Project Team
Northrop Grumman Corporation (Principal Investigator), Manufacturing Automation Systems (MAS), Ohio State University (OSU)
Background & Technical Challenge
First time quality is not accessible in current high tolerance, large complex robotic coatings applications within the defense and aerospace industries, leading to excessive manual rework, re-programming, and increased product lead time. Currently, there are limited, viable, solutions for coating and finishing of complex geometry parts with closed-loop metrology feedback with agile robotic path planning. The challenge is mapping complex surface geometries (for example: overhangs, vertices, and holes) to ensure surface coverage without overspray onto other surfaces in high-mix, high-variation parts. This overspray causes costly robot programming, commissioning and manual rework when automation fails to ensure quality. Defects include non-conformance coating thickness, orange peel, and runs.
When this happens, additional rework may include manual sanding, which can increase production times by one full day of work or in some cases two full weeks. This work has a high risk of causing damage to the underlying structure and the manual process typically requires worker exposure to hazardous and/or ergonomically challenging positions for extended periods of time.
By pursuing a fully autonomous closed-loop system, this project team addressed the concerns of quality, precision, and efficiency in potentially harmful, wasteful, and time-consuming painting and sanding procedures.
This project titled “Agile Robotic Path Planning for Spray Coating of Complex Geometry” was funded through our 24-01 Technology Core-Funded Project Call and addressed the following Special Topic Areas detailed in the Project Call: Multi-modal inputs for AI robotics in manufacturing, and Virtual Commissioning of Advanced Robotic Systems. Additionally, this project built on previously funded ARM Institute projects (the Collaborative Robotic Process Planning for Surface Treatment of Complex Components Project and Collaborative Robotic Process Planning for Surface Treatment of Complex Components Phase II Project) to leverage lessons learned and best practices and to further emphasize technology transition within the ARM Institute portfolio of technology projects.
Technical Approach
This project resulted in a robotic solution that autonomously generates a path program using the nominal CAD model and paint parameters and can automatically adjust the robot’s path based off the as-built conditions of the parts accounting for in-tolerance variation. The previously funded ARM Institute projects that this team leveraged as a foundation successfully demonstrated human-in-the-loop automated path planning using augmented reality (AR), process simulations, and robotic spray coating systems to adjust spraying coatings on complex aircraft parts. This work showed a key component to be carried into the next step of the development process, which includes the ability to process a wide range of inputs including computer aided designs and human-driven requirements to generate optimized robotic adaptive path planning
The project solution was developed by combining Ohio State University’s open-source robot operating system-industrial agile path planning software with the commercially available Manufacturing Automation Systems (MAS) QCPlus Scan-to-Path software. ARM Member Northrop Grumman acted as the target enduser and tester to ensure production viability.
To help achieve first time quality for robotic coatings systems, this project removed the manual labor that is intertwined within the baseline coatings process to optimize robotic paths and iteratively rework in a closed-loop automation system.
Results
In July 2025, the project team conducted the final demonstration in a production environment using two robotic work cells: one that performing the coating process and the other performing the sanding process. The demonstration showed the full robotic integration of the QC Plus Agile Path Plugin to scan then spray coat the representative article. Additionally, subsequent scans showed areas of high paint thickness or abnormalities, which were then autonomously sanded within tolerance.
The project resulted in a more consistent and accurate solution, resulting in reduced schedule span, labor, and overall reduction in production risks associated with high tolerance warfighter coating applications by accommodating for part-to-part variations.
Specifically, the project resulted in:
- 73% reduction in setup and process time (labor hours)
- 95% reduction in error rate, as measured by the manual inspection versus automated inspection process
- 90% of measurements on the demonstration article met thickness tolerance
Impact
The outputs from this project have industry applications beyond the scope of the project team. Accommodating for part-to-part variations is vital for both defense and commercial applications beyond coating and sanding. This technology can be used not only for initial production, but also for fleet sustainment, as individual aircraft parts will continue to vary further from the legacy CAD models over time. The overarching goal of this project is to not only positively advance manufacturing and sustainment in support of our warfighters, but also lower the barrier to entry of multiple robot integrators. ARM Member MAS is targeting supporting hypersonic manufacturing with this technology, as well as energetics in forging applications. ARM Member Northrop Grumman Corporation is aiming to further advance the outputs from this project for use in a factory environment.
Through the creation of a readily available solution for agile robotic path planning for the spray coating of complex geometry, this project team has made key strides towards solving a pervasive industry problem, particularly for organizations that are members of the ARM Institute with ARM Members able to access the consortium-developed intellectual property (CDIP) from this project and all ARM Institute funded projects.
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The ARM (Advanced Robotics for Manufacturing) Institute is a Manufacturing Innovation Institute (MII) funded by the Office of the Secretary of Defense under Agreement Number W911NF-17-3-0004 and is part of the Manufacturing USA® network. The ARM Institute leverages a unique and robust consortium of 450+ members and partners across industry, academia, and government to make robotics, autonomy, and artificial intelligence more accessible to U.S. manufacturers large and small, train and empower the manufacturing workforce, strengthen our economy and global competitiveness, and elevate national security and resilience. Based in Pittsburgh, PA since 2017, the ARM Institute is leading the way to a future where people & robots work together to respond to our nation’s greatest challenges and to produce the world’s most desired products. For more information, visit https://www.arminstitute.org and follow the ARM Institute on LinkedIn and X.