BIION-D
Next Gen AI for quality control
Advanced AI to optimize
quality control
In the competitive and dynamic environment of the manufacturing industry, quality control is one of the crucial challenges. Production defects or discrepancies from standards can cause direct cost increases (scrap, rework, returns), loss of customer confidence, damage to corporate reputation.
The key to total control of production
Visiofy‘s BIION-D solution, based on Deep Learning (AI), was specifically designed for the manufacturing SME and provides an ultimate answer to these needs.
It is therefore necessary to provide organizations with tools that are:
- Faster in identifying problems
- More precise in ensuring high standards
- More efficient in optimizing production processes
Indeed, QUALITY CONTROL appears to be high on the list of priorities and investments in smart manufacturing technologies, especially those based on Artificial Intelligence (AI) and Machine and Deep Learning.
It is an end-to-end solution, complete with software, edge computers and interfaces that can be up and running in a matter of days. Thanks to Deep Learning (AI), it does not require collection and cataloging of defect samples, reducing the effort required of the operator.
It is integrated with standard factory protocols and ready for further interfacing. Its intuitive software makes it easy to configure detection parameters and monitor analysis results in real time.
Added values of BIION-D
Increased productivity
- Enables increased profit margin
- Flanks and/or replaces operator on line
- Provides high performance on shifts, up to 24/7
Gaining competitive advantage
- Better management of internal know-how
- Production process optimization and digitalization
- Faster time to market
- Better brand perception
- Better customer relationship and satisfaction
Quality improvement
- Increased efficiency in detecting the smallest defects or anomalies
- Ensures 100% quality control
Cost reduction
- Decreased defective parts, rejects and returns
- Decreased staff time