Investigating multi-level ontology to support manufacturing during demand fluctuation

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

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