The first year of our project has concluded, and in this brief interview, we share updates from the Decathlon use case.

Here are insights from our partner:

Can you provide an overview of the status of your use case, highlighting any major milestones or achievements that have been reached after 1 year of the project?

Our focus centers on the current assembly Takt-line, orchestrated by a master PLC overseeing the coordination of automated activities, Robots, AGV, and operator safety. Together, these elements work seamlessly to manufacture substantial aircraft structures.

Particularly thanks to the MASTERLY project’s we are committed to produce an automated solution for handling and lifting large panels. This includes precise placement into the assembly jig, ensuring collision-free processes, controlling swinging, and managing loads to prevent any damage to parts or personnel. The result is enhanced performance and reduced stress during critical operations.

Our primary efforts have involved gathering, describing, sharing, and discussing all aspects related to AERNNOVA’s Case of Use. This comprehensive approach provides essential details for the development of our partners’ tasks. In April, a pivotal meeting was held at our facilities, offering project participants a detailed view of the CoU. Key individuals in production and maintenance were interviewed, providing valuable insights into the real view and complexity of operations.

All these crucial topics are meticulously documented in deliverable1.1 of WP1, ensuring transparency and traceability in our collaborative endeavors.

Can you discuss some of the challenges (if any) encountered during the development of the use case and the corresponding solutions or strategies employed to overcome them?

In the dynamic phase of defining and developing our Case of Use (CoU), we’ve encountered and successfully addressed three key challenges:

Perception of Working Area and Environment:
Navigating a working area filled with various uncontrolled factors such as operators, tools, missing objects, dollys, and overhead cranes posed a challenge. To address this, we are leveraging new technologies supported by AI. These technologies provide real-time information during automated handling and lifting processes, ensuring collision avoidance and securing the overall operation.

Sensorization of Assembly Jig Parts:
Ensuring the required accuracy in the assembly jig demanded sensorization of specific parts. Integrating sensors into panels and tooling faced constraints, requiring removal and precise positioning throughout the process, impacting other assembly activities. We opted for a solution involving strain gauges in various directions, integrated into locating pins. The manufacturing of this specialized device, with sensors incorporated, presented challenges. The developed solution allows the captured loads to feed back into the system, providing control over induced stress on the panel and meeting geometric requirements.

Accurate Panel Positioning for Overhead Crane:
Achieving an accurate position for the panel within the required range proved challenging for an overhead crane designed for heavy loads. To address this, we implemented a flexible vision system supported by AI algorithms, acting on the gripper positioned between the overhead crane and the panel. This ensures fine control of the process, achieving the precise location of the skin within the assembly jig.

If you want to know more about the AERNNOVA use case https://www.masterly-project.eu/use-cases/