Quality Control
We make Smart Manufacturing a Reality
AI is ideally suited to detect and categorize defects. AI models can be trained to differentiate between good and defective units by showing them examples. This enables them to autonomously make an ok/not okay decision for every unit they are shown. They can also learn to categorize defects based on examples.
- Very high accuracy
- 100% inspection even of high-volume products (10,000s of units per hour)
- Runs 24/7 with consistently high accuracy
- Accommodates changing external factors e.g., daily variations of sunlight in the plant
- Performs tasks that are hard to hire for
- Learns quickly if product parameters change without the need to write new code
- Works with more affordable hardware (e.g. cameras) resulting in hardware savings of up to 80%.
- Defect categorization helps with root cause analysis of production issues
- Able to detect novel defect categories
AI is fast, reliable, consistent and cheaper than traditional quality control methods that either rely on human inspection or on expensive and inflexible machine vision systems.
Here are some resources if you want to dig deeper:
Find out how AI makes quality control faster, better and cheaper here.
Use case: Quality Control – Welding Solution
Use case: Control – Class A Surface Defect Detection
Use case: Quality Control – Primary Battery Manufacturing