Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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Numerical and experimental assessment of liquid metal embrittlement in externally loaded spot welds

2024-01-30 , Prabitz, Konstantin , Antretter, Thomas , Rethmeier, Michael , El-Sari, Bassel , Schubert, Holger , Hilpert, Benjamin , Gruber, Martin , Sierlinger, Robert , Ecker, Werner

Zinc-based surface coatings are widely applied with high-strength steels in automotive industry. Some of these base materials show an increased brittle cracking risk during loading. It is necessary to examine electrogalvanized and uncoated samples of a high strength steel susceptible to liquid metal embrittlement during spot welding with applied external load. Therefore, a newly developed tensile test method with a simultaneously applied spot weld is conducted. A fully coupled 3D electrical, thermal, metallurgical and mechanical finite element model depicting the resistant spot welding process combined with the tensile test conducted is mandatory to correct geometric influences of the sample geometry and provides insights into the sample’s time dependent local loading. With increasing external loads, the morphology of the brittle cracks formed is affected more than the crack depth. The validated finite element model applies newly developed damage indicators to predict and explain the liquid metal embrittlement cracking onset and development as well as even ductile failure.

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A Practical Approach to Realize a Closed Loop Energy Demand Optimization of Milling Machine Tools in Series Production

2023 , Can, Alperen , Schulz, Hendrik , El-Rahhal, Ali , Thiele, Gregor , Krüger, Jörg

Energy efficiency is becoming increasingly important for industry. Many approaches for energy efficiency improvements lead to the purchase of new hardware, which could neglect the sustainability. Therefore, optimizing the energy demand of existing machine tools (MT) is a promising approach. Nowadays energy demand optimization of MT in series production is mainly done manually by the operators, based on implicit knowledge gained by experience. This involves manual checks to ensure that production targets like product quality or cycle time are met. With data analytics it is possible to check these production targets autonomously, which allows optimizing production systems data driven. This paper presents the approach and evaluation of a closed loop energy demand optimization of auxiliary units for milling MT during series production. The approach includes, inter alia, a concept for machine connectivity using edge devices and a concept for validating production targets

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Automated continuous learn and improvement process of energy efficiency in manufacturing

2020 , Can, Alperen , Fisch, Jessica , Stephan, Philipp , Thiele, Gregor , Krüger, Jörg

Optimizing the energy efficiency of machine tools automatically is promising. There are several metrics to be considered when it comes to automated optimization approaches in serial production which are especially quality, technical availability, and cycle time. These are not supposed to be impaired whereas they are indicated as a central obstacle. The measurements and the machine data show the actions happening in the machine which also leads to the data-driven traceability of machine states. This article presents a method to formulate the necessary expert knowledge to optimize the energy efficiency of a machine tool and is basically done by a decision tree which leads to a set of rules which will be explained in this article. This set of rules coordinate an optimization algorithm, which technically manipulates selected variables under the given rules. The development and is a result of a research which was done at the serial production of camshafts at the MB plant in Berlin.

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