Publications and presentations

Friction stir welding (FSW) has developed into a reliable and increasing used industrial joining technology. Various tool configurations can be used for FSW, each of which has advantages and challenges. State-of-the-art FSW employs various tool configurations, including the conventional, the stationary shoulder, and the dual-rotational configuration which is characterized by separate control of shoulder and probe. In this study, an innovative method to combine various tool configurations was developed by a novel FSW spindle stack construction. With an additional servomotor, existing FSW systems can be extended by separate control of shoulder and probe so that varying rotational speeds and rotational directions can be set. This allows enhanced possibilities (a) to adjust frictional heat generation and (b) to apply several tool configurations. The main advantages of this enhanced type of FSW are demonstrated in three ways: increased weld penetration depth, reduction of undesirable machine vibrations, and the combination of varying tool configurations such as stationary shoulder and conventional FSW. The investigations were carried out with 2-mm EN AA 5754 H22 sheets and performed on a robotized FSW setup.

This research presents a hybrid approach to generate sample data for future machine learning applications for the prediction of mechanical properties in directed energy deposition-arc (DED-Arc) using the GMAW process. DED-Arc is an additive manufacturing process which offers a cost-effective way to generate 3D metal parts, due to its high deposition rate of up to 8 kg/h. The mechanical properties additively manufactured wall structures made of the filler material G4Si1 (ER70 S-6) are shown in dependency of the t8/5 cooling time. The numerical simulation is used to link the process parameters and geometrical features to a specific t8/5 cooling time. With an input of average welding power, welding speed and geometrical features such as wall thickness, layer height and heat source size a specific temperature field can be calculated for each iteration in the simulated welding process. This novel approach allows to generate large, artificial data sets as training data for machine learning methods by combining experimental results to generate a regression equation based on the experimentally measured t8/5 cooling time. Therefore, using the regression equations in combination with numerically calculated t8/5 cooling times an accurate prediction of the mechanical properties was possible in this research with an error of only 2.6%. Thus, a small set of experimentally generated data set allows to achieve regression equations which enable a precise prediction of mechanical properties. Moreover, the validated numerical welding simulation model was suitable to achieve an accurate calculation of the t8/5 cooling time, with an error of only 0.3%.

In recent years, the interest of the scientific community in perforated plates for ballistic protection has increased. Perforated plates do not represent protection by themselves, rather, they are used in the armour systems of armoured vehicles, in conjunction with base armour, since they are intended to induce bend stresses, where a penetrating core fracture occurs. The fragments are subsequently stopped by base armoured vehicle armour. Although for the first time used several decades ago, perforated plates are found to be attractive even today. The main reason is the combination of very convenient properties. Besides high mass effectiveness, they possess a high multi-impact resistance, since their perforations arrest cracks. Therefore, a relatively wide array of materials is suitable for perforated plate fabrication, ranging from alloy steel to some types of cast iron. Being made of metallic materials, raw material costs are relatively low compared to ceramics or composite materials, making them very attractive for present and future armoured vehicles. Finally, armour system consisting of a perforated plate and base plate at some distance, reduce the effectiveness of both shaped charge jets and act as blast mitigators.

Industrie 4.0" ist für kleine und mittelständische Unternehmen (KMU), die sich mit dem Fügen, Trennen und Beschichten auskennen, künftig von großer Bedeutung. Dabei geht es aber weniger darum, konkrete Produktions-, Fertigungs- oder Schweißprozesse zu beschreiben, sondern kritisch zu prüfen, wo in kleinen und mittelständischen Unternehmen Lücken hinsichtich Industrie 4.0 bestehen und wie sich diese schließen lassen. Denn nur so können Unternehmen langfristig den bestehenden, digitalen Vorsprung für sich nutzen. Aus diesem Grund beschäftigt sich die Arbeitsgruppe "Industrie 4.0" im DVS aktuell mit diesem Thema. Sie stößt die Diskussion über die Digitalisierung in der Schweißtechnik an und initiiert unter dem Titel "Vom Fortschritt profitieren: Industrie 4.0 in der Schweißtechnik" eine Serie von Fachbeiträgen, die - mit der vorliegenden Ausgabe beginnend - in dieser Zeitschrift veröffentlicht werden.