How smart AI tools can help build better vehicles
2026-05-05
Written by Sara Foss and Mariana Reyes Hernandez
Manufacturing requires precision. From casting parts to metal stamping, each step of the manufacturing process is not only scalable but also customizable for each assembly site.
As vehicles pass through GM manufacturing plants, they undergo a variety of inspections and touchpoints. GM’s factory teams are using new technology, such as machine learning models and AI-driven analytics, to enhance quality checks and make those checks faster and more efficient. Advanced technology and AI analytics on the line not only enable faster decision-making and improved accuracy, but also help realize GM outcomes. better quality for customers.
Here are some examples of how GM is reimagining manufacturing through technology and innovation. Some of these processes have already been recognized through the Boss Kettering Awards, which recognize projects that help shape GM’s future.
Device level analysis (DLA)
DLA is a sensor system that acts as the eyes of the entire plant, monitoring and analyzing how the plant is physically operating. Think about capturing vibration data, electrical current, and information from other sources. The information collected is used to proactively schedule preventive maintenance to eliminate unplanned shutdowns and downtime.
As DLA continues to expand through manufacturing, we leverage machine learning models and AI systems to improve accuracy and flag issues faster.
An example:
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Previously, team members manually checked all vehicles in their group (5,600 total).
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Thanks to the data obtained from DLA, the team pinpointed where the welds were missing, quickly identified which vehicles were affected, and narrowed down the suspects from thousands to fewer than 10.
Photo caption: DLA sensors monitor the conveyors that transport vehicles in the factory. The data is then sent to a command center that flags anything outside of normal ranges and creates a report indicating that repairs may be needed.
welding brain™
Welding is an important step in vehicle assembly. The vehicle skeleton is joined by welding. A quality checkpoint in an auto body shop typically involves one employee physically checking the strength of the weld. There is now technology that can help workers see things that the human eye alone cannot see.
At Factory ZERO, GM is piloting WeldBrAIn™. This is a unique technology to monitor the quality of the production line. This AI-powered system expanded quality checking capabilities from manual inspection of four parts per shift to checking every weld on every body in real-time.
Photo Caption: Workers access the WeldBrAIn™ dashboard to check the quality of welds throughout the vehicle. On the factory floor, the same dashboard is used to directly inspect the vehicle.
paint repair vision system
In GM’s factory paint shop, team members physically check for defects and use their hands to feel for surface imperfections that need to be polished. Although GM’s painting process works to eliminate final paint problems, it can introduce quality issues that are less visible.
An example:
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These “superhuman eyes” can see defects at a microscopic level, enabling faster, more confident decision-making and a better paint finish for your customers.
caption: Vision systems inspect paint quality as vehicles move through the store, detecting and correcting problems invisible to the human eye.
Smart tools like device-level analytics, WeldBrAIn™, and vision systems help GM employees discover issues early, protect quality, and make calls quickly and confidently. This allows GM to consistently deliver high-quality products to customers and enable a culture of safety, ownership, and continuous improvement every shift.
Written by Sara Foss and Mariana Reyes Hernandez
Manufacturing requires precision. From casting parts to metal stamping, each step of the manufacturing process is not only scalable but also customizable for each assembly site.
As vehicles pass through GM manufacturing plants, they undergo a variety of inspections and touchpoints. GM’s factory teams are using new technology, such as machine learning models and AI-driven analytics, to enhance quality checks and make those checks faster and more efficient. Advanced technology and AI analytics on the line not only enable faster decision-making and improved accuracy, but also help GM deliver better quality to customers.
Here are some examples of how GM is reimagining manufacturing through technology and innovation. Some of these processes have already been recognized through the Boss Kettering Awards, which recognize projects that help shape GM’s future.
Device level analysis (DLA)
DLA is a sensor system that acts as the eyes of the entire plant, monitoring and analyzing how the plant is physically operating. Think about capturing vibration data, electrical current, and information from other sources. The information collected is used to proactively schedule preventive maintenance to eliminate unplanned shutdowns and downtime.
As DLA continues to expand through manufacturing, we leverage machine learning models and AI systems to improve accuracy and flag issues faster.
An example:
- In Fort Wayne, the team used plant data to identify and narrow down warranty issues. routine After quality inspection, it was discovered that there was a welding error in the vehicle’s batch.
- Previously, team members manually checked all vehicles in their group (5,600 total).
- Thanks to the data obtained from DLA, the team pinpointed where the welds were missing, quickly identified which vehicles were affected, and narrowed down the suspects from thousands to fewer than 10.
- By leveraging all available data and resources, they made the right decision in hours, not days, and prevented the nine affected vehicles from leaving the building.
DLA sensors monitor the conveyors that transport vehicles within the factory. The data is then sent to a command center that flags anything outside of normal ranges and creates a report indicating that repairs may be needed.
welding brain™
Welding is an important step in vehicle assembly. The vehicle skeleton is joined by welding. A quality checkpoint in an auto body shop typically involves one employee physically checking the strength of the weld. There is now technology that can help workers see things that the human eye alone cannot see.
At Factory ZERO, GM is piloting WeldBrAIn™. This is a unique technology to monitor the quality of the production line. This AI-powered system expanded quality checking capabilities from manual inspection of four parts per shift to checking every weld on every body in real-time.
Workers access the WeldBrAIn™ dashboard to check the quality of welds throughout the vehicle. On the factory floor, the same dashboard is used to directly inspect the vehicle.
paint repair vision system
In GM’s factory paint shop, team members physically check for defects and use their hands to feel for surface imperfections that need to be polished. Although GM’s painting process works to eliminate final paint problems, it can introduce quality issues that are less visible.
An example:
- GM paint shops in Spring Hill and Flint have added Finesse Paint Repair vision cameras to detect paint quality issues as vehicles roll down the line.
- These “superhuman eyes” can see defects at a microscopic level, enabling faster, more confident decision-making and a better paint finish for your customers.
- The tool also provides defect data to GM paint process engineers, providing valuable real-time feedback to help improve and adjust the paint process and prevent defects in the first place.
Vision systems inspect paint quality as vehicles move through the store, detecting and correcting problems invisible to the human eye.
Smart tools like device-level analytics, WeldBrAIn™, and vision systems help GM employees discover issues early, protect quality, and make calls quickly and confidently. This allows GM to consistently deliver high-quality products to customers and enable a culture of safety, ownership, and continuous improvement every shift.
