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An Overview and Classification of Tolerance Compensation Methods

Part of: Robust Design

Published online by Cambridge University Press:  26 July 2019

Alexander Aschenbrenner ,
Benjamin Schleich  and
Sandro Wartzack

Abstract

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Technological advances as well as novel manufacturing and design paradigms, such as industry 4.0 and digitalization, offer new opportunities for innovative products. However, they also increase the product complexity and cause new challenges in the production process. Therefore, agile production approaches are crucial. Tolerance compensation provides more flexibility in the production process, as demands on dimensional accuracy of the components are reduced. As a result, tolerance compensation also offers the possibility of reducing production costs without compromising product quality. Nevertheless, tolerance compensation is often considered a reactive intervention to reduce the number of out-of-spec parts a posteriori instead of including it in the early stages of Geometrical Variations Management. The contribution tackles this issue by characterizing and categorizing different methods of tolerance compensation as well as providing design guidelines for the application of tolerance compensation methods. This enables design engineers to select a suitable tolerance compensation method for different applications.

Keywords

Tolerance CompensationRobust designTolerance representation and managementUncertainty
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 3471 - 3480
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Aschenbrenner, A., Schleich, B. and Wartzack, S. (2017), “The influence of sorting on the statistical behavior of functional dimensions”, 28th Symposium Design for X (DFX 2017), Bamberg/Germany, 4th-5th October 2017, TuTech Verlag, Hamburg/Germany, pp. 75–86.Google Scholar
Aschenbrenner, A. and Wartzack, S. (2017), “A Method for the Tolerance Analysis of Bearing Seats for Cylindrical Roller Bearings in Respect To Operating Clearance and Fatigue Life”, 21st International Conference on Engineering Design (ICED 17), Vancouver/Canada, 21st-25th August 2017, Design Society, Glasgow, pp. 79–88.Google Scholar
Chan, K.C. and Linn, R.J. (1998), “A grouping method for selective assembly of parts of dissimilar distributions”, Quality Engineering, Vol. 11 No. 2, pp. 221–234. http://doi.org/10.1080/08982119808919233Google Scholar
Colledani, M., Ebrahimi, D. and Tolio, T. (2014), “Integrated quality and production logistics modelling for the design of selective and adaptive assembly systems”, CIRP Annals, Vol. 63 No. 1, pp. 453–456. http://doi.org/10.1016/j.cirp.2014.03.120Google Scholar
Ebro, M. and Howard, T.J. (2016), “Robust design principles for reducing variation in functional performance”, Journal of Engineering Design, Vol. 27 No. 1–3, pp. 75–92. http://doi.org/10.1080/09544828.2015.1103844Google Scholar
Henning, F. and Moeller, E. (2011), Handbuch Leichtbau, Carl Hanser Verlag GmbH & Co. KG, Munich/Germany. http://doi.org/10.3139/9783446428911Google Scholar
Howard, T.J., Eifler, T., Pedersen, S.N., Göhler, S.M., Boorla, S.M. and Christensen, M.E. (2017), “The variation management framework (VMF): A unifying graphical representation of robust design”, Quality Engineering, Vol. 29 No. 4, pp. 563–572. http://doi.org/10.1080/08982112.2016.1272121Google Scholar
Lanza, G., Haefner, B. and Kraemer, A. (2015), “Optimization of selective assembly and adaptive manufacturing by means of cyber-physical system based matching”, CIRP Annals, Vol. 64 No. 1, pp. 399–402. http://doi.org/10.1016/j.cirp.2015.04.123Google Scholar
Lindkvist, L., Carlson, J.S. and Söderberg, R. (2005), “Virtual Locator Trimming in Pre-Production: Rigid and Non-Rigid Analysis”, ASME International Mechanical Engineering Congress and Exposition (IMECE), Orlando/USA, 5th-11th November 2005, ASME, pp. 561–568. http://doi.org/10.1115/IMECE2005-81266Google Scholar
