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Carbon fiber reinforced polymer (CFRP) is widely used in high-tech industries because of its interesting characteristics and properties. This material presents good strength and stiffness, relatively low density, high damping ability, good dimensional stability, and good corrosion resistance. However, the machinability of composite materials is complex because of the matrix/fiber interface, being a challenging machining material. The CFRP milling process is still necessary to meet dimensional tolerances, the manufacture of difficult-to-mold features like pockets or complexes advance surfaces, finish the edges of laminated composites, or drill holes for the assembly of the components. Besides, the demand for low-cost, reconfigurable manufacturing systems of the industry demonstrates that the application of industrial robots (IRs) in the CFRP milling process becomes an alternative for providing automation and flexibility. Therefore, the objective of this work is to evaluate the performance of the low payload IR KUKA KR60 HA in a milling experiment of CFRP, which indicates its potential application as an alternative to milling process. Furthermore, the influence of the cutting tool geometry as well as the cutting parameters in the machining behavior with IRs is evaluated.

Counterfeiting, with a global trade volume of approximately 450 billion euro a year compromises business results of companies in all industrial segments. At worst, product plagiarism causes severe damages to the individual brand reputation due to product defects or liability issues. Therefore, product integration of inseparable and unique security features is essential for a preserving market share in all manufacturing branches. This paper presents a novel approach regarding a replication technology for the manufacturing of holographic security features. Using a microstructured aluminium substrate with holographic properties as a base material, a forming die is manufactured by a combination of physical vapour deposition (PVD) and galvanic coating processes. Furthermore, a process adapted hardness progression between individual layers was created. By the use of this die, the forming of a holographic microstructure into high strength aluminium alloy (3.3547) and spring steel (1.1248) could be demonstrated within a preliminary study.

In the manufacturing process of ship propellers, large quantities of grinding chips are generated. These grinding chips result from the finishing of the blade surfaces after the primary casting process of the propeller. The aim of this study was to investigate and compare different preparation processes used to produce chip powders with sufficient powder quality for the additive manufacturing process of directed energy deposition. The preparation of the samples was performed through different sieving, milling and re-melting processes. For the characterization of the prepared samples, powder analysis according to relevant industry standards was carried out. It was found that the re-melting processes result in superior powder quality for additive manufacturing in terms of particle size, morphology, and flowability. For some characteristics, the powder exhibits even better properties than those of commercial powders. Furthermore, the powder properties of the milled samples demonstrate a promising potential for use in additive manufacturing.

Decades of catalysis research have created vast amounts of experimental data. Within these data, new insights into property-performance correlations are hidden. However, the incomplete nature and undefined structure of the data has so far prevented comprehensive knowledge extraction. We propose a meta-analysis method that identifies correlations between a catalyst's physico-chemical properties and its performance in a particular reaction. The method unites literature data with textbook knowledge and statistical tools. Starting from a researcher's chemical intuition, a hypothesis is formulated and tested against the data for statistical significance. Iterative hypothesis refinement yields simple, robust and interpretable chemical models. The derived insights can guide new fundamental research and the discovery of improved catalysts. We demonstrate and validate the method for the oxidative coupling of methane (OCM). The final model indicates that only well-performing catalysts provide under reaction conditions two independent functionalities, i.e. a thermodynamically stable carbonate and a thermally stable oxide support.