, H Leitte, and B Hamann. Decomposing deviations of scanned surfaces of sheet metal assemblies[submitted]. Journal of Manufacturing Systems, 2020. Google Scholar
  9. Christopher Fleischmann, Irina Leher, Reinhold Hartwich, Marc Hainke, and Stefan Sesselmann. A new approach to quickly edit geometries and estimate stresses and displacements of implants in real-time. Current Directions in Biomedical Engineering, 5(1):553-556, 2019. URL: https://doi.org/10.1515/cdbme-2019-0139.
  10. Richard Franke. Scattered data interpolation: Tests of some method. Mathematics of Computation, 38(157):181-200, 1982. URL: http://www.jstor.org/stable/2007474.
  11. A. S. Gendy and A. F. Saleeb. Nonlinear material parameter estimation for characterizing hyper elastic large strain models. Computational Mechanics, 25(1):66-77, 2000. URL: https://doi.org/10.1007/s004660050016.
  12. Stratos Idreos, Olga Papaemmanouil, and Surajit Chaudhuri. Overview of data exploration techniques. In Timos Sellis, Susan B. Davidson, and Zack Ives, editors, Compilation proceedings of the 2015 ACM Symposium on Principles of Database Systems, ACM SIGMOD International Conference on Management of Data, and SIGMOD/PODS 2015 PhD symposium, May 31 - June 4, 2015, Melbourne, VIC, Australia, pages 277-281, New York, NY, 2015. ACM. URL: https://doi.org/10.1145/2723372.2731084.
  13. Michael L. Johnson and Lindsay M. Faunt. Parameter estimation by least-squares methods. In Numerical Computer Methods, volume 210 of Methods in Enzymology, pages 1-37. Academic Press, 1992. URL: https://doi.org/10.1016/0076-6879(92)10003-V.
  14. Gergely Kristóf and Bálint Papp. Application of gpu-based large eddy simulation in urban dispersion studies. Atmosphere, 9(11):442, 2018. URL: https://doi.org/10.3390/atmos9110442.
  15. Xiaoyun Liao and G. Gary Wang. Simultaneous optimization of fixture and joint positions for non-rigid sheet metal assembly. The International Journal of Advanced Manufacturing Technology, 36(3):386-394, 2008. URL: https://doi.org/10.1007/s00170-006-0827-5.
  16. S. C. Liu, S. J. Hu, and T. C. Woo. Tolerance Analysis for Sheet Metal Assemblies. Journal of Mechanical Design, 118(1):62-67, March 1996. URL: https://doi.org/10.1115/1.2826857.
  17. Cong Lu and Hong-Wang Zhao. Fixture layout optimization for deformable sheet metal workpiece. The International Journal of Advanced Manufacturing Technology, 78(1):85-98, 2015. URL: https://doi.org/10.1007/s00170-014-6647-0.
  18. Kuan Lu, Yulin Jin, Yushu Chen, Yongfeng Yang, Lei Hou, Zhiyong Zhang, Zhonggang Li, and Chao Fu. Review for order reduction based on proper orthogonal decomposition and outlooks of applications in mechanical systems. Mechanical Systems and Signal Processing, 123:264-297, 2019. URL: https://doi.org/10.1016/j.ymssp.2019.01.018.
  19. Yuki Mori and Takeo Igarashi. Plushie. ACM Transactions on Graphics, 26(99):45, 2007. URL: https://doi.org/10.1145/1239451.1239496.
  20. Giulio Reina, Matilde Paiano, and Jose-Luis Blanco-Claraco. Vehicle parameter estimation using a model-based estimator. Mechanical Systems and Signal Processing, 87:227-241, 2017. Signal Processing and Control challenges for Smart Vehicles. URL: https://doi.org/10.1016/j.ymssp.2016.06.038.
  21. Evan Strasnick, Maneesh Agrawala, and Sean Follmer. Scanalog. In Krzysztof Gajos, Jennifer Mankoff, and Chris Harrison, editors, Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, pages 321-330, New York, NY, USA, 10202017. ACM. URL: https://doi.org/10.1145/3126594.3126618.
  22. Mario Teixeira Parente, Steven Mattis, Shubhangi Gupta, Christian Deusner, and Barbara Wohlmuth. Efficient parameter estimation for a methane hydrate model with active subspaces. Computational Geosciences, 23(2):355-372, 2019. URL: https://doi.org/10.1007/s10596-018-9769-x.
  23. Steven K. Thompson. Adaptive cluster sampling. Journal of the American Statistical Association, 85(412):1050-1059, 1990. URL: https://doi.org/10.1080/01621459.1990.10474975.
  24. J. Whyte, N. Bouchlaghem, A. Thorpe, and R. McCaffer. From cad to virtual reality: modelling approaches, data exchange and interactive 3d building design tools. Automation in Construction, 10(1):43-55, 2000. URL: https://doi.org/10.1016/S0926-5805(99)00012-6.
  25. F. Yoshida, M. Urabe, and V.V. Toropov. Identification of material parameters in constitutive model for sheet metals from cyclic bending tests. International Journal of Mechanical Sciences, 40(2):237-249, 1998. URL: https://doi.org/10.1016/S0020-7403(97)00052-0.
  26. A. Zerwer, G. Cascante, and J. Hutchinson. Parameter estimation in finite element simulations of rayleigh waves. Journal of Geotechnical and Geoenvironmental Engineering, 128(3):250-261, 2002. URL: https://doi.org/10.1061/(ASCE)1090-0241(2002)128:3(250).
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