MATEC Web Conf.
Volume 190, 20185th International Conference on New Forming Technology (ICNFT 2018)
|Number of page(s)||9|
|Section||Micro cold forming, Special session SFB 747|
|Published online||18 September 2018|
Application of Cause-Effect-Networks for the process planning in laser rod end melting
BIBA – Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, 28359 Bremen, Germany
2 BIAS – Bremer Institut für angewandte Strahltechnik GmbH, 28359 Bremen, Germany
3 University of Bremen, Center for industrial mathematics (ZeTeM), 28359 Bremen, Germany
Corresponding author: firstname.lastname@example.org
In micro manufacturing, a precise configuration of manufacturing processes constitutes an essential factor for success. The continuing miniaturization of work pieces results in ever decreasing tolerances, whereas machines and processes become more and more specialized. As a result, a precise determination of each process result is important to guarantee the final product quality. Unfortunately, so called size effects often prevent the direct transfer of knowledge from the area of macro manufacturing. To cope with these effects, finite element simulations provide a suitable tool to simulate forming processes and their results in advance and to perform parameter studies in order to analyze the process and effect interdependencies. Unfortunately, these simulations usually require a rather long computing time, so that only simulations for a small subset of the available parameter range can be performed in a reasonable planning interval. In this context, this article presents an application of the method “Micro – Process Planning and Analysis” (μ-ProPlAn) for the configuration of laser rod end melting, which is used to create preforms for further forming processes. This method uses cause-effect networks, to combine expert knowledge with methods from artificial intelligence to estimate the result of laser melting processes quickly. For this purpose, the cause-effect networks are trained using a finite element simulation of the laser process using different process parameters and varying rod diameters. Results show a high accuracy for the prediction of the finite element simulation results. This article focusses on the validation of these cause-effect networks in comparison to the real laser rod end melting process and demonstrates how these models can be used to predict the resulting volume, eccentricity and the largest diameter of the solidified preform for different process configurations.
Key words: Laser Micro Machining / Simulation / Predictive Model
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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