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Towards a Model-Based Systems Engineering Approach for Robotic Manufacturing Process Modelling with Automatic FMEA Generation

Published online by Cambridge University Press:  26 May 2022

A. Korsunovs ,
A. Doikin ,
F. Campean ,
S. Kabir ,
E. M. Hernandez ,
D. Taggart ,
S. Parker  and
G. Mills
A. Korsunovs*
Affiliation:
University of Bradford, United Kingdom
A. Doikin
Affiliation:
University of Bradford, United Kingdom
F. Campean
Affiliation:
University of Bradford, United Kingdom
S. Kabir
Affiliation:
University of Bradford, United Kingdom
E. M. Hernandez
Affiliation:
University of Bradford, United Kingdom Arrival Ltd, United Kingdom
D. Taggart
Affiliation:
Arrival Ltd, United Kingdom
S. Parker
Affiliation:
Arrival Ltd, United Kingdom
G. Mills
Affiliation:
Arrival Ltd, United Kingdom
*
a.korsunovs2@bradford.ac.uk

Abstract

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The process of generating FMEA following document-centric approach is tedious and susceptible to human error. This paper presents preliminary methodology for robotic manufacturing process modelling in MBSE environment with a scope of automating multiple steps of the modelling process using ontology. This is followed by the reasoning towards automatic generation of process FMEA from the MBSE model. The proposed methodology allows to establish robust and self-synchronising links between process-relevant information, reduce the likelihood of human error, and scale down time expenses.

Keywords

model-based systems engineering (MBSE)process modellingprocess analysisfailure mode and effects analysis (FMEA)reliability
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1905 - 1914
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), 2022.

