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Investigating multi-level ontology to support manufacturing during demand fluctuation

Kazantsev, N.; Niewiadomski, K.; Martínez-Arellano, G.; Elshafei, B.; Mo, F.; Murthy, S. R.

Authors

N. Kazantsev

K. Niewiadomski

F. Mo

S. R. Murthy



Abstract

Responding to demand fluctuations represents a challenge for manufacturers, as they often face resource limitations and cannot assess all potential solutions. This paper presents a low-cost semantic engineering solution (ontology) to coordinate potential responses to disruption at the supply chain, factory and firm levels. The research method uses three cycles of design science research to develop a multi-level ontology and assess its potential to coordinate responses. The feedback from companies positions ontology as a solution for stress-testing next generation manufacturing systems. Using semantic engineering, companies can assess the available responses before disruptions, plan potential responses, and support their decision-making during demand fluctuation.

Citation

Kazantsev, N., Niewiadomski, K., Martínez-Arellano, G., Elshafei, B., Mo, F., & Murthy, S. R. (2023). Investigating multi-level ontology to support manufacturing during demand fluctuation. In Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023). https://doi.org/10.1049/icp.2023.1752

Presentation Conference Type Edited Proceedings
Conference Name Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023)
Start Date Sep 25, 2023
End Date Sep 26, 2023
Acceptance Date Jun 21, 2023
Online Publication Date Nov 21, 2023
Publication Date 2023
Deposit Date Mar 19, 2024
Publicly Available Date Apr 9, 2024
Publisher Institution of Engineering and Technology (IET)
Book Title Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023)
DOI https://doi.org/10.1049/icp.2023.1752
Public URL https://nottingham-repository.worktribe.com/output/28140223
Publisher URL https://ieeexplore.ieee.org/document/10324808

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