Artificial Intelligence (AI)

Deep learning that automates factory defect
inspection

Defect Inspection Factory Automation

Conventional Approach

When quality control fails the consequences can be damaging.
Potential fallout can include high-profile recalls, dissatisfied customers, customer loss and a tarnished reputation.
Automated imaging-based analysis using machine vision systems offer manufacturers a certain level of assurance in defect inspection as do manual reviews by trained and qualified inspectors. Yet these safeguards can be inconsistent with some anomalies too difficult to catch making quality failure possible.

Simplified Visual Inspection

Feed image data will be used by NEC RAPID Machine Learning to create its defect inspection engine
which can be utilized by users to inspect defects automatically.

Image analysis requires a huge number of pictures of both good and defective products to be collected for learning by AI,
but collecting images of defective products is no easy matter in the precision manufacturing industry.

AI-based surface inspection algorithm called "One Class" is a new feature of RAPID machine learning that is extremely powerful
for manufacturing inspections. Manufacturers do not need to collect images of defective products.

NEC RAPID Machine Learning's Core Deliverables


Dependable Intelligence
Ready access to reliable insight based on real-time information.

Improved Efficiency
The ability to make meaningful changes that deliver both time and cost savings.

Risk Mitigation
The capability to identify potential issues before they become detrimental situations.

Questions?

Looking for an alternative way to improve quality control efficiency?

Let's Talk

Questions?