Development of software complex for analysis and optimization of the aircraft assembly process

DOI: 10.34759/trd-2022-124-23


Zaitseva N. I.*, Pogarskaia T. A.**

Peter the Great Saint-Petersburg Polytechnic University, 29, Polytechnicheskaya str., St. Petersburg, 195251, Russia



The presented work is devoted to describing the multiprocessor software complex ASRP (Assembly Simulation of Riveting Process), being developed as part of a joint project of Peter the Great St. Petersburg Polytechnic University and the AIRBUS SAS. This complex is meant for simulating and optimizing the aircraft assembly process, with account for the fact that aircraft building places rather strict requirements to the parts assembly quality due to high operational loads. The authors propose employing in the complex mathematical modeling and numerical optimization methods, which allow predicting and optimizing the quality of the parts joints prior to implementation of the technologies for the assembly line being developed.

In the aircraft building industry, one and the same assembly technology is being employed while series assembly for all aircraft of the same type being assembled. Accordingly, while modeling the assembly process it is necessary to account for random assembly deviations, such as deviations of parts from the rated shape or errors in positioning. The ASRP suggests accounting for these deviations through modelling the random initial gap between parts.

To optimize assembly processes, it is necessary creation and analysis of various options of the fixing elements positioning is required. A fundamentally new approach has been developed for the ASRP to optimize the temporary fastener patterns, based on the preliminary assessment of the stress-strain state of the assembled structure.

When modeling assembly processes considering assembly variations and the fastener patterns optimizing, the necessity to solving many similar problems with hundreds of different initial data arises. For this reason, the ASRP suggests employing parallel computations for analyzing and optimizing the assembly processes.

This presented article describes the structure of the ASRP software package, the developed methods for the assembly process modeling, methods for the initial gap modeling, as well as methods for optimizing the fastener elements placing. The efficiency of the proposed optimization methods and parallelization algorithms is being studied on a practical example associated with the analysis of the assembling process of the tail section of Airbus A350.


process, optimization, contact problem, theory of reliability


  1. Wei L. Prediction of the aircraft fault maintenance sorties based on least squares of linear regression, 2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization, 2012. DOI:10.1109/ICSSEM.2012.6340849
  2. Tolstikov V.G., Pykhalov A.A. Trudy MAI, 2021, no. 118. URL: DOI: 10.34759/trd-2021-118-05
  3. Peng H., Wang B. 3D statistical tolerance analysis technique and the application in piston aeroengine assembly, 2017 8th International Conference on Mechanical and Aerospace Engineering (ICMAE), 2017. DOI:10.1109/ICMAE.2017.8038680
  4. Shen Z., Ameta G., Shah J.J., Davidson J.K. A Comparative Study Of Tolerance Analysis Methods, Journal of Computing and Information Science in Engineering, 2005, vol. 5 (3), DOI:10.1115/1.1979509 95
  5. Yang D., Qu W., Ke Y. Evaluation of residual clearance after pre-joining and pre-joining scheme optimization in aircraft panel assembly, Assembly Automation, 2016, vol. 5(3). DOI:10.1108/AA-12-2015-129
  6. Blanchot V., Daidie A. Riveted assembly modelling: Study and numerical characterisation of a riveting process, Journal of Materials Processing Technology, 2006, vol. 180, no. 1-3, pp. 201-209. DOI:10.1016/J.JMATPROTEC.2006.06.005
  7. Bedair O.K., Eastaugh G.F. A numerical model for analysis of riveted splice joints accounting for secondary bending and plates/rivet interaction, Thin-Walled Structures, 2007, vol. 45, no. 3, pp. 251-258. DOI:10.1016/J.TWS.2007.03.001
  8. Ni J., Tang W.C., Pan M., Qiu X., Xing Y. Assembly sequence optimization for minimizing the riveting path and overall dimensional error, Journal of Engineering Manufacture, 2018, vol. 232, no.14. DOI:10.1177/0954405417699012
  9. Dyukov V.A. Trudy MAI, 2021, no. 116. URL: DOI: 10.34759/trd-2021-116-12
  10. Chzho I.K., Solyaev Yu.O. Trudy MAI, 2021, no. 120. URL: DOI: 10.34759/trd-2021-120-07
  11. Tabar R.S., Warmefjord K., Soderberg R. Rapid sequence optimization of spot welds for improved geometrical quality using a novel stepwise algorithm, Engineering Optimization, 2021, vol. 53, no. 5. DOI:10.1080/0305215X.2020.1757090
  12. Liao Y.G. Optimal design of weld pattern in sheet metal assembly based on a genetic algorithm, International Journal of Advanced Manufacturing Technology, 2005, vol. 26, no. 5-6, pp. 512-516. DOI:10.1007/S00170-003-2003-5
  13. Ertas A.H., Sonmez F.O. Optimization of spot-weld joints // Proceedings of the Institution of Mechanical Engineers, Part C., Journal of Mechanical Engineering Science, 2009, vol. 223, no. 3, pp. 545-555. DOI:10.1243/09544062JMES1171
  14. Rakotondrainibe L., Desai J., Orval P., Allaire G. Coupled topology optimization of structure and connections for bolted mechanical systems, European Journal of Mechanics, A/Solids, 2022, vol. 93. DOI: 10.1016/j.euromechsol.2021.104499
  15. Petukhova M., Lupuleac S., Shinder J., Smirnov A., Yakunin S., Bretagnol B. Numerical approach for airframe assembly simulation, Journal of Mathematics in Industry, 2014, vol. 4, no. 8. DOI:10.1186/2190-5983-4-8
  16. Hu M., Lin Z., Lai X., Ni J. Simulation and analysis of assembly processes considering compliant, non-ideal parts and tooling variations, International Journal of Machine Tools and Manufacture, 2001, vol. 41, no. 15, pp. 2233-2243. DOI:10.1016/S0890-6955(01)00044-X
  17. Zaitseva N., Lupuleac S., Khashba V., Shinder, J. Bonhomme E. Approaches to initial gap modeling in final aircraft assembly simulation, ASME International Mechanical Engineering Congress and Exposition, 2020. DOI:10.1115/IMECE2020-23528
  18. Stefanova M., Minevich O., Baklanov S., Petukhova M., Lupuleac S., Grigor’ev B., Kokkolaras M. Convex optimization techniques in compliant assembly simulation, Optimisation Engineering, 2020, vol. 21 (2). DOI:10.1007/s11081-020-09493-z
  19. Pogarskaia T., Lupuleac S., Bonhomme E. Novel approach to optimization of fastener pattern for airframe assembly process, Procedia CIRP, 2020, vol. 93, pp. 1151-1157. DOI:10.1016/j.procir.2020.04.035
  20. Pogarskaia T., Churilova M., Bonhomme E. Application of a Novel Approach Based on Geodesic Distance and Pressure Distribution to Optimization of Automated Airframe Assembly Process, Communications in Computer and Information Science, 2020, pp. 1672-1673. DOI:10.1007/978-3-030-64616-5_14
  21. Lupuleac S., Zaitseva N., Stefanova M., Berezin S., Shinder J., Petukhova M., Bonhomme E. Simulation of the Wing-to-Fuselage Assembly Process, Journal of Manufacturing Science and Engineering, Transactions of the ASME, 2019, vol. 141, no. 6. DOI:10.1115/1.4043365
  22. Lupuleac S., Pogarskaia T., Churilova M., Kokkolaras M., Bonhomme E. Optimization of fastener pattern in airframe assembly, Assembly Automation, 2020, vol. 40, no. 5. DOI:10.1108/aa-03-2019-0040

Download — informational site MAI

Copyright © 2000-2024 by MAI