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Optimized Routine of Machining Distortion Characterization Based on Gaussian Surface Curvature

Authors Destiny R. Garcia, Barbara S. Linke , Rida T. Farouki

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Author Details

Destiny R. Garcia
  • Mechanical and Aerospace Engineering Department, University of California Davis, CA, USA
Barbara S. Linke
  • Mechanical and Aerospace Engineering Department, University of California Davis, CA, USA
Rida T. Farouki
  • Mechanical and Aerospace Engineering Department, University of California Davis, CA, USA

Funding

  • Garcia, Destiny R.: partially funded by NSF award No. 1663341.
  • Linke, Barbara S.: partially funded by NSF award No. 1663341.

Acknowledgements

Thank you to Michael Hill, UC Davis for guiding the machining distortion research. Many thanks to Christopher D'Elia and Renan Ribeiro, both UC Davis, for designing and machining the samples. We express our sincere thanks to Jan Aurich, Benjamin Kirsch, and Daniel Weber at TU Kaiserslautern for discussing the distortion application. All above mentioned researchers are collaborators on the NSF/DFG Collaboration to Understand the Prime Factors Driving Distortion in Milled Aluminum Workpieces, funded through NSF Award No. 1663341 and DFG Project No. 351381681. We also thank Jörg Seewig from TU Kaiserslautern for the helpful discussions on metrology. We furthermore interact in the IRTG 2057 Physical Modeling for Virtual Manufacturing Systems and Processes, funded by DFG.

Cite AsGet BibTex

Destiny R. Garcia, Barbara S. Linke, and Rida T. Farouki. Optimized Routine of Machining Distortion Characterization Based on Gaussian Surface Curvature. 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. 5:1-5:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.iPMVM.2020.5

Abstract

Machining distortion presents a significant problem in products with high residual stresses from materials processing and re-equilibration after machining removes a large part of the material volume and is common in the aerospace industries. While many papers research on mechanisms of machining distortion, few papers report on the measurement, processing and characterization of distortion data. Oftentimes only line plot data is used to give a maximum distortion value. This paper proposes a method of measurement tool selection, measurement parameter selection, data processing through filtering and leveling, and use of Bézier Surfaces and Gaussian Curvature for distortion characterization. The method is demonstrated with three sample pieces of different pocket geometry from quenched aluminum. It is apparent that samples with machining distortion can have complex surface shapes, where Bézier Surfaces and Gaussian Curvature provide more information than the commonly used 2D line plot data.

Subject Classification

ACM Subject Classification
  • Applied computing → Engineering
Keywords
  • Machining distortion
  • Metrology
  • Gaussian curvature

