A mathematical foundation to support bidirectional mappings between digital models: an application of multi-scale modelling in manufacturing

Q. Qi; W. Terkaj; M. Urgo; X. Jiang; P. J. Scott

doi:10.1098/rspa.2022.0156

A mathematical foundation to support bidirectional mappings between digital models: an application of multi-scale modelling in manufacturing

Q. Qi, W. Terkaj, M. Urgo, X. Jiang, P. J. Scott^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

3 Citations (Scopus)

Abstract

With manufacturing going through the Industry 4.0 revolution, a vast amount of data and information exchange leads to an increase in complexity of digitized manufacturing systems. To tackle such complexity, one solution is to design and operate a digital twin model under different levels of abstraction, with different levels of detail, according to the available information and scope of the model. To support efficient, coherent and stable information flows between models with different levels of detail, a mathematical structure, called a delta lens, has been explored and developed to support rigorous bidirectional transitions between the models. To support different types of abstractions in manufacturing, a hybrid delta lens has been proposed and its formal representation is developed to support the generalization of its structure and properties. Benefits of the proposed hybrid delta lenses are demonstrated through an application to an industrial case to support the modelling of an automatic, high-throughput assembly line.

Original language	English
Article number	20220156
Journal	Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume	478
Issue number	2264
DOIs	https://doi.org/10.1098/rspa.2022.0156
Publication status	Published - 31 Aug 2022

Bibliographical note

Funding Information:
The Huddersfield team (Q.Q., X.J. and P.J.S.) would like to acknowledge the funding support from the EPSRC UKRI Innovation Fellowship (ref. EP/S001328/1), EPSRC Future Advanced Metrology Hub (ref. EP/P006930/1) and EPSRC Fellowship in Manufacturing (ref. EP/R024162/1).

Publisher Copyright:
© 2022 The Authors.

Keywords

assembly line
bidirectional transition
delta lens
digital twin
hybrid delta lens
information flow

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abstract = "With manufacturing going through the Industry 4.0 revolution, a vast amount of data and information exchange leads to an increase in complexity of digitized manufacturing systems. To tackle such complexity, one solution is to design and operate a digital twin model under different levels of abstraction, with different levels of detail, according to the available information and scope of the model. To support efficient, coherent and stable information flows between models with different levels of detail, a mathematical structure, called a delta lens, has been explored and developed to support rigorous bidirectional transitions between the models. To support different types of abstractions in manufacturing, a hybrid delta lens has been proposed and its formal representation is developed to support the generalization of its structure and properties. Benefits of the proposed hybrid delta lenses are demonstrated through an application to an industrial case to support the modelling of an automatic, high-throughput assembly line.",

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A mathematical foundation to support bidirectional mappings between digital models: an application of multi-scale modelling in manufacturing. / Qi, Q.; Terkaj, W.; Urgo, M. et al.
In: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 478, No. 2264, 20220156, 31.08.2022.

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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A mathematical foundation to support bidirectional mappings between digital models: an application of multi-scale modelling in manufacturing

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