Konfiguration verteilter Large-Scale Metrology Systeme in rekonfigurierbaren Montageumgebungen
- Configuration of distributed large-scale metrology systems in reconfigurable assembly environments
Nicksch, Christoph; Schmitt, Robert H. (Thesis advisor); Corves, Burkhard (Thesis advisor)
1. Auflage. - Aachen : Apprimus Verlag (2023)
Book, Dissertation / PhD Thesis
In: Ergebnisse aus der Produktionstechnik 11/2023
Page(s)/Article-Nr.: 1 Online-Ressource : Illustrationen, Diagramme
Dissertation, RWTH Aachen University, 2023
Abstract
The industrial assembly of large-scale products represents a challenge in terms of production technology. In addition to the complex handling of large and bulky components, assembly tolerances in the submillimeter range must be met for high quality requirements. To enable flexible and high-precision assembly of large components, the line-less mobile assembly systems (LMAS) approach is designed. LMAS is based on mobile assembly resources that can perform efficient reconfiguration of the assembly environment to adapt to new processes in an automated and flexible way. High-precision position data is an important prerequisite for the position control of the assembly resources. Distributed metrology systems of the largescale metrology (LSM), which enable optical measurements over long distances with low measurement uncertainties, are suitable for collecting the position data. The measurement uncertainty of these systems depends on the configuration of the transmitters and receivers and varies over the assembly process. To ensure the process capability of such measurement processes, the measurement uncertainty must be known during the assembly process. In this work, a methodology is developed to enable measurement uncertainty-optimized configuration of distributed LSM-systems for LMAS and inherent a priori determination of the process capability of measurement processes. The methodology is composed of three submodels: a measurement uncertainty model for configuration-dependent determination of the measurement uncertainty, an optimization model for minimizing the measurement uncertainty, and a simulation model for line-of-sight simulation of distributed LSM-systems in an LMAS process. For this purpose, a measurement uncertainty model is developed for the class of multiangulation-based LSM-systems, since this measurement system class allows simultaneous measurements of several assembly resources in LMAS. Depending on the configuration of the transmitters, the measurement uncertainty of a position measurement can be determined for a given receiver position. For the design of the optimization model, a particle swarm algorithm is used. By modifying the standard algorithm, distributed LSM-systems can be used and considered with respect to their working ranges and specific measurement uncertainty models. The simulation model is coupled to the optimization model and collects data on line-of-sight and geometric relationships between transmitters and receivers. These data are required to determine the measurement uncertainty, which serves as the target value of the optimization model. Verification on an aircraft final assembly use case shows that lasertrackers and an iGPS can be configured as two examples of distributed LSM-systems and capable processes can be realized within the simulation. The developed methodology for configuring distributed LSM-systems is finally validated in an experiment using the iGPS. Here, an LMAS process is mimicked and a laser tracker is used as a reference metrology system to investigate the measurement uncertainty. The results of the experiments show that the optimization of the configuration reduces the measurement uncertainty and thus also the minimum verifiable assembly tolerances by 25%, which underlines the added value of the developed methodology for industrial practice.
Institutions
- Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University [417200]
- Chair of Production Metrology and Quality Management [417510]
Identifier
- ISBN: 978-3-98555-152-1
- DOI: 10.18154/RWTH-2023-02595
- RWTH PUBLICATIONS: RWTH-2023-02595