Ian Stroud
Papers
2
Total Citations
28
H-Index
2
About
Ian Stroud is a leading researcher at the intersection of advanced manufacturing and sustainable production, with a primary focus on energy-efficient laser welding processes. His work has been instrumental in developing predictive models for remote laser welding, a critical technology for the automotive industry. Stroud’s major contributions include the creation of the first Total Energy Estimation Model for remote laser welding (2013, 17 citations), which addressed the automotive sector’s pressing need to balance productivity with energy savings during equipment selection. He later advanced this work by integrating deep learning approaches (2019, 11 citations) to refine energy consumption predictions, tackling the critical issue that robot companies often only provide average, rather than precise, energy data. By providing robust, data-driven frameworks for evaluating process efficiency, Stroud’s research directly supports the industry’s transition toward more sustainable manufacturing. His work is essential reading for engineers and researchers seeking to optimize both productivity and energy performance in modern assembly lines.
Research Focus
Key Achievements
Top Papers
- 1Total Energy Estimation Model for Remote Laser Welding Process17 citations · 2013
- 2Deep Learning Approach of Energy Estimation Model of Remote Laser Welding11 citations · 2019