OptNeTol: Integrated, optimization-based parameter and tolerance design
Final Report Abstract
Unavoidable geometrical variations are limited explicitly by geometrical and dimensional tolerances to ensure that technical systems fulfill their function despite manufacturing inaccuracies. However, in doing so, the requirements for the subsequent manufacturing and, thus, the costs are implicitly set. The method of tolerance-cost optimization manages the balancing act between low costs and high product quality by allocating all tolerance values in a cost-optimized and automated manner. However, the existing solution approaches cannot answer the practice-relevant questions comprehensively. Limitations in accuracy, completeness, efficiency, and the lack of integration into the modern product development process make it difficult to solve industrial problems, whereby hidden cost potentials mostly remain unused. Aiming to overcome these obstacles, this two-and-a-half-year project used the findings from the previous project “Tolerance optimization of statically under- and over-constrained assemblies” and enhanced the method of sampling-based tolerance-cost optimization. On the one hand, the novel methods foster its use with only approximate cost information available and the identification of robust nominal dimensions and thus their application in early product design phases. On the other hand, the integration of form, orientation, and location tolerances, as well as machine selection and allocation strategies with machine-specific manufacturing distributions, enables its application to complex, non-linear assemblies while simultaneously considering manufacturing boundary conditions at an early stage. Harmonizing the optimization routines with variance reduction sampling and non-conformance rate estimation techniques ensures the optimization results’ reliability. Due to the newly developed efficiency enhancement methods based on adaptive sample sizes and surrogate models, computation times can be significantly reduced without compromising the quality of the results. The final evaluation of the overall framework developed and transferred into a software prototype shows that the enhancements contribute significantly to its universal applicability. Product developers without in-depth knowledge of statistics and optimization can now determine nominal dimensions and tolerances robustly and cost optimally.
Link to the final report
https://doi.org/10.25593/open-fau-1719
Publications
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Toward cost-efficient tolerancing of 3D-printed parts: a novel methodology for the development of tolerance-cost models for fused layer modeling. The International Journal of Advanced Manufacturing Technology, 119(3-4), 2461-2478.
Roth, Martin; Schaechtl, Paul; Giesert, Andreas; Schleich, Benjamin & Wartzack, Sandro
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Concurrent Machine and Batch Size Selection in Sampling-based Tolerance-Cost Optimization. Procedia CIRP, 109(2022), 13-18.
Roth, Martin; Schleich, Benjamin & Wartzack, Sandro
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Coupling Sampling-Based Tolerance-Cost Optimization and Selective Assembly – An Integrated Approach for Optimal Tolerance Allocation. Volume 2A: Advanced Manufacturing. American Society of Mechanical Engineers.
Roth, Martin; Seitz, Markus Johannes; Schleich, Benjamin & Wartzack, Sandro
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Handling Sampling-induced Uncertainties in Tolerance-Cost Optimization. Procedia CIRP, 114(2022), 209-214.
Roth, Martin; Schleich, Benjamin & Wartzack, Sandro
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„Boosting the Accuracy of Sampling-based Tolerance-Cost Optimization”. Vortrag auf dem Meeting der European Research Group of Tolerancing (EGRT) 2023, 13.06-14.06.2023, Bordeaux, Frankreich
M. Roth, S. Goetz & S. Wartzack
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Accelerating sampling-based tolerance–cost optimization by adaptive surrogate models. Engineering Optimization, 57(2), 404-426.
Roth, Martin; Freitag, Stephan; Franz, Michael; Goetz, Stefan & Wartzack, Sandro
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Sampling-Based Tolerance-Cost Optimization: Automating Least-Cost Tolerance Allocation Through Joint Metaheuristic Optimization and Sampling-Based Tolerance Analysis. Research in Tolerancing, 101-127. Springer Nature Switzerland.
Roth, Martin & Wartzack, Sandro
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„Sampling-based Tolerance-Cost Optimization. The Key to Optimal Tolerance Allocation”, Dissertation, Friedrich-Alexander-Universität Erlangen-Nürnberg, 2024.
M. Roth
