Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-12T21:50:06.506Z Has data issue: false hasContentIssue false
  • English
  • Français

Light automation for aircraft fuselage assembly

Published online by Cambridge University Press:  04 October 2019

L. G. Trabasso Open the ORCID record for L. G. Trabasso [Opens in a new window]  and
G. L. Mosqueira
L. G. Trabasso*
Affiliation:
Aeronautics Institute of Technology, São José dos Campos, Brazil
G. L. Mosqueira
Affiliation:
Eletroimpact of Brazil, Jacareí, Brazil
*
gonzaga@ita.br; luis.gonzaga@sc.senai.br
Get access Rights & Permissions [Opens in a new window]

Abstract

The ever-growing need to improve manufacturing processes has led recently to an increase in the number of automation solutions used to assemble aircraft structural elements. A process of interest to this industry is the alignment of fuselage sections, which is currently done either manually or by complex, expensive automated systems. The manual method introduces a significant production delay and most automated systems have limited flexibility. This article presents an integration solution implemented in an alternative low-cost, high-flexibility alignment robotic cell. The performance of an optical coordinate measuring machine (CMM) as feedback source for the adaptive control of a conventional industrial manipulator is assessed. Laser interferometry readings are used as reference. The contribution of the work lies in the execution of experiments based on the EN ISO 9283 standard (Manipulating industrial robots - performance criteria and related test methods) to determine the adequacy of the commercial off-the-shelf system to the tolerances and requirements of the fuselage alignment process at hand. The optimal configuration of the integrated system attained the nominal alignment position with an average accuracy of 0.16mm and $0.004^\circ$ , partially meeting the required tolerances, and the obtained values are nearly 16x better compared to a baseline, open-loop manipulator. These results serve as reference for the aerospace industry in the development of the next generation of tools and automated assembly processes.

