Towards Industry 4.0: The Future Automated Aircraft Assembly Demonstrator

  • Adrien DrouotEmail author
  • Ran Zhao
  • Lucas Irving
  • Svetan Ratchev
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 530)


As part of the Future Automated Aircraft Assembly Demonstrator developed by the University of Nottingham, this paper presents a new flexible production environment for the complete manufacturing of high-accuracy high-complexity low-volume aerospace products. The aim is to design a product-independent manufacturing and assembly system that can react to fluctuating product specifications and demands through self-reconfiguration. This environment features a flexible, holistic, and context-aware solution that includes automated positioning, drilling and fastening processes, and is suitable for different aircraft structures with scope to address other manufacturing domains in the future (e.g. automotive, naval and energy). The assembly cell features industrial robots for the handling of aircraft components, while intelligent metrology and control systems monitor the cell to ensure that the assembly process is safe and the target tolerances are met. These three modules are integrated into a single standardized interface, requiring only one operator to control the cell. Performance analyses have shown that, using the reconfigurable production environment described hereafter, a positioning accuracy better than ±0.1 mm can be achieved for large airframe components.


Intelligent and flexible manufacturing systems Positioning systems High accuracy Industrial robots 


  1. 1.
    Ahmad, S.: Analysis of robot drive train errors, their static effects, and their compensations. IEEE J. Robot. Autom. 4(2), 117–128 (1988)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Biagiotti, L., Melchiorri, C.: Trajectory Planning for Automatic Machines and Robots. Springer, Heidelberg (2008). Scholar
  3. 3.
    Browne, J., Dubois, D., Rathmill, K., Sethi, S.P., Stecke, K.E.: Classification of flexible manufacturing systems. FMS Mag. 2, 114–117 (1984)Google Scholar
  4. 4.
    Chaplin, J.C., et al.: Evolvable assembly systems: a distributed architecture for intelligent manufacturing. IFAC-PapersOnLine 48(3), 2065–2070 (2015). Proceedings of the 15th IFAC Symposium on Information Control in Manufacturing, Ottawa, CanadaCrossRefGoogle Scholar
  5. 5.
    Drath, R., Horch, A.: Industrie 4.0: hit or hype? IEEE Ind. Electron. Mag. 8(2), 56–58 (2014)CrossRefGoogle Scholar
  6. 6.
    Dumas, C., Caro, S., Chérif, M., Garnier, S., Furet, B.: A methodology for joint stiffness identification of serial robots. In: Proceedings of the IEEE-RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, pp. 464–469 (2010)Google Scholar
  7. 7.
    Gong, C., Yuan, J., Ni, J.: Nongeometric error identification and compensation for robotic system by inverse calibration. Int. J. Mach. Tools Manuf. 40(14), 2119–2137 (2000)CrossRefGoogle Scholar
  8. 8.
    Greenway, B.: Robot accuracy. Ind. Robot: Int. J. 27(4), 257–265 (2000)CrossRefGoogle Scholar
  9. 9.
    Inman, J., Carbrey, B., Calawa, R., Hartmann, J., Hempstead, B., Assadi, M.: A flexible development system for automated aircraft assembly. SAE Technical Paper 961878 (1996)Google Scholar
  10. 10.
    Kabsch, W.: A solution for the best rotation to relate two sets of vectors. Acta Cryst. A32, 922–923 (1976)CrossRefGoogle Scholar
  11. 11.
    Kabsch, W.: A Discussion of the Solution for the Best Rotation to Relate Two Sets of Vectors. Acta Cryst. A34, 827–828 (1978)CrossRefGoogle Scholar
  12. 12.
    Kihlman, H., Ossbahr, G., Engström, M., Anderson, J.: Low-cost automation for aircraft assembly. SAE Technical Paper 2004-01-2830 (2004)Google Scholar
  13. 13.
    Kröger, T.: On-Line Trajectory Generation in Robotic Systems. Springer, Heidelberg (2010). Scholar
  14. 14.
    Leitão, P., Restivo, F.: ADACOR: a holonic architecture for agile and adaptive manufacturing control. Comput. Ind. 57(2), 121–130 (2006)CrossRefGoogle Scholar
  15. 15.
    Meffert, G., Mbarek, T., Biyiklioglu, N.: High precision positioning system for aircraft structural. In: Proceedings of the 15th International Conference on Experimental Mechanics, Porto, Portugal (2012)Google Scholar
  16. 16.
    Mehrabi, M.G., Ulsoy, A.G., Koren, Y.: Reconfigurable manufacturing systems: key to future manufacturing. J. Intell. Manuf. 11(4), 403–419 (2000)CrossRefGoogle Scholar
  17. 17.
    Mooring, B.W., Roth, Z.S., Driels, M.R.: Fundamentals of Manipulator Calibration. Wiley, Hoboken (1991)Google Scholar
  18. 18.
    Olabi, A., Damak, M., Béarée, R., Gibaru, O., Leleu, S.: Improving the accuracy of industrial robots by offline compensation of joints errors. In: Proceedings of the IEEE International Conference on Industrial Technology, Kos, Greece (2012)Google Scholar
  19. 19.
    Rognant, M., Courteille, E., Maurine, P.: A systematic procedure for the elastodynamic modeling and identification of robot manipulators. IEEE Trans. Robot. 26(6), 1085–1093 (2010)CrossRefGoogle Scholar
  20. 20.
    Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators. Springer, London (2000). Scholar
  21. 21.
    Sethi, A.K., Sethi, S.P.: Flexibility in manufacturing: a survey. Int. J. Flex. Manuf. Syst. 2(4), 289–328 (1990)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Tharumarajah, A.: Comparison of the bionic, fractal and holonic manufacturing system concepts. Int. J. Comput. Integr. Manuf. 9(3), 217–226 (1996)CrossRefGoogle Scholar
  23. 23.
    Van Brussel, H., Wyns, J., Valckenaers, P., Bongaerts, L., Peeters, P.: Reference architecture for holonic manufacturing systems: PROSA. Comput. Ind. 37(3), 255–274 (1998)CrossRefGoogle Scholar
  24. 24.
    Wooldridge, M., Jennings, N.R.: Agent theories, architectures, and languages: a survey. In: Wooldridge, M.J., Jennings, N.R. (eds.) ATAL 1994. LNCS (LNAI), vol. 890, pp. 1–39. Springer, Heidelberg (1995). Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Adrien Drouot
    • 1
    Email author
  • Ran Zhao
    • 2
  • Lucas Irving
    • 3
  • Svetan Ratchev
    • 3
  1. 1.Institut FEMTO-ST, CNRS UMR 6174, UFC – ENSMM – UTBMBesançonFrance
  2. 2.College of Information and Electrical EngineeringChina Agricultural UniversityBeijingChina
  3. 3.Institute for Advanced ManufacturingUniversity of NottinghamNottinghamUK

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