Denis Daniel Stoerkle
Papers
1
Total Citations
7
H-Index
1
About
Denis Daniel Stoerkle is a researcher at the forefront of advanced manufacturing, with a primary focus on incremental sheet forming and the integration of machine learning into robotic production processes. His most-cited work, "Machine Learning In Incremental Sheet Forming" (2016, 7 citations), introduces a novel methodology to enhance geometric accuracy in the ROBOFORMING process—a robot-based approach designed for producing sheet metal components in small lot sizes and prototypes. By leveraging two cooperating industrial robots, Stoerkle’s research addresses a critical challenge in flexible manufacturing: achieving high precision without the need for costly, dedicated tooling. This contribution is particularly impactful for industries requiring rapid prototyping and low-volume production, such as aerospace and automotive. While his citation count reflects a specialized niche, the practical significance of his work lies in bridging the gap between machine learning and real-world forming operations. Stoerkle’s achievements underscore a commitment to making robotic forming more reliable and efficient, positioning him as a key innovator in the evolution of smart manufacturing technologies.
Research Focus
Key Achievements
Top Papers
- 1Machine Learning In Incremental Sheet Forming7 citations · 2016