Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Recommendations for an Open Science approach to welding process research data
    ( 2021)
    Fabry, C.
    ;
    Pittner, A.
    ;
    Hirthammer, V.
    ;
    Rethmeier, M.
    The increasing adoption of Open Science principles has been a prevalent topic in the welding science community over the last years. Providing access to welding knowledge in the form of complex and complete datasets in addition to peer-reviewed publications can be identified as an important step to promote knowledge exchange and cooperation. There exist previous efforts on building data models specifically for fusion welding applications; however, a common agreed upon implementation that is used by the community is still lacking. One proven approach in other domains has been the use of an openly accessible and agreed upon file and data format used for archiving and sharing domain knowledge in the form of experimental data. Going into a similar direction, the welding community faces particular practical, technical, and also ideological challenges that are discussed in this paper. Collaboratively building upon previous work with modern tools and platforms, the authors motivate, propose, and outline the use of a common file format specifically tailored to the needs of the welding research community as a complement to other already established Open Science practices. Successfully establishing a culture of openly accessible research data has the potential to significantly stimulate progress in welding research.
  • Publication
    Design of neural network arc sensor for gap width detection in automated narrow gap GMAW
    ( 2018)
    Fabry, C.
    ;
    Pittner, A.
    ;
    Rethmeier, M.
    An approach to develop an arc sensor for gap width estimation during automated NG-GMAW with a weaving electrode motion is introduced by combining arc sensor readings with optical measurements of the groove shape to allow precise analyses of the process. The two test specimen welded for this study were designed to feature a variable groove geometry in order to maximize efficiency of the conducted experimental efforts, resulting in 1696 individual weaving cycle records with associated arc sensor measurements, process parameters and groove shape information. Gap width was varied from 18 mm to 25 mm and wire feed rates in the range of 9 m/min to 13 m/min were used in the course of this study. Artificial neural networks were applied as a modelling tool to derive an arc sensor for estimation of gap width suitable for online process control that can adapt to changes in process parameters as well as changes in the weaving motion of the electrode. Wire feed rate, weaving current, sidewall dwell currents and angles were defined as inputs to calculate the gap width. The evaluation of the proposed arc sensor model shows very good estimation capabilities for parameters sufficiently covered during the experiments.
  • Publication
    Influence of grain size on mechanical properties of aluminium GTA weld metal
    ( 2013)
    Schempp, P.
    ;
    Cross, C.E.
    ;
    Häcker, R.
    ;
    Pittner, A.
    ;
    Rethmeier, M.
    Grain refinement is an important possibility to enhance the mechanical properties such as strength, ductility and toughness of aluminium weld metal. In this study, grain refinement was achieved through the addition of commercial grain refiner Al Ti5B1 to gas tungsten arc weld metal of the aluminium alloys 1050A (Al 99.5) and 5083 (Al Mg4.5Mn0.7). The grain refiner additions led to a significant reduction of the weld metal mean grain size (Alloy 1050A, 86 %; Alloy 5083, 44 %) with a change in grain shape from columnar to equiaxed. Tensile tests showed for Alloy 5083 that the weld metal's ductility can be increased through grain refinement. No improvement in weld metal strength (i.e. yield strength and ultimate tensile strength) was observed. Furthermore, tear tests with notched specimens revealed that the resistance against initiation and propagation of cracks in the weld metal can be enhanced through grain refinement. The toughness was observed to increase clearly by grain refinement in weld metal of commercial pure Al (Alloy 1050A). In Alloy 5083 weld metal, the toughness was not improved through grain refinement, likely because of a semi-continuous network of brittle intermetallic phases that facilitate crack propagation.
  • Publication
    Fast temperature field generation for welding simulation and reduction of experimental effort
    ( 2011)
    Pittner, A.
    ;
    Weiss, D.
    ;
    Schwenk, C.
    ;
    Rethmeier, M.
    The quality of welding processes is governed by the occurring induced distortions yielding an increase in production costs due to necessary reworking. Especially for more complex specimens, it is difficult to evaluate the optimal configuration of welding sequences in order to minimize the distortion. Even experienced welding operators can solve this task only by trial and error which is time and cost consuming. In modern engineering the application of welding simulation is already known to be able to analyse the heat effects of welding virtually. However, the welding process is governed by complex physical interactions. Thus, recent weld thermal models are based on many simplifications. The state of the art is to apply numerical methods in order to solve the transient heat conduction equat ion. Therefore, it is not possible to use the real process parameters as input for the mathematical model. The model parameters which allow calculating a temperature field that is in best agreement with the experiments cannot be defined directly but inversely by multiple simulations runs. In case of numerical simulation software based on finite discretization schemes this approach is very time consuming and requires expert users. The weld thermal model contains an initial weakness which has to be adapted by finding an optimal set of model parameters. This process of calibration is often done against few experiments. The range of model validity is limited. An extension can be obtained by performing a calibration against multiple experiments. The focus of the paper is to show a combined mode lling technique which provides an efficient solution of the inverse heat conduction problem mentioned above. On the one hand the inverse problem is solved by application of fast weld thermal models which are closed form solutions of the heat conduction equation. In addition, a global optimization algorithm allows an automated calibration of the weld thermal model. This technique is able to provide a temperature field automatically that fits the experimental one with high accuracy within minutes on ordinary office computers. This fast paradigm permits confirming the application of welding simulation in an industrial environment as automotive industry. On the other hand, the initial model weakness is compensated by calibrating the model against multiple experiments. The unknown relationship between model and process parameters is approximated by a neural network. The validity of the model is increased successively and enables to decrease experimental effort. For a test case, it is shown that this approach yields accurate temperature fields within very short amount of time for unknown process parameters as input data to the model contributing to the requirement to construct a substitute system of the real welding process.