Manufacturing more efficiently

Local AI can maximize throughput and increase safety in manufacturing processes

Edge AI use cases in industries are wide ranging, from quality control in manufacturing lines to safety monitoring of human-machine interaction. These applications need fast, low latency inference without compromising on accuracy.

20% of leading manufacturers will rely on embedded intelligence by 2021. AI, IoT and blockchain applications are expected to increase execution times by up to 25%.
Source: IDC


Imagine spotting defects the human eye can’t see.

Quality control in manufacturing can be complex, especially where high precision is needed. Components defects are difficult or impossible for human eyes to see, which makes the error rate on this type of inspection very high.

Missing defects can be costly and industries are deploying local AI at a rapid pace. Coral can enable visual inspection systems that can detect faults with high accuracy in situations where human vision falls short.

See how LG implements quality control with Coral

Imagine extending the operating life of expensive machines.

Downtime of a production line or critical machine can lead to slower production, costly repairs, or even catastrophic failure.

With Coral, equipment manufacturers can incorporate features that monitor and analyze machine behavior and warn of impending failures. That can inform a system of predictive maintenance to avoid expensive downtime.

See how Olea Edge helps municipal water utilities predict meter failure

Imagine a worksite that can see accidents before they happen.

Many worksite injuries are due to preventable accidents — workers falling, failing to see heavy equipment, or failing to be seen by machinery.

Using Coral enabled cameras and other local sensors monitoring a job site, operators can give robots and vehicles the ability to operate safely alongside human workers, preventing collisions and making collaborative work with machines a reality.

Incident and avoidance data pooled into predictive models allow site managers to anticipate activities that may prove dangerous and make process changes.