Application
Spark helps to detect 100% of chips on glass containers in the luxury industry
100%
Chipped defects detected
10,000
Bottles inspected per hour. Customer's pace respected.
100%
Spark's adaptability to different bottle formats to be inspected.
Client presentation
Main and historic actor of Cognac, this House has been able to combine tradition and modernity of the 4.0 industry in the production and bottling of its products. Always striving for excellence, the engineers and technicians of this great house have ambitious expectations and objectives, and a rigorous quality defaultery concerning their bottling lines and the container formats they adopt.
Quality at the center of concerns.
This big house bottles its Cognac in glass containers. In this context, checking for chipped glass is a necessity for consumer safety. With high production speeds and important consumer safety constraints, the slightest quality decision error on the bottles has an impact. Alongside this, the existing industrial vision quality control systems are aging and do not easily handle new container formats. In some cases, the historical system discards too many flawless bottles due to light reflections and acceptable imperfections on the glass, causing numerous line stops that are detrimental to the production of the required volumes.
The client's objectives
Detect 100% of chips at the rate
Limit false rejections due to glass reflections or imperfections to 0.5%.
Reduce line stops caused by detection errors (estimated at several dozen stops per day)
Reduce costs related to downtime as well as quality costs (false rejects)
The solution: Spark Multi View
To achieve these objectives, Scortex has implemented its AI-powered automated quality inspection solution with Spark, and has enabled:
The implementation of inspections dedicated to quality specifications for the detection of chips, especially on glass bottle necks.
Rapid adaptation of Spark to changes in glass surface condition and potential false rejects
Flexibility for changes in references and shapes of glass containers through high-performance training of Spark's artificial intelligence
Reduction of false detections compared to the installed solution thanks to greater robustness against reflections.
Premium access to the Customer Success team for on-site deployment of the Spark solution and support for the exploitation of quality data collected by the Spark stations on the production lines.
Access to all data generated by the Spark stations deployed on the production lines via its Web Quality Center platform (real-time quality analysis, inspection report history, root cause analysis).
The Results
100% of defects (chipped) detected
Respect of the client's pace of 10,000 bottles inspected per hour
100% adaptability of the Spark quality control system to the different bottle formats to be inspected.
Seamless integration of Spark into production lines and rapid deployment.
"The Spark solution detects all critical chip defects to the security of our products and limits the number of line stops for cleaning"
Yves, Production Director
Frequent questions
How does our AI-powered automated inspection technology take into account the specific constraints related to the materials and manufacturing processes used in the glass packaging industry?
Our technology is designed to adapt to the specificities of glassware, taking into account the different properties of glass, as well as surface finishes. We have developed specific inspection algorithms and parameters to detect potential defects while considering the characteristics specific to glass packaging production.
How does our solution ensure effective detection of defects in glass packaging while ensuring continuous production flow and waste reduction?
How can our technology be adapted to meet the specific needs of glass packaging manufacturers, such as detecting defects on complex shapes or unique textures?
What tangible operational benefits can glass packaging manufacturers expect from implementing our AI-powered automated inspection technology in their production process?