References

AIAG - Automotive Industry Action Group, (2019), AIAG & VDA FMEA Handbook, Detroit, MIGoogle Scholar
Bell, D., Cox, D., Jackson, S., and Schaefer, P., (1992), “Using Causal Reasoning for Automated Failure Modes and Effects Analysis”, Proc 1992 IEEE Annual Reliability and Maintainability Symposium, pp. 343 – 353, https://dx.doi.org/10.1109/ARMS.1992.187847CrossRefGoogle Scholar
EN, BS 60812:2018 Failure Modes and Effects Analysis (FMEA and FMECA), BSI / European Standard.Google Scholar
Day, J., Donahue, K., Ingham, M., Kadesch, A., Kennedy, A. and Post, E., 2012. Modeling off-nominal behavior in sysml. In Infotech@ Aerospace 2012 (p. 2576), https://dx.doi.org/10.2514/6.2012-2576Google Scholar
Draxler, D., Neureiter, C., Lastro, G., Schwartzkopff, T. and Boumans, M., 2019, May. A domain specific systems engineering framework for modelling electric vehicle architectures. In 2019 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific) (pp. 1–6). IEEE, https://dx.doi.org/10.1109/ITEC-AP.2019.8903596Google Scholar
Ford Motor Company, (1997) The Strategy of Dynamic Control Planning, Training and Reference Manual.Google Scholar
Ford Motor Company, (2011), Failure Modes and Effects Analysis, FMEA Handbook (with Robustness Linkages), Version 4.2, Dearborn, MIGoogle Scholar
Giles, K. and Giammarco, K., 2019. A mission-based architecture for swarm unmanned systems. Systems Engineering, 22(3), pp.271–281, https://dx.doi.org/10.1002/sys.21477CrossRefGoogle Scholar
Girard, Gaëlle & Baeriswyl, Ivan & Hendriks, Jonathan & Scherwey, Roland & Müller, Christian & Hönig, Philipp & Lunde, Rüdiger. (2020). Model based Safety Analysis using SysML with Automatic Generation of FTA and FMEA Artifacts. 5051–5058, https://dx.doi.org/10.3850/978-981-14-8593-0_4941-cdGoogle Scholar
Hawkins, P. G. and Woollons, D. J., (1998), “Failure Modes and Effects Analysis of Complex Engineering Systems using Functional Models, Artificial Intelligence in Engineering, 12, pp. 375 – 397, https://dx.doi.org/10.1016/S0954-1810(97)10011-5Google Scholar
Hecht, M., Dimpfl, E. and Pinchak, J., 2014, November. Automated generation of failure modes and effects analysis from SysML models. In 2014 IEEE International Symposium on Software Reliability Engineering Workshops (pp. 62–65). IEEE, https://dx.doi.org/10.1109/ISSREW.2014.117CrossRefGoogle Scholar
Hecht, Myron & Dimpfl, Emily & Pinchak, Julia., 2014. Automated Generation of Failure Modes and Effects Analysis from SysML Models https://dx.doi.org/10.13140/2.1.4578.9446.Google Scholar
Henshall, E., Campean, I., and Rutter, B. (2014) A Systems Approach to the Development and Use of FMEA in Complex Automotive Applications. SAE Int. J. Mater. Manf. 7(2):280–290, https://dx.doi.org/10.4271/2014-01-0740.Google Scholar
Huang, Z., Hansen, R. and Huang, Z., 2018, January. Toward FMEA and MBSE integration. In 2018 Annual Reliability and Maintainability Symposium (RAMS) (pp. 1–7). IEEE, https://dx.doi.org/10.1109/RAM.2018.8463084Google Scholar
Huang, Z., Swalgen, S., Davidz, H. and Murray, J., 2017, January. MBSE-assisted FMEA approach—Challenges and opportunities. In 2017 Annual Reliability and Maintainability Symposium (RAMS) (pp. 1–8). IEEE, https://dx.doi.org/10.1109/RAM.2017.7889722Google Scholar
Johnson, K.G. and Khan, M. K., (2003), “A Study Into the Use of the Process Failure Mode and Effects Analysis in the Automotive Industry in the UK”, Journal of Materials Processing Technology, 139, pp. 348 - 356, https://dx.doi.org/10.1016/S0924-0136(03)00542-9CrossRefGoogle Scholar
Donahue, K., Kennedy, A & Day, J, (2015) “Automated Generation of Failure Modes and Effects Document from a Simple SysML Model,” NASA Tech Brief.Google Scholar
Kmenta, S. and Ishii, K., (1998), “Advanced FMEA Using Meta Behaviour Modeling For Concurrent Design of Products and Controls”, Proceedings of 1998 ASME Design Engineering Technical Conferences, https://dx.doi.org/10.1115/DETC98/CIE-5702Google Scholar
Marques, M., Agostinho, C., Zacharewicz, G. and Jardim-Gonçalves, R., 2017. Decentralized decision support for intelligent manufacturing in Industry 4.0. Journal of Ambient Intelligence and Smart Environments, 9(3), pp.299–313, https://dx.doi.org/10.3233/AIS-170436CrossRefGoogle Scholar
Papadopoulos, Y., (2013), HiP-HOPS - Automated Fault Tree, FMEA and Optimisation Tool User Manual ver. 2.5, available at: https://hip-hops.co.uk.Google Scholar
Promyoo, R., Alai, S. and El-Mounayri, H., 2019. Innovative digital manufacturing curriculum for industry 4.0. Procedia manufacturing, 34, pp.1043–1050, https://dx.doi.org/10.1016/j.promfg.2019.06.092CrossRefGoogle Scholar
Sarathi, T., Cyr, J., DeLaura, R., Balcius, J., Collins, P. and Shatz, M., 2021, July. Developing a Model Based Systems Engineering Architecture for Defense Wearable Technology. In INCOSE International Symposium (Vol. 31, No. 1, pp. 1065–1078), https://dx.doi.org/10.1002/j.2334-5837.2021.00887.xCrossRefGoogle Scholar
International, SAE (2021) Potential Failure Mode and Effects Analysis (FMEA) Including Design FMEA, Supplemental FMEA-MSR, and Process FMEA, Ground Vehicle Standards J 1739_202101, https://dx.doi.org/10.4271/J1739_202101Google Scholar
Wymore, AM., 1993, Model-Based Systems Engineering: An Introduction to the Mathematical Theory of Discrete Systems and to the Tricotyledon Theory of System Design. Boca Raton: CRC PressGoogle Scholar