Enriching Laser Powder Bed Fusion Part Data Using Category Theory

Laser powder bed fusion (LPBF) is a promising metal additive manufacturing technology for producing functional components. However, there are still a lot of obstacles to overcome before this technology is considered mature and trustworthy for wider industrial applications. One of the biggest obstacl...

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Published in:Journal of Manufacturing and Materials Processing 2024-08, Vol.8 (4), p.130
Main Authors: Qin, Yuchu, Narasimharaju, Shubhavardhan Ramadurga, Qi, Qunfen, Lou, Shan, Zeng, Wenhan, Scott, Paul J., Jiang, Xiangqian
Format: Article
Language:English
Subjects:
Additive manufacturing
Barriers
category theory
Collaboration
data modelling
data semantics
Design specifications
Geometry
Industrial applications
Knowledge management
Knowledge representation
laser powder bed fusion
Lasers
Ontology
part realisation process
Powder beds
Process planning
Product life cycle
Reproducibility
Semantic web
Semantics
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container_issue 4
container_start_page 130
container_title Journal of Manufacturing and Materials Processing
container_volume 8
creator Qin, Yuchu
Narasimharaju, Shubhavardhan Ramadurga
Qi, Qunfen
Lou, Shan
Zeng, Wenhan
Scott, Paul J.
Jiang, Xiangqian
description Laser powder bed fusion (LPBF) is a promising metal additive manufacturing technology for producing functional components. However, there are still a lot of obstacles to overcome before this technology is considered mature and trustworthy for wider industrial applications. One of the biggest obstacles is the difficulty in ensuring the repeatability of process and the reproducibility of products. To tackle this challenge, a prerequisite is to represent and communicate the data from the part realisation process in an unambiguous and rigorous manner. In this paper, a semantically enriched LPBF part data model is developed using a category theory-based modelling approach. Firstly, a set of objects and morphisms are created to construct categories for design, process planning, part build, post-processing, and qualification. Twenty functors are then established to communicate these categories. Finally, an application of the developed model is illustrated via the realisation of an LPBF truncheon.
doi_str_mv 10.3390/jmmp8040130
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subjects Additive manufacturing
Barriers
category theory
Collaboration
data modelling
data semantics
Design specifications
Geometry
Industrial applications
Knowledge management
Knowledge representation
laser powder bed fusion
Lasers
Ontology
part realisation process
Powder beds
Process planning
Product life cycle
Reproducibility
Semantic web
Semantics
title Enriching Laser Powder Bed Fusion Part Data Using Category Theory
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