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Process design

 

The main scientific and technological challenges are related to the need to develop and integrate deterministic/statistical models to predict the interaction of different sources of error (from robot, parts and fixtures) on the quality of the weld. This integration will permit to have a comprehensive model of all error sources. It will consider tolerance analysis as well as the feasibility to compensate different error sources affecting the system. On the other hand, it is strategic to design the fixture used to join the parts, which should maximize the quality of the weld by ensuring appropriate gap control between the joined parts. Gaps are affected by geometrical variation and are controlled by the location and closing sequence of the fixture clamps. So enabling the choice of a suitable fixturing strategy is a key factor to guarantee the successful of RLW process. The third issue is related to the lack of analytical and numerical models to accurately predict the weld quality; so RLW parameters (related to width & penetration depth, seam porosity, and so on) have to be determined experimentally, through DOE techniques, for different types of materials as well as a combination of materials. The parameters to be determined include laser incident angle, laser spot diameter, laser power, and welding speed. The information captured during the experiments will be used to optimize the parameters selection. The aim of this task is to specify a proper DOE and build the meta-models on the experimental data.

Task 3.1 Error Budget Map Generation
Task Leader: Warwick
Participants: SZTAKI, UP, Stadco

The first set of activities aims at analyzing the contribution that different source of error and variation have on weld quality (see Figure WP3-1, Part B). The main expected outcomes from Task 3.1 are:

•To have a comprehensive model of all error sources;
•To identify how the interaction of errors may affect the quality of the weld.

 

Task 3.2 Robust Fixture Design for RLW
Task Leader: Warwick
Participants: SZTAKI, UP, EPFL, UNIMOL, JCL, LR, Stadco, Comau, ES

This task will focus on the design of the fixture used to join the parts, which should maximize the quality of the weld by ensuring appropriate gap control between the joined parts. Due to parts' geometrical variation, the gap between them at the location of the weld can exceed the technical limit for RLW to ensure an appropriate joint. Gaps are controlled by the location and closing sequence of the fixture clamps; hence, location and closing sequence have to ensure that for any in-spec incoming parts variation the gap will be maintained inside the technical limit. Gap control can be a very challenging task especially for parts with complex geometries, e.g., door inner structures, as the clamps are closed, deformations of the parts can accumulate in critical areas creating gaps which exceed the limits resulting in a bad joint. Therefore, fixture design has to be done considering erroneous or not nominal/perfect parts with geometrical errors.

To view tools developed under WP3 please click here.

 

 

 

 

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RLW Navigator is a three year, €3.9M, project funded by the European Commission under the ICT-Factories of the Future programme.  The project has fourteen partners and began in January 2012.

The goal of the project is to develop an engineering platform for an emerging joining technology from the automotive industry, Remote Laser Welding (RLW), that will enable the exploitation of this technology and ultimately support other joining processes.

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