Amos Ng
School of Engineering Science
Amos Ng
Professor of Automation Engineering
Virtual factories with knowledge-driven optimization (VF-KDO) is an eight-year research profile that is being coordinated by the University of Skövde. Research within this profile aims to help strengthen the competitiveness of Swedish industry.
In order to do this, the research within this profile aims to deliver the kinds of knowledge and innovations in virtual development and optimization techniques that are crucial for designing and operating next-generation manufacturing systems. In this way, industrial enterprises can pursue development without needing to invest in unfinished solutions.
Production facility of the future
This profile conducts research into how a smart and connected factory (VF) can utilise autonomous decision-making processes to optimise operational planning, prioritisation, logistics and changeovers in the manufacturing process. The results of this research will be decision support that permits flexible and cost-effective production.
The other aspect of this research profile – knowledge-driven optimization (KDO) – works to manage the ever-shorter product life cycles in industry. This work includes data from many process and production levels. It allows the optimization of the entire production chain – unlike today, where each part of the chain is optimized separately.
Eight partner companies
Besides the University of Skövde, this research profile includes Aurobay, AB Volvo, Scania, IKEA Industry, Skandia Elevator, FlexLink, Arla Foods, and ABB. Companies today that lie the forefront of technological development, but which are also aware of the challenges of the future and the importance of further strengthening their expertise. This profile is financed by the Knowledge Foundation, the partner companies and the University.
The profile's unique combination
The range of industry solutions within this profile fall within seven different areas of research
- OPT-KNOW (knowledge-driven optimisation)
- INTERACT (interactive and visual analyses)
- LINK (data, models and data-linked infrastructure)
- FLOW (flow modelling and reconfiguration at many levels)
- ROBOT (virtual robotics)
- HUMAN (digital modelling of human beings)
- PROCESS (virtual processes)
Together, these cover the entire production chain, generating knowledge and innovations so that Sweden’s manufacturing industry can continue to lie at the forefront.
For more information, please visit the external webpage.
Publications
2023
2023. Doctoral thesis.
Mathematics
2023. Article.
https://doi.org/10.3390/math11061527
International Journal of Manufacturing Research
2023. Article. https://doi.org/10.1504/IJMR.2023.131583
International Journal of Manufacturing Research
2023. Article.
https://doi.org/10.1504/ijmr.2024.10057049
Systems
2023. Article.
https://doi.org/10.3390/systems11080395
International Journal of Services Operations and Informatics
2023. Article.
https://doi.org/10.1504/IJSOI.2023.132345
2023. Doctoral thesis.
2022
Proceedings of the 2022 Winter Simulation Conference
2022. Conference paper. https://doi.org/10.1109/WSC57314.2022.10015335
Decision Analytics Journal
2022. Article.
https://doi.org/10.1016/j.dajour.2022.100039
Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022: 14–16 October 2022 Bournemouth, United Kingdom
2022. Conference paper. https://doi.org/10.1109/ICEBE55470.2022.00058
