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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.

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