Conference
On Neural Networks’ Ability to Approximate Geometrical Variation Propagation in Assembly
| العنوان: | On Neural Networks’ Ability to Approximate Geometrical Variation Propagation in Assembly |
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| المؤلفون: | Andolfatto, Loïc, Thiébaut, François, Douilly, Marc, Lartigue, Claire |
| المساهمون: | Laboratoire Universitaire de Recherche en Production Automatisée (LURPA), École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11), EADS Innovation Works Suresnes (EADS IW), EADS - European Aeronautic Defense and Space |
| المصدر: | 12th CIRP Conference on Computer Aided Tolerancing https://hal.science/hal-01094434 12th CIRP Conference on Computer Aided Tolerancing, Apr 2012, Huddersfield, United Kingdom. pp.224 - 232, ⟨10.1016/j.procir.2013.08.035⟩ |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2012 |
| مصطلحات موضوعية: | geometrical variation propagation, assembly, contact influence, neural network, [SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph] |
| جغرافية الموضوع: | Huddersfield, United Kingdom |
| الوصف: | International audience ; Tolerance analysis is an important step to validate assembly process planning scenario. Simulations are generally performed to evaluate the expected geometrical variations of the assembled product. When the simulation models take into account part compliance, assembly sequence and contact interaction, the resulting behaviour of the assembly are generally non-linear and simulations – mainly performed using finite element analysis – require high computing efforts. This paper investigates the ability to approximate the non-linear propagation of geometrical variations in assembly with artificial neural networks. The aim is to drastically reduce the computing efforts required for the simulation and therefore allow its use for the geometrical tolerances allocation optimisation. The influence of the neural network design parameters on the approximation quality is presented in a case study. The quality of the neural network approximation is also evaluated and discussed. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| Relation: | hal-01094434; https://hal.science/hal-01094434; https://hal.science/hal-01094434/document; https://hal.science/hal-01094434/file/2012_OnNeuralNetworkAbility.pdf |
| DOI: | 10.1016/j.procir.2013.08.035 |
| الاتاحة: | https://hal.science/hal-01094434 https://hal.science/hal-01094434/document https://hal.science/hal-01094434/file/2012_OnNeuralNetworkAbility.pdf https://doi.org/10.1016/j.procir.2013.08.035 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.7CBBA83B |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.procir.2013.08.035 |
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