Kevin Gumma
Papers
2
Total Citations
22
H-Index
2
About
Kevin Gumma is a leading researcher in the field of smart manufacturing and reconfigurable assembly systems, with a focus on leveraging digital twins and multi-agent artificial intelligence to create highly adaptive production environments. His work addresses the critical challenge of achieving both flexibility and repeatability in manufacturing, particularly for small-box assembly and reconfigurable robotic cells. Gumma’s most-cited paper, “Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin” (2024, 18 citations), introduces a novel framework that combines swarm intelligence with digital twin technology to enable rapid, autonomous factory layout reconfiguration in response to dynamic market demands. His earlier work, “An adaptive, repeatable and rapid auto-reconfiguration process in a smart manufacturing system for small box assembly” (2022, 4 citations), establishes foundational methods for controlling the repeatability of reconfigurable components—a key hurdle in industrial automation. Together, these contributions demonstrate Gumma’s impact on the future of Industry 4.0, offering scalable, data-driven solutions that promise to reduce downtime and increase productivity in high-mix, low-volume production environments.
Research Focus
Key Achievements
Top Papers
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