Keywords

Aircraft assemblyfuselage alignmentadaptive robot controlEN ISO 9283
Type
Research Article
Information
The Aeronautical Journal , Volume 124 , Issue 1272 , February 2020 , pp. 216 - 236
Copyright
© Royal Aeronautical Society 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Sarh, B., Buttrick, J., Munk, C. and Bossi, R. Springer Handbook of Automation, Cap. 51 - Aircraft Manufacturing and Assembly, Springer, 2009, Berlin, Heidelberg, pp 893–910.CrossRefGoogle Scholar
Crothers, P.J., Nesbit, A., Steele, P., Lam, G., Gower, S., Van Duin, S. and Newberry, J. Light Automation Development, In: SAE Aerospace Automated Fastening Conference & Exposition, September 20–23, 2004, St. Louis, MAGoogle Scholar
Simonetti, M.L. and Trabasso, L.G. Automated Positioning and Alignment Method and System for Aircraft Structures using Robots, US Patent 8,634,950 B2, 2014 Google Scholar
Negroni, D.Y. and Trabasso, L.G. Process for Joining Aircraft Structural Components. US Patent US 9,102,019 B2, 2015.Google Scholar
Vieira, T.G. Delmia Simulation of the ASAA process. ASAA Lab. Internal Report, 2012.Google Scholar
Smith, S.O., Zieve, P.B. and Gurievsky, M. Join Cell for the G150 Aircraft. SAE Technical Paper, v. 2006-01-3123, 2006.Google Scholar
Barnfather, J.D., Goodfellow, M.J. and Abram, T. Achievable tolerances in robotic feature machining operations using a low-cost hexapod, INT J ADV MANUF TECHNOL, 2018, 95, pp 1421. doi: 10.1007/s00170-017-1266-1 CrossRefGoogle Scholar
Kihlman, H. Affordable Automation for Airframe Assembly - Development of Key Enabling Technologies, Doctorate thesis, Linköping University, Sweden.Google Scholar
Yagi, T. Recent trends in the Robotization of the Japanese automotive industry. IND ROBOT, 2002, 29, (6), pp 495–499.CrossRefGoogle Scholar
Leali, F., Vergnano, A., Pini, F., Pellicciari, M. and Berselli, G. A workcell calibration method for enhancing accuracy in robot machining of aerospace parts, INT J ADV MANUF TECHNOL, 2016, 85, p 47. doi: 10.1007/s00170-014-6025-y CrossRefGoogle Scholar
Costa, S. Dassault adaptice cells. IND ROBOT, 1996, 23, (1), pp. 34–40.CrossRefGoogle Scholar
ABB. Robot function package guarantees absolute accuracy, IND ROBOT, 2002, 29, (3), pp 291–300.Google Scholar
KUKA Roboter GmbH. KUKA.XRob APR 2.0 - Positionally Accurate Robot. [S.l.], Version: 2.1, 2007.Google Scholar
Freeman, P. A Novel Means of Software Compensation for Robots and Machine Tools. SAE Technical Paper, v. 2006-01-3167, 2006. doi: 10.4271/2006-01-3167.CrossRefGoogle Scholar
Devlieg, R. and Szallay, T. Improved Accuracy of Unguided Articulated Robots. SAE Technical Paper, v. 2009-01-3108, 2009. doi: 10.4271/2009-01-3108.CrossRefGoogle Scholar
Devlieg, R. Expanding the Use of Robotics in Airframe Assembly via Accurate Robot Technology. SAE Technical Paper, v. 2010-01-1846, 2010. doi: 10.4271/2010-01-1846.CrossRefGoogle Scholar
Devlieg, R. and Szallay, T. Applied Accurate Robotic Drilling for Aircraft Fuselage. SAE Technical Paper, v. 2010-01-1836, 2010. doi: 10.4271/2010-01-1836.CrossRefGoogle Scholar
Devlieg, R. High-Accuracy Robotic Drilling/Milling of 737 Inboard Flaps. SAE Technical Paper, v. 2011-01-2733, 2011. doi: 10.4271/2011-01-2733.CrossRefGoogle Scholar
Estler, W., Edmundson, K.L., Peggs, G.N. and Parker, D.H. Large-scale metrology - an update. CIRP ANN, 2002, 51, (2), pp. 587–609. doi: 10.1016/S0007-8506(07)61702-8.CrossRefGoogle Scholar
Villani, E., Suterio, R., Trabasso, L.G, Furtado, L.F.F., Alvarado, B.H.L. and Amorim, D.Y.K. Metrological analysis of an industrial robot for aircraft fuselage assembly. REVISTA SBA CONTROLE & AUTOMAÇÃO, 2010, 21, (6), pp 634–646.CrossRefGoogle Scholar
Mosqueira, G., Apetz, J., Santos, K.M., Villani, E., Suterio, R. and Trabassoa, L.G. Analysis of the Indoor GPS System as Feedback for the Robotic Alignment of Fuselages using Laser Radar Measurements as Comparison. ROBOT COM INTEGRAT MANUF, 2012, 28, (6), pp 700–709. doi: 10.1016/j.rcim.2012.03.004.CrossRefGoogle Scholar
Marguet, B. and Ribere, B. Measurement-Assisted Assembly Applications on Airbus Final Assembly Lines. SAE Technical Paper, v. 2003-01-2950, 2003. doi: 10.4271/2003-01-2950.CrossRefGoogle Scholar
Zhang, Z., Li, H., Han, Q. and Gao, H. Visual sensor-guided robotic adaptive assembly of aero aluminum alloy tube, INT J ADV MANUF TECHNOL, 2015, 78, pp 2057. doi: 10.1007/s00170-014-6771-x.CrossRefGoogle Scholar
Summers, M. Robot Capability Test and Development of Industrial Robot Positioning System for the Aerospace Industry. SAE Technical Paper, v. 2005-01-3336, 2005. doi: 10.4271/2005-01-3336.CrossRefGoogle Scholar
Kiraci, E., Franciosa, P., Turley, G.A., Olifent, A., Attridge, A. and Williams, M.A. Moving towards in-line metrology: evaluation of a Laser Radar system for in-line dimensional inspection for automotive assembly systems, INT J ADV MANUF TECHNOL, 2017, 91, pp 69. doi: 10.1007/s00170-016-9696-8.CrossRefGoogle Scholar
Nikon Metrology K-series optical CMM Data Sheet. [S.l.], 2012.Google Scholar
Amorim, D. Y. K., Sutério, R. and Trabasso, L.G. Evaluation of a Photogrammetric System Employed in the Closed Loop Control of Robots Performing Drilling and Fastening of Aeronautical Structural Assembly. ABCM Symposium Series in Mechatronics - Sensors&Actuators.1 ed., v.5, pp 1306–1314, 2012.Google Scholar
Furtado, L., Villani, E., Trabasso, L.G. and Silva, C. DTW: A Design Method for Designing Robot End-Effectors. J BRAZ SOC MECH SCI, 2014, 36, (4), pp 871–885. doi: 10.1007/s40430-013-0109-8.CrossRefGoogle Scholar
Santos, K.M. and Trabasso, L.G. A Cooperative Robotic System Applied to the Riveting Process. ABCM Symposium Series in Mechatronics - Robotics.1 ed., v.5, pp 1185–1193, 2012.Google Scholar
KUKA Roboter GmbH. KR 500-2 Data Sheet. 02.09.2008. ed. [S.l.], 2008.Google Scholar
ISO. EN ISO 9283: Manipulating industrial robots - Performance criteria and related test results, 1998.Google Scholar
Montgomery, D.C. Design and Analysis of Experiments. John Wiley & Sons, Hoboken, NJ, 2006.Google Scholar