Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-19T13:06:29.720Z Has data issue: false hasContentIssue false
  • English
  • Français

IMPLEMENTATION AND INTERPRETATION OF A SCRAP AND FAILURE ORIENTED MULTI-OBJECTIVE OPTIMIZATION CONSIDERING OPERATIONAL WEAR

Published online by Cambridge University Press:  19 June 2023

Christoph Bode ,
Stefan Goetz ,
Benjamin Schleich  and
Sandro Wartzack
Christoph Bode*
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
Stefan Goetz
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
Benjamin Schleich
Affiliation:
Product Life Cycle Management, Technische Universitat Darmstadt, Otto-Berndt-StraBe 2, 64287 Darmstadt
Sandro Wartzack
Affiliation:
Friedrich-Alexander-Universitat Erlangen-Nurnberg, Engineering Design, MartensstraBe 9, 91058 Erlangen, Germany
*
Bode, Christoph, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Germany, bode@mfk.fau.de

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The tolerancing of products for manufacturing is usually performed at the end of the design process and the responsibility of the designer. Although components are commonly tolerated to ensure functionality, time-based influences, like wear, that occur during operation, are often neglected. This could result in small amounts of scrap after production, but high quantities of failure during operation. To overcome this issue, this paper presents an approach to perform a multi-objective optimization considering tolerances based on a wear simulation. Thereby, mean shifts serve as optimization variables, while the aim of the optimization is to generate an optimal ratio of scrap to failure. In addition, the optimization results are interpreted and further options for the designer are presented. Moreover, the approach is exemplary applied to a use case.

Keywords

Tolerance representation and managementOptimisationSimulationScrap and failureOperational wear
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2225 - 2234
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), 2023. Published by Cambridge University Press

