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MULTIDISCIPLINARY DESIGN ANALYSIS AND OPTIMIZATION FRAMEWORK FOR REGULATORY DRIVEN MEDICAL DEVICE DEVELOPMENT

Published online by Cambridge University Press:  19 June 2023

Soumya Ranjan Mishra  and
Kamran Behdinan
Soumya Ranjan Mishra*
Affiliation:
University of Toronto
Kamran Behdinan
Affiliation:
University of Toronto
*
Mishra, Soumya Ranjan, University of Toronto, Canada, sr.mishra@mail.utoronto.ca

Abstract

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Multidisciplinary design optimization (MDO) is a technique used in the design of systems involving the integration of many disciplines. The architecture and formulation of MDO has an impact on the solution time and optimality of final designs. The process of developing medical devices requires the combination of medical and technical knowledge and abilities. Developing a medical device is done by a complicated collection of Product Development Processes that entail tremendous oversight to ensure conformity to regulatory requirements. Regulatory standards often provide stern “Go / No-Go” policies which may discretize the design variables further increasing the complexity of the optimization problem. This work proposes a novel design approach which utilizes systems engineering practices to undertake complex multidisciplinary design optimization while implementing regulatory guidelines for medical devices. The formulated model is then applied and examined in a case study towards the development of a piezoelectric respiratory sensor. It is observed that the novel framework would extensively improve the design space definition and process driven product development practices.

Keywords

Multi- / Cross- / Trans-disciplinary processesOptimisationBiomedical design
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2735 - 2744
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Behdinan, , et al. (2004). “Evaluation of multidisciplinary optimization approaches for aircraft conceptual design.” 10th AIAA/ISSMO multidisciplinary analysis and optimization conference.Google Scholar
Behdinan, , et al. (2005). “Uncertainty-based MDO for aircraft conceptual design.” Aircraft Engineering and Aerospace Technology: An International Journal 87, no. 4 (2015): 345–356.Google Scholar
Behdinan, , et al. (2011). “Reliability and possibility based multidisciplinary design optimization for aircraft conceptual design.” In 11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, including the AIAA Balloon Systems Conference and 19th AIAA Lighter-Than, p. 6960.Google Scholar
Benaouali, Abdelkader, and Kachel, Stanisław. 2019. “Multidisciplinary Design Optimization of Aircraft Wing Using Commercial Software Integration.” Aerospace Science and Technology 92 (September): .CrossRefGoogle Scholar
Bussemaker, J., Boggero, L. and Ciampa, P.D. (2022), From System Architecting to System Design and Optimization: A Link Between MBSE and MDAO. INCOSE International Symposium, 32: 343–359.CrossRefGoogle Scholar
Ciampa, P. D., & Nagel, B. (2020). Agile paradigm: The next generation collaborative MDO for the development of Aeronautical Systems. Progress in Aerospace Sciences, 119, 100643. https://doi.org/10.1016/j.paerosci.2020.100643CrossRefGoogle Scholar
Ciampa, P.D., La Rocca, G. and Nagel, B. (2020), “A MBSE Approach to MDAO Systems for the Development of Complex Products”, AIAA AVIATION 2020 FORUM, American Institute of Aeronautics and Astronautics.CrossRefGoogle Scholar
Estefan, J. A. 2007. “Survey of Model-Based Systems Engineering (MBSE) Methodologies.” Incose MBSE Focus Group. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.517.219&rep=rep1&type=pdf.Google Scholar
Fuchs, Joachim. 2012. “Multi-Disciplinary MBSE Approach in Industrial Phases.” In Infotech@Aerospace 2012. Infotech@Aerospace Conferences. American Institute of Aeronautics and Astronautics.CrossRefGoogle Scholar
Giunta, A. A., Balabanov, V., Haim, D., Grossman, B., Mason, W. H., Watson, L. T., and Haftka, R. T.. 1997. “Multidisciplinary Optimisation of a Supersonic Transport Using Design of Experiments Theory and Response Surface Modelling.” The Aeronautical Journal 101 (1008): 347–356.CrossRefGoogle Scholar
Habermehl, C., Höpfner, G., Berroth, J., Neumann, S. and Jacobs, G. (2022), “Optimization Workflows for Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO)”, NATO Advanced Science Institutes Series E: Applied Sciences, Multidisciplinary Digital Publishing Institute, Vol. 12 No. 11, p. 5316.Google Scholar
Hill, B. and Annesley, S.H. (2020) “Monitoring respiratory rate in adults,” British Journal of Nursing, 29(1), pp. 12–16. Available at: https://doi.org/10.12968/bjon.2020.29.1.12.CrossRefGoogle ScholarPubMed
Kazlovich, Kate, Mishra, Soumya Ranjan, Behdinan, Kamran, Gladman, Aviv, May, Jesse, and Mashari, Azad. “Open Ventilator Evaluation Framework: A Synthesized Database of Regulatory Requirements and Technical Standards for Emergency Use Ventilators from Australia, Canada, UK, and US.” HardwareX 11 (2022). https://doi.org/10.1016/j.ohx.2022.e00260.CrossRefGoogle Scholar
Leserf, P., de Saqui-Sannes, P. and Hugues, J. (2015), “Multi domain optimization with SysML modeling”, 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), available at:https://doi.org/10.1109/etfa.2015.7301406.CrossRefGoogle Scholar
Madni, Azad M., and Sievers, Michael. 2018. “Model-Based Systems Engineering: Motivation, Current Status, and Research Opportunities.” Systems Engineering and Electronics 21 (3): .Google Scholar
Martins, Joaquim R. R. A., and Lambe, Andrew B.. 2013. “Multidisciplinary Design Optimization: A Survey of Architectures.” AIAA Journal 51 (9): .CrossRefGoogle Scholar
Massaroni, C. et al. (2019) “Contact-based methods for measuring respiratory rate,” Sensors, 19(4), p. 908. Available at: https://doi.org/10.3390/s19040908.CrossRefGoogle ScholarPubMed
Torry-Smith, Mørkeberg, et al, J.. (2012) “Challenges in designing Mechatronic Systems,” Journal of Mechanical Design, 135(1). Available at: https://doi.org/10.1115/1.4007929.Google Scholar
Nicolò, A. et al. (2020) “The importance of respiratory rate monitoring: From healthcare to sport and exercise,” Sensors, 20(21), p. 6396. Available at: https://doi.org/10.3390/s20216396.CrossRefGoogle ScholarPubMed
Ocampo, Jovany Uribe, and Kaminski, Paulo Carlos. 2019. “Medical Device Development, from Technical Design to Integrated Product Development.” Journal of Medical Engineering & Technology 43 (5): 287–304.CrossRefGoogle ScholarPubMed
Wynn, David C., and John Clarkson, P.. 2018. “Process Models in Design and Development.” Research in Engineering Design 29 (2): 161–202CrossRefGoogle Scholar