Service oriented digital twin for additive manufacturing process
Zijue Chen, Kanishka Surendraarcharyagie, Keenan Granland, Chao Chen, Xun Xu, Yi Xiong, C.H.J. Davies, Yunlong Tang
Abstract
Currently, Industry 4.0 is rapidly developing, empowered by IoT, cloud computing and AI. As two crucial components of Industry 4.0, digital twins and additive manufacturing (AM) are attracting increasing attention. Despite considerable research in recent years on developing digital twins for AM, the field still faces discrepancies in definition and confusion in development processes, making the development of AM digital twins expensive. The reason behind this is the uniqueness of each AM process, leading to low adaptability in AM digital twins. To address this issue, this work summarises AM digital twins found in the literature review and proposes a novel, service-oriented framework comprising four layers: service, model, data, and interface. This framework aims to enhance the reusability of developed AM digital twins across various levels. The commonly used components in each layer are also summarised to assist developers in rapidly constructing AM digital twins tailored to their specific needs. A case study is included to demonstrate the framework’s effectiveness and potential.