References

Archard, J.F. (1953), “Contact and rubbing of flat surfaces”, Journal of Applied Physics, Vol. 24 No. 8, pp. 981–988, http://doi.Org/10.1063/1.1721448.CrossRefGoogle Scholar
Bode, C., Schleich, B. and Wartzack, S. (2022), “Consideration of operational wear in tolerance analysis for process-oriented tolerancing”, Procedia CIRP, Vol. 114, pp. 177–182, http://doi.org/10.1016Zj.procir.2022.10.024.CrossRefGoogle Scholar
Chase, K.W., Gao, J. and Magleby, S. (1995), “General 2-d tolerance analysis of mechanical assemblies with small kinematic adjustments”, Journal of Design and Manufacturing, Vol. 5, pp. 263–274.Google Scholar
Chou, C.Y. and Chang, C.L. (2001), “Minimum-loss assembly tolerance allocation by considering product degradation and time value of money”, The International Journal of Advanced Manufacturing Technology, Vol. 17 No. 2, pp. 139–146, http://doi.org/10.1007/s001700170202.CrossRefGoogle Scholar
Fortini, E. (1967), Dimensioning for interchangeable manufacture, Industrial Press, New York.Google Scholar
Halim, A.H., Ismail, I. and Das, S. (2021), “Performance assessment of the metaheuristic optimization algorithms: an exhaustive review”, Artificial Intelligence Review, Vol. 54 No. 3, pp. 2323–2409, http://doi.org/10.1007/s10462-020-09906-6.CrossRefGoogle Scholar
Hallmann, M., Schleich, B., Heling, B., Aschenbrenner, A. and Wartzack, S. (2018), “Comparison of different methods for scrap rate estimation in sampling-based tolerance-cost-optimization”, Procedia CIRP, Vol. 75, pp. 51–56, http://doi.org/10.1016/jj.procir.2018.01.005.CrossRefGoogle Scholar
Hallmann, M., Schleich, B. and Wartzack, S. (2020), “From tolerance allocation to tolerance-cost optimization: a comprehensive literature review”, The International Journal of Advanced Manufacturing Technology, Vol. 107 No. 11-12, pp. 4859–4912, http://doi.org/10.1007/s00170-020-05254-5.CrossRefGoogle Scholar
Heling, B., Hallmann, M. and Wartzack, S. (2017), “Hybrid tolerance representation of systems in motion”, Procedia CIRP, Vol. 60, pp. 50–55, http://doi.org/10.1016/jj.procir.2017.02.048.CrossRefGoogle Scholar
Heling, B., Schleich, B. and Wartzack, S. (2018), “Robust-design-optimization of mechanisms based on kinematic requirements considering uncertainties”, Procedia CIRP, Vol. 75, pp. 27–32, http://doi.org/10.1016Zj.procir.2018.04.048.CrossRefGoogle Scholar
Holm, R. (1967), Electric Contacts: Theory and Application, Springer, Berlin and Heidelberg, fourth completely rewritten edition, http://doi.org/10.1007/978-3-662-06688-1.CrossRefGoogle Scholar
Khodaygan, S. (2019), “A multiple objective framework for optimal asymmetric tolerance synthesis of mechanical assemblies with degrading components”, The International Journal of Advanced Manufacturing Technology, Vol. 100 No. 9-12, pp. 2177–2205, http://doi.org/10.1007/s00170-018-2658-6.CrossRefGoogle Scholar
Konak, A., Coit, D.W. and Smith, A.E. (2006), “Multi-objective optimization using genetic algorithms: A tutorial”, Reliability Engineering & System Safety, Vol. 91 No. 9, pp. 992–1007, http://doi.org/10.1016/jj.ress.2005.11. 018.CrossRefGoogle Scholar
Liu, X., Mao, K., Wang, X., Wang, X. and Wang, Y. (2020), “A modified quality loss model of service life prediction for products via wear regularity”, Reliability Engineering & System Safety, Vol. 204, p. 107187, http://doi.org/10.1016/jj.ress.2020.107187.CrossRefGoogle Scholar
Marler, R.T. and Arora, J.S. (2010), “The weighted sum method for multi-objective optimization: new insights”, Structural and Multidisciplinary Optimization, Vol. 41 No. 6, pp. 853–862, http://doi.org/10.1007/s00158-009-0460-7.CrossRefGoogle Scholar
Walter, M., Spruegel, S. and Wartzack, S. (2012), “Tolerance analysis of mechanism taking into account the interactions between deviations using meta-models”, in: Proceedings ofNordDesign 2012, the 9th NordDesign conference, DS / Design Society.Google Scholar
Walter, M., Spruegel, T. and Wartzack, S. (2015), “Least cost tolerance allocation for systems with time-variant deviations”, Procedia CIRP, Vol. 27, pp. 1–9, http://doi.org/10.1016/jj.procir.2015.04.035.CrossRefGoogle Scholar
Walter, M. and Wartzack, S. (2013), “Statistical tolerance-cost-optimization of systems in motion taking into account different kinds of deviations”, in: Abramovici, M. and Stark, R. (Editors), Smart Product Engineering, Lecture Notes in Production Engineering, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 705–714, http://doi.org/10.1007/978-3-642-30817-8{_}69.CrossRefGoogle Scholar
Zeng, W. and Rao, Y. (2019), “Modeling of assembly deviation with considering the actual working conditions”, International Journal of Precision Engineering and Manufacturing, Vol. 20 No. 5, pp. 791–803, http://doi.org/10.1007/s12541-019-00014-2.CrossRefGoogle Scholar
Zeng, W., Rao, Y., Long, C. and Wang, P. (2017), “Prediction of service life for assembly with time-variant deviation”, IOP Conference Series: Materials Science and Engineering, Vol. 212, http://doi.org/10.1088/1757-899X/212/1/012021.CrossRefGoogle Scholar
Zeng, W., Yi, J., Lin, R. and Lu, W. (2022), “Statistical tolerance-cost-service life optimization of blade bearing of controllable pitch propeller considering the marine environment conditions through meta-heuristic algorithm”, Journal of Computational Design and Engineering, Vol. 9 No. 2, pp. 689–705, http://doi.org/10.1093/jcde/qwac023.CrossRefGoogle Scholar
Zhao, Y.M., Liu, D.S. and Wen, Z.J. (2016), “Optimal tolerance design of product based on service quality loss”, The International Journal of Advanced Manufacturing Technology, Vol. 82 No. 9-12, pp. 1715–1724, http://doi.org/10.1007/s00170-015-7480-9.CrossRefGoogle Scholar
Zhu, L., Zhang, Y., Zhang, R. and Zhang, P. (2018), “Time-dependent reliability of spur gear system based on gradually wear process”, Eksploatacja i Niezawodnosc - Maintenance and Reliability, Vol. 20 No. 2, pp. 207–218, http://doi.org/10.17531/ein.2018.2.05.CrossRefGoogle Scholar