TY - JOUR
T1 - Enriching Laser Powder Bed Fusion Part Data Using Category Theory
AU - Qin, Yuchu
AU - Ramadurga Narasimharaju, Shubhavardhan
AU - Qi, Qunfen
AU - Lou, Shan
AU - Zeng, Wenhan
AU - Scott, Paul
AU - Jiang, Jane
N1 - Funding Information:
Y.Q. would like to acknowledge the support of the National Natural Science Foundation of China (No. 52105511). Q.Q. would like to acknowledge the support of the EPSRC UKRI Innovation Fellowship (Ref. EP/S001328/1).
Publisher Copyright:
© 2024 by the authors.
PY - 2024/8/1
Y1 - 2024/8/1
N2 - 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.
AB - 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.
KW - Additive manufacturing
KW - Laser powder bed fusion
KW - Part realisation process
KW - Data modelling
KW - Data semantics
KW - Category theory
KW - additive manufacturing
KW - data semantics
KW - data modelling
KW - part realisation process
KW - category theory
KW - laser powder bed fusion
UR - http://www.scopus.com/inward/record.url?scp=85202616486&partnerID=8YFLogxK
U2 - 10.3390/jmmp8040130
DO - 10.3390/jmmp8040130
M3 - Article
VL - 8
JO - Journal of Manufacturing and Materials Processing
JF - Journal of Manufacturing and Materials Processing
SN - 2504-4494
IS - 4
M1 - 130
ER -