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In Line-less Mobile Assembly Systems, the mobilization of assembly resources and products enables rapid physical system reconfigurations to increase flexibility and adaptability. The clean floor approach discards fixed anchor points, so that assembly resources such as mobile robots and automated guided vehicles transporting products can adapt to new products and form new processes. Associated challenges are accurate spatial referencing between mobile resources to meet assembly tolerance requirements. There is a need for more accurate positioning data to locate and navigate mobile assembly resources. An indoor-GPS, as a distributed large-scale metrology system, is able to cover a wide shop floor area and to obtain positioning data with uncertainties in the submillimeter range. The measurement uncertainty of such a system depends on the spatial distribution of the transmitters and the receiver positions. To be able to validate positioning tolerance requirements of an assembly process, measurement uncertainties must be determined. Virtual measurements simulate measurement processes and model dependencies between the environment and the metrology system. This work presents a novel approach for a virtual indoor-GPS to determine measurement uncertainties during a process and to evaluate the measurement process capability. Experiments show the validity of the virtual indoor-GPS which can be used as a planning tool for metrology system setups within Line-less Mobile Assembly Systems.

Im automobilen Prototypenbau werden starre Vorrichtungen genutzt, um Karosseriebauteile für Fügeprozesse zueinander auszurichten. Geringe Stückzahlen der Vorserie führen zu kurzen Nutzungsphasen der aufwendig aufgebauten und eingemessenen Vorrichtungen. Im Beitrag wird ein Ansatz zur vorrichtungslosen Montage durch den Einsatz von Industrierobotik und laserbasierter Messtechnik vorgestellt. Die Ergebnisse zeigen, dass sich für einzelne Baugruppen Möglichkeiten für das vorrichtungslose Fügen in der industriellen Praxis ergeben.   Rigid fixtures are used in automotive prototype construction to align body parts for joining processes. Small quantities of the prototype series lead to short usage of the laboriously assembled and calibrated fixtures. In the following, an approach of fixtureless assembly using industrial robots and laser metrology is presented. The results show that some fixtures and jigs can be dispensed with for individual components in industrial practice.

In Line-less Mobile Assembly Systems (LMAS) the mobilization of assembly resources and products enables rapid physical system reconfigurations to increase flexibility and adaptability. The clean-floor approach discards fixed anchor points, so that assembly resources such as mobile robots and automated guided vehicles transporting products can adapt to new product requirements and form new assembly processes without specific layout restrictions. An associated challenge is spatial referencing between mobile resources and product tolerances. Due to the missing fixed points, there is a need for more positioning data to locate and navigate assembly resources. Distributed large-scale metrology systems offer the capability to cover a wide shop floor area and obtain positioning data from several resources simultaneously with uncertainties in the submillimeter range. The positioning of transmitter units of these systems becomes a demanding task taking visibility during dynamic processes and configuration-dependent measurement uncertainty into account. This paper presents a novel approach to optimize the position configuration of distributed large-scale metrology systems by minimizing the measurement uncertainty for dynamic assembly processes. For this purpose, a particle-swarm-optimization algorithm has been implemented. The results show that the algorithm is capable of determining suitable transmitter positions by finding global optima in the assembly station search space verified by applying brute-force method in simulation.

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