FG Automatisierungstechnik
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This paper presents a novel approach for automated smart factory based on the ideas of Internet of Things (IoT) and the usage of mobile technology of the german „Industry 4.0“ [6]. IoT enables the achievement of greater value and service by exchanging data between different devices and the manufacturer. The data collected from all devices will be exchanged via wireless networks. Mobile technology can be used to cover non value-added processes [3] i.e. transportation in the manufacturing. By combining transportation tasks and value adding production steps, waste of production time, cost and effort can be reduced. This paper presents the first step toward this approach [7]: the mobile robot moves alongside the moving object and executes the manufacturing tasks during its transportation. For the demonstration of the developed solution a mobile
platform and an optical measurement system was used. The synchronization between the mobile platform and the object will be experimentally tested. Consequently the results will demonstrate how the mobile robot is able to follow the moving object.
Synchronisation von mobilen Robotern zu einer kontinuierlichen Fließfertigung für Montageaufgaben
(2015)
A variant-flexible assembly cell for hydraulic valve sections using a sensitive lightweight robot
(2016)
Increasing Robotic Machining Accuracy Using Offline Compensation Based on Joint-Motion Simulation
(2014)
Offline Path Compensation to Improve Accuracy of Industrial Robots for Machining Applications
(2013)
The optimization processes in production planning often encounter problems due to unavailability of skilled workers in the concerned production departments since the decisions made in uncertain situations rely mainly on the knowledge possessed by the relevant planners. This paper further presents and elaborates the unified web-based knowledge based decision support system concept to automate and reuse implicit knowledge generated during interaction with the dedicated software tools as well as during interaction with real hardware setups in an industrial environment. The unified concept has been devised considering two pilot cases i.e. decision making on eco-efficient decentralized production schemes for manufacturing customized products and decision support for solving problems in ramp-up management process. This paper further discusses the development issues concerning web-based knowledge based decision support system to demonstrate the unified concept. The software modules from both pilot cases are validated considering two pilot cases.
Industrial robots offer a good basis for machining from a conceptual point of view. However they are rarely utilized for machining applications in industry due to their low stiffness and the bad achievable work piece quality. Available solutions using position control of the tool require costly additional hardware and measurement equipment; force controlled solutions depend on low level controller access that is not commonly available for generic cell setups. This paper proposes a three-step approach to compensate for process force induced accuracy errors: (1) selection of appropriate milling strategies and cutting parameters, (2) an offline compensation of the force induced deviations and (3) a respective online compensation method. Experimental validation of the results has been performed for the first two steps.
The manufacturing industry is distinguished by regionalization and individualization of products accompaniedby varying customer demands, faster time to market, short innovation cycles and product life cycles. Theintroduction of new materials, new processes as well as struggle to achieve economic and efficient use ofresources has raised complexities to achieve quick and optimal configuration in manufacturing systems. Toresolve the complexities, the reconfiguration at different levels in the manufacturing system is presented byusing three distinct examples. The first example refers to reconfigurable joining cell design for versatile joiningof automotive subassemblies. Second example refers to strategy for quick reconfiguration of robots for precisemachining applications. The third example elaborates fast calibration of monitoring system in joiningprocesses to enable fast reconfiguration of sensors in commissioning as well as in the maintenance.