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A Conceptual Digital Twin for Cost-Effective Development of a Welding Robotic System for Smart Manufacturing

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Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) (MMMS 2020)

Abstract

With rapid technology advancements and impacts of digital trans-formation technologies, there have been a lot of efforts in recent years at the global and national scope to develop technology eco-systems moving toward Industry 4.0. There has also been a growing number of studies about optimization of process parameters based on AI, IoT and Bigdata analytics, including CNC machining, additive manufacturing, as well as industrial welding with robots, for development of Smart Manufacturing (SM), which is one of the key elements of Industry 4.0. However, there are challenges to fully develop and apply in industrial practices the ideal SM models in the next 5 to 10 years. It is necessary to develop the cost-effective SM models that are easy to understand with a high level of applicability in practice and adoptability for SMEs. In this paper, a conceptual digital twin is proposed, with the focus on cost-effective design and development of a welding robotic system for smart manufacturing.

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Acknowledgement

This research is supported by Vingroup Innovation Foundation (VINIF) in project code VINIF.2019.DA08. It is also supported by a Research Environment Links, ID 528085858, under the Newton Fund partnership; the grant is funded by the UK Department for Business, Energy and Industrial Strategy and delivered by the British Council.

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Correspondence to Chu Anh My .

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Vu, M.D. et al. (2021). A Conceptual Digital Twin for Cost-Effective Development of a Welding Robotic System for Smart Manufacturing. In: Long, B.T., Kim, YH., Ishizaki, K., Toan, N.D., Parinov, I.A., Vu, N.P. (eds) Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). MMMS 2020. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-69610-8_134

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  • DOI: https://doi.org/10.1007/978-3-030-69610-8_134

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