Case
Retrofit in the pharmaceutical industry
In the pharmaceutical industry, automated visual inspection (AVI) systems are already industry standard. AVI systems are more consistent, more reliable, and faster than human inspectors. However, in some applications such as vial inspection AVI systems produce up to 20% of false positives (defined as parts that are OK, but misclassified by the AVI system as NOK). This results in annual costs for the industry of up to EUR 750mn.
One typical cause for this misclassification is the presence of water bubbles in the vial (which are ok) that the AVI recognizes as black dots (which are NOK).
Deevio’s AI software can reliably separate water bubbles from black dots and solve this problem while maintaining the false reject rate below 1%. Read more about this case.
SPEED
70 images
PER SECOND
SAVINGS
300.000
EUR
LABELLED
4600 Images
AI MODEL
Classification
What we did
-
Retrofitted an existing AVI system by connecting our AI box to the image acquisition setup for data transfer of up to 70 images per second
-
Labeled OK and NOK images together with the customer's domain experts
-
Developed an AI model that reliably detects NOK parts as NOK parts while reducing the false eject rate to < 1%
-
Our AI software for pharmaceutical inspections is able to generate savings of up to EUR 300.000 annually
If you want to learn more about how we can retrofit your AVI system, please reach out to us and discuss your case.
Case
Retrofit in the packaging industry
Similar to vial production, quality requirements for the pharmaceutical packaging in the pharmaceutical industry are extraordinarily high. Manufacturing companies use machine vision systems to detect defects such as scratches, holes, or deformations. The machine vision systems that are currently used in the industry are good at detecting defects, but at the same time, they have high false rejection rates that result in high costs and waste for manufacturing companies.
AVI SYSTEM
30 images
PER SECOND
SAVINGS
+70.000
EUR
LABELLED
250 Images
AI MODEL
Segmentation
What we did
-
Retrofitted an existing machine vision system by connecting our AI box to the image acquisition setup for data transfer of up to 30 images per second
-
Labelled OK and NOK images together with the customer’s domain experts
-
Developed an AI segmentation model that reliably detects NOK parts as NOK parts while reducing the false eject rate to < 1%
Case
New inspection system in the Die Casting Industry
Our customer is a German aluminum die casting company that produces more than 600.000 engine parts for Tier 1 automotive suppliers every year. The natural variance of the raw materials and the difficulties during the die casting process result in scrap rates between 5-10% with defects such as scratches, blowholes, or excess material.
Thus, the company must perform a 100% visual quality control before products can be shipped to its customers. The company employs two full-time operators per shift in order to perform 100% visual inspection of the product.
CYCLE TIME
30 Seconds
PER PART
SAVINGS
> 80.000
EUR
LABELLED
200 Images
AI MODEL
Segmentation
What we did
-
Defined the appropriate image acquisition setup to capture all the different defects in the images
-
Acquired images of OK and NOK parts and labelled defects with the customer’s domain experts using our dedicated labeling tool
-
Developed an AI segmentation model that can detect all defects and is able to cope with the surface variations of the parts
-
EUR 50.000 annual savings for the customer
Results
In similar customers’ use cases, our AI-based SW has proven accurate and resilient at detecting defects in parts made with other raw materials such as magnesium, steel, and iron.
If you want to learn more about what Deevio can do in the die casting and automotive industry, get in touch with us. Our data scientists would be delighted to talk to you.
Case
New inspection system in the machining industry
Precision tools are an integral part of CNC machines that are used to make critical parts in many industries such as oil and gas, space, and automotive. The quality requirements for precision tools are high, which is why companies still rely on humans to visually inspect every tool manufactured before such a tool is shipped to customers.
Previous attempts to automate this visual inspection task failed due to the small size and the different shapes of defects, such as scratches, broken edges, or dents. Moreover, the high product variety of precision tools makes it hard to effectively deploy traditional rule-based machine vision software which would need to be updated and configured for each type of product.
CYCLE TIME
7 Seconds
PER PART
SAVINGS
> 80.000
EUR
LABELLED
100 Images
AI MODEL
Segmentation
What we did
-
Defined the appropriate image acquisition setup to capture the different defects in the images on a micron-level
-
Defined the industrial an automation setup needed to handle the parts and feed them to the image acquisition system
-
Acquired images of OK and NOK parts of different product variations and labeled defects with the customer’s domain experts using our dedicated labeling tool
-
Developed an AI segmentation model that can detect all defects and works with all different shapes of the precision tools
-
Our system generates savings of > EUR 50.000 annually for the customer
If you want to learn more about what deevio can do in the precision tooling industry, reach out!