Measurement Assisted Assembly for High Accuracy Aerospace Manufacturing

Abstract Measurement Assisted Assembly is a key concept for the modernisation of aerospace assembly processes, i.e. improving their efficiency while reducing the manufacturing costs. This concept suggests a paradigm shift in the assembly of high-complexity products as it encompasses the development and the use of robotics solutions smartly integrated with innovative measurement technologies. Expected outcomes are, among others, a better positioning accuracy of the components and a significant reduction of the rectification and rework requirements that are usually common with traditional assembly processes, especially but not limited to aerospace manufacturing. To achieve these objectives, a high precision metrology system that automatically inspects and corrects the pose of the robotic manipulators during the assembly operations is of great importance. In this paper, a high-accuracy real-life application of the concept of Measurement Assisted Assembly is presented as a part of the Future Automated Aircraft Assembly Demonstrator developed by the University of Nottingham. Experimentations have shown that, using the production environment described hereafter, a positioning accuracy better than ±0.1 mm can be achieved for large airframe components.

[1]  Benoît Furet,et al.  A methodology for joint stiffness identification of serial robots , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  W. Kabsch A discussion of the solution for the best rotation to relate two sets of vectors , 1978 .

[3]  Jody Muelaner,et al.  Achieving Low Cost and High Quality Aero Structure Assembly through Integrated Digital Metrology Systems , 2013 .

[4]  Brian Logan,et al.  Evolvable Assembly Systems: A Distributed Architecture for Intelligent Manufacturing , 2015 .

[5]  Paul G. Maropoulos,et al.  Review of the application of flexible, measurement-assisted assembly technology in aircraft manufacturing , 2014 .

[6]  Eric Courteille,et al.  A Systematic Procedure for the Elastodynamic Modeling and Identification of Robot Manipulators , 2010, IEEE Transactions on Robotics.

[7]  Jody Muelaner,et al.  A new paradigm in large-scale assembly—research priorities in measurement assisted assembly , 2014 .

[8]  Svetan Ratchev,et al.  A Transformable Manufacturing Concept for Low-Volume Aerospace Assembly , 2017 .

[9]  Euripides G. M. Petrakis,et al.  A survey on industrial vision systems, applications, tools , 2003, Image Vis. Comput..

[10]  Rainer Drath,et al.  Industrie 4.0: Hit or Hype? [Industry Forum] , 2014, IEEE Industrial Electronics Magazine.

[11]  Daniel F. García,et al.  Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review , 2016, Sensors.

[12]  Shaheen Ahmad,et al.  Analysis of robot drive train errors, their static effects, and their compensations , 1988, IEEE J. Robotics Autom..

[13]  W. Kabsch A solution for the best rotation to relate two sets of vectors , 1976 .

[14]  Jun Ni,et al.  Nongeometric error identification and compensation for robotic system by inverse calibration , 2000 .