Autors: Zaharinov, V. V., Malakov, I. K., Hasansabri H.
Title: Determining the Influence of Model Parameters on the Choosing of an Optimal Size Range of Linear Modules for Automated Sliding Doors
Keywords: automatic sliding doors, optimization, post-optimal analysis, sensitivity analysis, size ranges

Abstract: The paper shows the results from a sensitivity (post-optimal) analysis of an optimization problem regarding the choosing of an optimal size range of driving modules for automatic doors. The analysis is carried out by changing certain mathematical model parameters while holding the rest constant. The obtained solutions are compared against the optimal solution and an analysis is carried out. The latter aims for exposing the most significant (influential) parameters of the mathematical model, which must be specified with utmost precision and certainty, in order for the obtained optimal solution to meet the problem's definition and requirements. All of this shows the practical significance of such analysis, and makes it an important stage in the design of size ranges.

References

  1. Lotz, J. Beherrschung von Unsicherheit in der Baureihenentwicklung, Ph.D. Dissertation, Mechanical Engineering, TU-Darmstadt, Darmstadt, Germany, 2018.
  2. Pahl, G., Beitz, W. & Feldhuzen, J. Konstruktionslehre. Methoden und anwendung, Springer-Verlag, ISBN 354-0-340-60-2, Berlin/Heidelberg, 2007.
  3. Simpson, T. Product platform design and customization: Status and promise, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 18, No. 1, 2004, pp. 3-20, DOI: 10.1017/S0890060404040028.
  4. Mueller, D. A cost calculation model for the optimal design of size ranges, Journal of Engineering Design, Vol. 22, No. 7, 2011, pp. 467-485, DOI: 10.1080/09544820903449218.
  5. Malakov, I., Zaharinov, V. & Tzenov, V. Size ranges optimization, Procedia Engineering, Vol. 100, 2015, pp. 791-800, DOI: 10.1016/j.proeng.2015.01.433.
  6. Dorion, Automated doors, https://dorion.bg/produkti-iuslugi/ avtomatichni-vrati/, Accessed on May, 2024.
  7. Dormakaba Meeting all your access needs, Product Brochure, 2022.
  8. Alumil, Automated sliding doors and windows. https://www.alumil.com/international/homeowners/products/windows-doors/automated-sliding-insulated-system-supreme-s650-e-motion, Accessed on May, 2024.
  9. Record, Automated doors, https://record-bg.com/, Accessed on May, 2024
  10. GEZE, Automatic Sliding Door, Product Brochure, 2023.
  11. Borgonovo, E. Sensitivity analysis, Springer, 2017, ISBN 978-3-319-52257-9.
  12. Saltelli, A., Chan, K. & Scott, E. Sensitivity analysis, John Wiley & Sons, ISBN 978-0-470-74382-9, New York, 2009.
  13. Diakov, D., Komarski, D., Nikolova, H., Optimization of Butterfly Flexures for Angular Positioning(2021) 31st International Scientific Symposium Metrology and Metrology Assurance, MMA 2021, DOI: 10.1109/MMA52675.2021.9610833
  14. Dichev, D., Zhelezarov, I., Madzharov, N. System for measuring the attitude of moving objects, using a Kalman filter and MEMS sensors. Comptes rendus de l'Academie bulgare des Sciences, volume 72, issue 11, 2019, pp. 1527-1536. DOI 10.7546/CRABS.2019.11.10
  15. Dichev, D., I. Zhelezarov, T. Karadzhov, N. Madzharov, D. Diakov. Method for Measuring Motion Parameters of Moving Objects. 12th International Scientific and Practical Conference on Environment, Technology, Resources, volume 3, June, 2019, Rezekne, Latvia, pp. 27-31. DOI: 10.17770/etr2019vol3.4131
  16. Dichev, D., Koev, H., Bakalova, T., Louda, P. suring Method for Gyro-Free Determination of the Parameters of Moving Objects. Metrology and Measurement Systems. Volume 23, Issue 1, 2016, pp. 107-118. DOI: 10.1515/mms-2016-0001
  17. Dichev, D., I. Zhelezarov, R. Dicheva, D. Diakov, H. Nikolova, G. Cvetanov. Algorithm for estimation and correction of dynamic errors. 30th International Scientific Symposium Metrology and Metrology Assurance, MMA 2020, September, 2020, Sozopol, Bulgaria. DOI: 10.1109/MMA49863.2020.9254261
  18. Rai, R. & Allada, V. Modular product family design: Agent-based pareto-optimization and quality loss function-based post-optimal analysis, International journal of production research, Vol. 41, No. 17, 2003, pp. 4075-4098, DOI: 10.1080/0020754031000149248.
  19. Razavi, S. & Gupta, H. A new framework for comprehensive, robust, and efficient global sensitivity analysis: Theory, Water Resource Research, Vol. 52, No. 1, 2016, pp. 423-439, DOI: 10.1002/2015WR017559.
  20. Pianosi, F., Beven, K., Freer, J., Hall, J., Rougier, J., Stephenson, D. & Wagener, T. Sensitivity analysis of environmental models: A systematic review with practical workflow, Environmental Modelling & Software, Vol. 79, 2016, pp. 214-232, DOI: 10.1016/j.envsoft.2016.02.008.
  21. Malakov, I. Optimization of size ranges of technical means for automation of discrete production, Dissertation for the Doctor of Science degree, Sofia, 2020.
  22. Kats, G., Kovalev, A. Technical and economic analysis and optimization of machine structures. Moscow, Mashinostroenie, 1981.
  23. Groover, M. Automation, Production Systems and Computer-Integrated Manufacturing, Second Edition, Prentice Hall, ISBN: 9780130889782, 2001.

Issue

34th International Scientific Symposium Metrology and Metrology Assurance 2024, MMA 2024, 2024, , https://doi.org/10.1109/MMA62616.2024.10817624

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus