Automate

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SwRI will be exhibiting at Automate, booth no. 5607.

For more than four decades, SwRI has provided expert robotics R&D support across the full spectrum of robot types, markets, and applications, including manipulator integration and application development, custom robot and end effector design and fabrication, human-machine cooperation, and autonomous mobile robots. SwRI curates the Robot Operating System-Industrial (ROS-I) open-source project, which is a global robotics research initiative steered by a consortium. The project creates software capabilities and applications for the industry based on open-source building blocks. Operating as a nonprofit since its foundation in 1947, SwRI works in the public’s best interest and toward the betterment of humanity.

Please join us for the following:

Tuesday, May 13
1:30 p.m. – 2:15 p.m.

“Leveraging Learning Algorithms to Predict Weld Distortion and Residual Stress in Real-Time,” Matt Robinson

In the fabricated structures community, there is a relationship between how the structure is made and how it will perform in service. One of the inherent benefits of automation is the consistency of the fabrication process that robotics afford, such as consistent heat input and process control. Combined with physics-based simulation and thermomechanical analysis structures maybe effectively optimized. However, the consistency that is possible with the application of robotic welding is compromised as the components to be fabricated vary in their shape and how they fit together. This input variation often results in distortion and residual stress profiles that are not intended. Recent developments in machine learning and artificial intelligence enable the understanding of a presented assembly variation and update of the welding plan in near real-time relative to that part condition. These developments would enable the target processes to be optimized and executed as if the physics-based simulation and optimization were computationally feasible. This takes advantage of both new approaches for machine learning based frameworks, as well as the ability to execute at the rate of production, leading to improved operational efficiencies and optimized fabricated products. This talk seeks to share progress in current work that seeks to apply this hybrid physics-based simulation with a novel learning framework that seeks to understand presented articles, how they deviate from plan and update welding plans on the fly to optimize measured distortion and residual stress. The goal is to create a system that may be added to welding systems that enable dynamic planning as presentations and conditions change in the real world, thereby making the upfront simulation work more valuable in the production phase, benefitting structures and shipbuilding fabricators as well as others concerned with as-fabricated quality.

Thursday, May 15
8:30 a.m. – 4:30 p.m.

ROS-Industrial Consortium Americas 2025 Annual Meeting The ROS-Industrial Consortium Americas will host its annual meeting in conjunction with the Automate 2025 show in Detroit. For more information, please visit ROS-Industrial Consortium Americas 2025 Annual Meeting

For more information, please contact Jerry Towler or visit Industrial Robotics & Automation.