MAE graduate student wins best paper award at MSEC 2020

Posted: July 23, 2020
Md Ferdous Alam
Ferdous Alam

Md Ferdous Alam, a graduate student in the department of mechanical and aerospace engineering won the Best Paper Award for the Manufacturing Science and Engineering Conference (MSEC 2020). The conference is The American Society of Mechanical Engineers’ (ASME) premier manufacturing conference.

Alam works with his advisor, MAE professor David Hoelzle, at the Hoelzle Research Lab (HRL) on autonomous manufacturing systems. The paper focuses on Alam and Hoelzle’s work building an autonomous additive manufacturing system that includes a cognitive element which would allow for intelligent online decisions.

To do this, Alam and Hoelzle are experimenting with various machine learning algorithms, with special interest in reinforcement learning. They are then looking into making these algorithms usable in data-expensive applications with complex dynamics.

“In essence, we want to take manufacturing systems, which may require either continual calibration, or have strict performance metrics in which the design space is uncertain and actual manufactured products deviate from the best models, and make sure the manufacturing systems are intelligent so they hit performance specs regardless of these challenges,” Alam said.

For Alam, this award was significant, as it was his first publication from his PhD research.

It is always great to have recognition for your hard work,” said Alam. “I am thankful to my advisor for his continuous support and guidance even when I get stuck in my research. I also love our lab tradition. We often have casual conversations with fellow lab-mates about various research topics which helps us to grow as researchers.”

Alam said he is excited about the possibility for the application of his research.  

Through this paper we introduced the idea and now we want to focus on building a robust framework for autonomous manufacturing system,” said Alam.

Alam hopes that the work he has done will be used as a framework by future researchers and engineers to build their own new and novel products.




Category: Undergraduate