Fargo, ND, United States of America

Md Atikur Rahman

This inventor holds 1 USPTO granted patent. Top assignee: Ndsu-Research Foundation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Md Atikur Rahman. Retrieved from https://idiyas.com/inventor/md-atikur-rahman

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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Average Co-Inventor Count = 1.0

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Md Atikur Rahman and AI-Enabled Additive Manufacturing

Introduction

Md Atikur Rahman is an inventor based in Fargo, North Dakota. His work includes an invention that combines additive manufacturing with artificial intelligence to improve the reliability and quality of 3D-printed parts.

Latest Patents

Rahman is associated with 1 patent, titled “Additive Manufacturing System Incorporated with Artificial Intelligence.” The technology addresses challenges in commercial additive manufacturing, including undetected print failures, limited printing parameters, low fiber volume fractions, and poor interlaminar adhesion.

The system incorporates applicator engineering, elevated-temperature control, and real-time monitoring to help improve adhesion and reduce dimensional errors associated with post-curing. It also uses ultrasonic vibration to disperse resin more effectively and reduce voids in printed parts. By detecting and mitigating print failures, the approach aims to save time and material while improving printing efficiency and the mechanical properties of printed products.

Career Highlights

Rahman is associated with the NDSU Research Foundation. His patent describes an approach to improving additive manufacturing through process monitoring and material-control techniques.

Collaborations

Rahman’s listed coworkers include Chad Ulven and Md Zahirul Islam.

Conclusion

Md Atikur Rahman’s patented work brings together artificial intelligence, monitoring, and manufacturing-process improvements to address print failures and enhance the quality of additively manufactured parts.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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