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Handhabungsprozesse sind Teil nahezu jedes automatisierten Prozesses. Während das Handhabungsgerät verhältnismäßig einfach an neue Handhabungsaufgaben angepasst werden kann, erfolgt die Gestaltung der Greiferfinger als Schnittstelle zwischen Handhabungssystem und Objekt meist händisch und basierend auf Erfahrungswissen. Dieser Beitrag beschreibt die Entwicklung eines Greiferfingerbaukastens, der für eine automatisierte Konfiguration anwendungsspezifischer Greiferfinger genutzt werden kann. Handling processes are part of almost every automated process. While the handling device is relatively easy to adapt to new handling tasks, the design of the gripper fingers as the interface between handling system and object is usually done manually, based on empirical knowledge. This paper describes the development of a gripper finger construction kit to automate the configuration of application-specific gripper fingers.

Das vorgestellte Konzept entstand im Rahmen des Verbundvorhabens 01225201/1 SyProLei ��� Systemischer Produktentstehungsprozess zur gezielten Hebung von Leichtbaupotenzialen, gef��rdert durch das Bundesministerium f��r Wirtschaft und Energie aufgrund eines Beschlusses des Deutschen Bundestages im Technologietransfer-Programm Leichtbau (TTP LB). Projekttr��ger ist das Forschungszentrum J��lich GmbH. Das Konsortium besteht aus den Unternehmen ConmatiX Engineering Solutions GmbH, :em engineering methods AG, Emm! solutions GmbH, Siemens Industry Software GmbH, Liebherr Verzahntechnik GmbH, Otto Bock SE & Co. KGaA, Qeridoo GmbH sowie der Universit��t des Saarlandes und dem Karlsruher Institut f��r Technologie.

Die Vernetzung von Maschinen und Anlagen im Produktionsumfeld ist ein entscheidender Schlüssel zur Steigerung der Effizienz. Allerdings wird die Vernetzung durch verschiedene Kommunikationsprotokolle gehemmt und erfordert oftmals ein hohes Maß an Erfahrung und Wissen im Umgang mit den jeweiligen Protokollen.

Einwegverpackungen aus Kunststoffen sorgen für eine große Umweltbelastung und tragen bei unsachgemäßer Entsorgung zur Umweltverschmutzung bei. Eine mögliche Alternative sind biologisch abbaubare Produkte, welche sich immer mehr auf dem Markt etablieren. Biologisches Faserverbundmaterial ist eines der neuartigen Systeme.

Additive Verfahren besitzen das Potenzial den durch die Globalisierung und Digitalisierung getriebenen Trend hin zur Individualisierung und kürzeren Produktlebenszyklen wirtschaftlich zu adressieren. Insbesondere im Bereich der Mobilität ergeben sich hierbei aufgrund der hohen Volatilität besondere Herausforderungen. Um diese zu bewältigen, wird hier ein hochflexibles Anlagenkonzept zur additiv-subtraktiven Fertigung hochfunktionaler Kunststoffbauteile mit Inline-Prozessregelung vorgestellt. Additive processes have the potential to address the trend towards individualization and shorter product life cycles driven by globalization and digitization. Particularly in the area of mobility, special challenges arise due to the high volatility. To overcome these, a highly flexible system concept for the additive-subtractive production of highly functional plastic components with inline process control is presented here.

Additive manufacturing of polymers offers great potential for the production of complex structures. In particular, Fused Filament Fabrication (FFF) processes can be used to create functionally integrated components, in addition to easy handling, tool-free production and large material options. By combining a FFF system with a robot, inserts of different types can be integrated automatically during the printing process [1]. The low dimensional accuracy of FFF induces great difficulties during the insertion operation. Furthermore, with FFF, a planar layer structure leads to a stair-step effect when overprinting inserts with curved outer contours and reduces the adhesion to the insert. Further, the adhesion of FFF-filaments to the insert depends on the surface treatment of the insert [1]. A FFF system was combined with a robot [2] and has now been expanded to include a subtractive finishing unit and an inline process control based on a machine vision system, which enables the dimensional accuracy of the FFF components to be checked during the printing process. To be able to produce functionally integrated components, a flexible control architecture is being developed that enables the execution of additive and subtractive process steps. Optimal integration of inserts with complex geometries is facilitated by using non-planar layers in the FFF path planning. For this purpose, the filament layers of the FFF components follow the tilted or curved contours of the inserts. The modified process is demonstrated by manufacturing an integrated stator for an electric motor. A system for an additive-subtractive process for the integration of functional inserts was developed. In addition, a concept for the implementation of an improved connection of the inserts through non-planar FFF layers was created. First steps for the integration of the various system-modules and optical analysis of the dimensional accuracy and the development of a printing strategy for non-planar overprinting of the inserts have been realized.

This work focuses on the development of a numerical mold filling simulation for the rotational molding process. In the rotational molding process, a dry fiber preform is placed in a mold and impregnated with a thermoset matrix under rotation. Additionally, metallic load introduction elements can be inserted into the mold and joined with co-curing or form-fit, resulting in hybrid drive shafts or tie rods. The numerical model can be used to simulate the impregnation of the preform. Based on the resin transfer molding process, an OpenFOAM solver is extended for the rotational molding process. Permeability, kinetic and curing models are selected and adapted to the materials used. A wireless measurement solution with a capacitive sensor is developed to validate the model. Comparisons between measurements and numerically calculated impregnation times to reach the capacitive sensor with the matrix show good quality of the developed model. The average deviation between calculated result and measured mean values in the experiment is 43.8% the maximum deviation is 65.8% . The model can therefore be used to predict the impregnation progress and the curing state.