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References

  1. S. Bell. Measurement Good Practice Guide No. 11. A Beginner’s Guide to Uncertainty of Measurement. Tech. rep., National Physical Laboratory, 1999. Google Scholar
  2. Yun-bo Bi, Qun-lin Cheng, Hui-yue Dong, and Ying-lin Ke. Machining distortion prediction of aerospace monolithic components. Journal of Zhejiang University-SCIENCE A, 2009. URL: https://doi.org/10.1631/jzus.a0820392.
  3. DM Bowden and JE Halley. Aluminum reliability improvement program final report 60606. The Boeing Company, Chicago, IL, USA, 2001. Google Scholar
  4. E. Brinksmeier, J.T. Cammett, W. König, P. Leskovar, J. Peters, and H.K. Tönshoff. Residual stresses — measurement and causes in machining processes. CIRP Annals, 31(2):491-510, 1982. URL: https://doi.org/10.1016/S0007-8506(07)60172-3.
  5. E. Brinksmeier and Jens Sölter. Prediction of shape deviations in machining. CIRP Annals, 58:507-510, December 2009. URL: https://doi.org/10.1016/j.cirp.2009.03.123.
  6. D. Chantzis, S. Van der Veen, J.Zettler, and W.M. Sim. An industrial workflow to minimise part distortion for machining of large monolithic components in aerospace industry. Procedia CIRP, 8:281-286, 2013. 14th CIRP Conference on Modeling of Machining Operations (CIRP CMMO). URL: https://doi.org/10.1016/j.procir.2013.06.103.
  7. M Conroy and J Armstrong. A comparison of surface metrology techniques. Journal of Physics: Conference Series, 13:458–465, 2005. Google Scholar
  8. Richard Leach David Flack, James Claverley. Chapter 9 - coordinate metrology. In Richard Leach, editor, Fundamental Principles of Engineering Nanometrology (Second Edition), Micro and Nano Technologies, pages 295-325, Oxford, 2014. William Andrew Publishing. URL: https://doi.org/10.1016/B978-1-4557-7753-2.00009-8.
  9. Rida T. Farouki. The bernstein polynomial basis: A centennial retrospective. Computer Aided Geometric Design, 29(6):379 – 419, 2012. URL: https://doi.org/10.1016/j.cagd.2012.03.001.
  10. Joint Committee for Guides in Metrology. JCGM 104:2009. Evaluation of measurement data – An introduction to the "Guide to the expression of uncertainty in measurement" and related documents, volume First edition. JCGM, 2009. Google Scholar
  11. International Organization for Standardization. ISO 10360-1:2000 geometrical product specifications (gps) — acceptance and reverification tests for coordinate measuring machines (cmm) — part 1: Vocabulary). Vernier, Geneva, Switzerland, 2000. Google Scholar
  12. Destiny R. Garcia, Michael R. Hill, Jan C. Aurich, and Barbara S. Linke. Characterization of machining distortion due to residual stresses in quenched aluminum. Proceedings of the ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing, Volume 1: Processes, June 2017. V001T02A031. URL: https://doi.org/10.1115/MSEC2017-2878.
  13. M. Gulpak, J. Sölter, and E. Brinksmeier. Prediction of shape deviations in face milling of steel. In Procedia CIRP, 2013. URL: https://doi.org/10.1016/j.procir.2013.06.058.
  14. Michael Hill, Christopher D’Elia, Renan Ribeiro, and Julianne Emily Jonsson. Measurement and prediction of distortion from bulk residual stress in aluminum 7050 coupons (in preparation). TBD, 2021. Google Scholar
  15. Xiaoming Huang, Jie Sun, and Jianfeng Li. Finite element simulation and experimental investigation on the residual stress-related monolithic component deformation. International Journal of Advanced Manufacturing Technology, 2015. URL: https://doi.org/10.1007/s00170-014-6533-9.
  16. Rémi Husson, Jean-Yves Dantan, Cyrille Baudouin, Serge Silvani, Thomas Scheer, and Régis Bigot. Evaluation of process causes and influences of residual stress on gear distortion. CIRP Annals, 61(1):551-554, 2012. URL: https://doi.org/10.1016/j.cirp.2012.03.106.
  17. ASTM International. ASTM E2782-17 standard guide for measurement systems analysis (msa). West Conshohocken, PA, 2017. URL: https://doi.org/10.1520/E2782-17.
  18. S. Jayanti, D. Ren, E. Erickson, Shuji Usui, T. Marusich, K. Marusich, and H. Elanvogan. Predictive modeling for tool deflection and part distortion of large machined components. Procedia CIRP, 12:37–42, December 2013. URL: https://doi.org/10.1016/j.procir.2013.09.008.
  19. Fritz Klocke. Manufacturing Processes 1. Springer Berlin Heidelberg, 2011. URL: https://doi.org/10.1007/978-3-642-11979-8.
  20. Ismail Lazoglu, Durul Ulutan, B. Alaca, Serafettin Engin, and Bilgin Kaftanoğlu. An enhanced analytical model for residual stress prediction in machining. CIRP Annals - Manufacturing Technology, 57:81-84, December 2008. URL: https://doi.org/10.1016/j.cirp.2008.03.060.
  21. Jian-guang Li and Shu-qi Wang. Distortion caused by residual stresses in machining aeronautical aluminum alloy parts: recent advances. The International Journal of Advanced Manufacturing Technology, 89:997-1012, March 2017. URL: https://doi.org/10.1007/s00170-016-9066-6.
  22. Karsten Luebke. Coordinate measuring machine. In Luc Laperrière and Gunther Reinhart, editors, CIRP Encyclopedia of Production Engineering, pages 285-289, Berlin, Heidelberg, 2014. Springer Berlin Heidelberg. URL: https://doi.org/10.1007/978-3-642-20617-7_6579.
  23. Ninshu Ma and Hui Huang. Efficient simulation of welding distortion in large structures and its reduction by jig constraints. Journal of Materials Engineering and Performance, 26:5206-5216, 2017. Google Scholar
  24. Daniel Jon Mitchell, Eran Tal, and Hasok Chang. The making of measurement: Editors’ introduction. Studies in History and Philosophy of Science Part A, 65-66:1-7, 2017. The Making of Measurement. URL: https://doi.org/10.1016/j.shpsa.2017.10.001.
  25. Enrico Savio, L. Chiffre, Simone Carmignato, and J. Meinertz. Economic benefits of metrology in manufacturing. CIRP Annals - Manufacturing Technology, 65:495-498, January 2016. URL: https://doi.org/10.1016/j.cirp.2016.04.020.
  26. Wei-Ming Sim. Challenges of residual stress and part distortion in the civil airframe industry. International Journal of Microstructure and Materials Properties, 5, December 2010. URL: https://doi.org/10.1504/IJMMP.2010.037621.
  27. Jerzy A. Sładek. Coordinate Metrology. Springer Berlin Heidelberg, 2016. URL: https://doi.org/10.1007/978-3-662-48465-4.
  28. Klaus-Dieter Thoben, Thomas Lübben, Brigitte Clausen Christian Prinz, Alwin Schulz, Rüdiger Rentsch, Ralf Kusmierz, Lutz Nowag, Holger Surm, Friedhelm Frerichs, Martin Hunkel, Dieter Klein, and Peter May. Distortion Engineering: Eine systemorientierte Betrachtung des Bauteilverzugs. HTM - Haerterei-Technische Mitteilungen, 57:276-282, April 2002. Google Scholar
  29. PF FEng Y Ma, S Liu and DW Yu. Finite element analysis of residual stresses and thin plate distortion after face milling. In 12th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Islamabad, pages 67-71, 2015. URL: https://doi.org/10.1109/IBCAST.2015.7058481.
  30. Zheng Zhang, Liang Li, Yinfei Yang, Ning He, and Wei Zhao. Machining distortion minimization for the manufacturing of aeronautical structure. International Journal of Advanced Manufacturing Technology, 2014. URL: https://doi.org/10.1007/s00170-014-5994-1.
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