Siyuan Chen

Doctoral Student at Production Systems

Siyuan holds a background in both computer science and industrial engineering. His research centers on the utilization of artificial intelligence-enhanced digital twins to facilitate smart maintenance practices. Siyuan's work aims to develop an integrated manufacturing analytical platform designed to empower decision-making for industrial workers. His research interests encompass reinforcement learning, deep learning, and digital twin technologies.

Source: chalmers.se
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Showing 2 publications

2023

Understanding Stakeholder Requirements for Digital Twins In Manufacturing Maintenance

Siyuan Chen, Juan Pablo González Sánchez, Ebru Turanoglu Bekar et al
Proceedings - Winter Simulation Conference, p. 2008-2019
Paper in proceeding
2023

Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP

Paulo Victor Lopes, Siyuan Chen, Juan Pablo González Sánchez et al
Proceedings - Winter Simulation Conference. Vol. 2023, p. 1996-2007
Paper in proceeding

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Showing 1 research projects

2021–2024

Integrated Manufacturing Analytics Platform för Prediktivt Underhåll med Iot.

Anders Skoogh Production Systems
Siyuan Chen Production Systems
Jon Bokrantz Production Systems
Ebru Turanoglu Bekar Production Systems
Sabino Francesco Roselli Automation
VINNOVA

1 publication exists
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