Litwa, F., Gottwald, M., Forstmeier, J. and Vielhaber, M. (2015), “Determination Of Functional Intersections Between Multiple Tolerance-Chains By The Use Of The Assembly-Graph”, NAFEMS World Congress 2015, San Diego/USA, 21st-24th June 2015, pp. 189–203.Google Scholar
Liu, M., Liu, C. and Zhu, Q. (2014), “Optional classification for reassembly methods with different precision remanufactured parts”, Assembly Automation, Vol. 34 No. 4, pp. 315–322. http://doi.org/10.1108/AA-03-2014-023Google Scholar
Mansoor, E.M. (1961), “Selective assembly — its analysis and applications”, International Journal of Production Research, Vol. 1 No. 1, pp. 13–24. http://doi.org/10.1080/00207546108943070Google Scholar
Martello, S. and Toth, P. (1990), Knapsack Problems: Algorithms and Computer Implementations, John Wiley & Sons, Inc., New York/USA.Google Scholar
Oberleiter, T., Heling, B., Schleich, B., Willner, K. and Wartzack, S. (2018), “Fuzzy Sensitivity Analysis in the Context of Dimensional Management”, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, Vol. 5 No. 1, pp. 011008–011008-7. http://doi.org/10.1115/1.4040919Google Scholar
Oh, H.L. (2004), “Unifying axiomatic design and robust design through the transfer function”, The Third International Conference on Axiomatic Design (ICAD2004), Seoul/South Korea, 21st-24th June 2005, pp. 1–4.Google Scholar
Rathert, T., Witzgall, C. and Wartzack, S. (2018), “Modular rapid design of multi-material lightweight truss structures – A novel approach”, Symposium Lightweight Design in Product Development, Zurich/Switzerland, 14th-15th June 2018, CMASLab, ETH Zurich, Zurich/Switzerland, pp. 21–23. http://doi.org/10.3929/ethz-b-000283432Google Scholar
Schleich, B., Anwer, N., Mathieu, L. and Wartzack, S. (2016), “Status and Prospects of Skin Model Shapes for Geometric Variations Management”, Procedia CIRP, Vol. 43, pp. 154–159. http://doi.org/10.1016/j.procir.2016.02.005Google Scholar
Schleich, B., Anwer, N., Mathieu, L. and Wartzack, S. (2017), “Shaping the digital twin for design and production engineering”, CIRP Annals, Vol. 66 No. 1, pp. 141–144. http://doi.org/10.1016/j.cirp.2017.04.040Google Scholar
Schleich, B., Wärmefjord, K., Söderberg, R. and Wartzack, S. (2018), “Geometrical Variations Management 4.0: Towards next Generation Geometry Assurance”, Procedia CIRP, Vol. 75, pp. 3–10. http://doi.org/10.1016/j.procir.2018.04.078Google Scholar
Schleich, B. and Wartzack, S. (2013), “How to determine the influence of geometric deviations on elastic deformations and the structural performance?”, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 227 No. 5, pp. 754–764. http://doi.org/10.1177/0954405412468994Google Scholar
Schleich, B. and Wartzack, S. (2018), “An Approach to the Sensitivity Analysis in Variation Simulations considering Form Deviations”, Procedia CIRP, Vol. 75, pp. 273–278. http://doi.org/10.1016/j.procir.2018.03.314Google Scholar
Schwarzbich, J. (2012), US patent US9074614B2: “Tolerance compensation member”.Google Scholar
Söderberg, R. and Johannesson, H. (1999), “Tolerance Chain Detection by Geometrical Constraint Based Coupling Analysis”, Journal of Engineering Design, Vol. 10 No. 1, pp. 5–24. http://doi.org/10.1080/095448299261399Google Scholar
Söderberg, R. and Lindkvist, L. (1999), “Computer Aided Assembly Robustness Evaluation”, Journal of Engineering Design, Vol. 10 No. 2, pp. 165–181. http://doi.org/10.1080/095448299261371Google Scholar
Söderberg, R., Wärmefjord, K., Carlson, J.S. and Lindkvist, L. (2017), “Toward a Digital Twin for real-time geometry assurance in individualized production”, CIRP Annals, Vol. 66 No. 1, pp. 137–140. http://doi.org/10.1016/j.cirp.2017.04.038Google Scholar
Suh, N.P. (1989), The principles of design, Oxford University Press, New York/USA.Google Scholar
Taguchi, G., Chowdhury, S. and Wu, Y. (2004), Taguchi's Quality Engineering Handbook, John Wiley & Sons, Inc., Hoboken/USA. http://doi.org/10.1002/9780470258354Google Scholar
Wärmefjord, K., Söderberg, R., Lindkvist, L., Lindau, B. and Carlson, J. S. (2017) “Inspection Data to Support a Digital Twin for Geometry Assurance”, ASME 2017 International Mechanical Engineering Congress and Exposition, Tampa/USA, 3rd-9th November 2017, ASME, http://doi.org/10.1115/IMECE2017-70398Google Scholar