RESUMEN
Once on Mars, maintenance and repair will be crucial for humans as supply chains including Earth and Mars will be very complex. Consequently, the raw material available on Mars must be processed and used. Factors such as the energy available for material production play just as important a role as the quality of the material that can be produced and the quality of its surface. To develop and technically implement a process chain that meets the challenge of producing spare parts from oxygen-reduced Mars regolith, this paper addresses the issue of low-energy handling. Expected statistically distributed high roughnesses of sintered regolith analogs are approximated in this work by parameter variation in the PBF-LB/M process. For low-energy handling, a dry-adhesive microstructure is used. Investigations are carried out to determine the extent to which the rough surface resulting from the manufacturing process can be smoothed by deep-rolling in such a way that the microstructure adheres and enables samples to be transported. For the investigated AlSi10Mg samples (12 mm × 12 mm × 10 mm), the surface roughness varies in a wide range from Sa 7.7 µm to Sa 64 µm after the additive manufacturing process, and pull-off stresses of up to 6.99 N/cm2 could be realized after deep-rolling. This represents an increase in pull-off stresses by a factor of 392.94 compared to the pull-off stresses before deep-rolling, enabling the handling of even larger specimens. It is noteworthy that specimens with roughness values that were previously difficult to handle can be treated post-deep-rolling, indicating a potential influence of additional variables that describe roughness or ripples and are associated with the adhesion effect of the microstructure of the dry adhesive.
RESUMEN
High-throughput screenings are established evaluation methods in the development of functional materials and pharmaceutical active ingredients. The transfer of this approach to the development of structural materials requires extensive adaptations. In addition to the investigation of new test procedures for the determination of material properties and the treatment of metallic materials, the design of experiments is a research focus. Based on given descriptor target values, the statistical design of experiments determines investigations and treatments for the investigation of these materials. In this context, process parameters also have to be determined, as these have a major influence on the later material properties, especially during the treatment of samples. In this article, a method is presented which determines the process parameters iteratively. The validation of the calculated process parameters takes place based on differential scanning calorimetry used as the furnace for the heat treatment of small batches and particle-oriented peening as the characterization method.
RESUMEN
High-throughput screenings are widely accepted for pharmaceutical developments for new substances and the development of new drugs with required characteristics by evolutionary studies. Current research projects transfer this principle of high-throughput testing to the development of metallic materials. In addition to new generating and testing methods, these types of high-throughput systems need a logistical control and handling method to reduce throughput time to get test results faster. Instead of the direct material flow found in classical high-throughput screenings, these systems have a very complex structure of material flow. The result is a highly dynamic system that includes short-term changes such as rerun stations, partial tests, and temporarily paced sequences between working systems. This paper presents a framework that divides the actions for system acceleration into three main sections. First, methods for special applications in high-throughput systems are designed or adapted to speed up the generation, treatment, and testing processes. Second, methods are needed to process trial plans and to control test orders, which can efficiently reduce waiting times. The third part of the framework describes procedures for handling samples. This reduces non-productive times and reduces order processing in individual lots.