Application
Spark divides by 3 the scrap rate of an automotive parts manufacturer
100%
defects presence / absence and poorly placed joints detected
100%
of automated quality control
1/3
Reject rate divided by 3
Client presentation
Tier 1 supplier of plastic parts and assemblies for the automotive industry, our client is a French company with several production sites in Europe. It is recognized for its expertise in plastic injection for high-stress applications in vehicles.
Quality at the center of concerns.
As in most production companies in the automotive sector, quality inspection for our client was mostly manual.
The client had a rejection rate varying between 5% and 10% for the detection of material shortages, presence/absence of components, and the correct placement of seals. This generated defects that were more complex to detect at the pace for line operators and consequently led to customer complaints about non-conformities.
The client's objectives
Switching from manual sampling quality control to 100% automated control
Reducing outgoing non-quality and customer claims
Maintaining autonomy in managing its industrializations
Inspecting at pace

The solution: Spark Multi View
To achieve these goals, Scortex has implemented its AI-powered automated quality inspection solution with Spark, and has enabled:
Automation of quality inspection on production lines
Flexibility for changes in references and produced series through Spark's high-performance AI training
Elimination of false detections through Spark's AI adaptability, taking into account user feedback
Implementation of an alert system for consecutive defect detection to stop production in case of drift
Access to all data generated by the Spark stations deployed on production lines via its Web Quality Center platform (real-time quality analysis, inspection report history, root cause analysis)
Including sequential review of categorized defective part images and temporal correlation with production tools used on the line
Defective tools were detected through process drift and the defects they induced
Their repair or replacement has reduced the scrap rate
The Results
100% of automated quality control
100% of defects presence/absence and poorly placed joints detected
Use of quality data generated by the Spark Web Quality Center platform to divide the rejection rate by 3
Detection of all defects to reduce customer complaints and deliver a compliant finished product.
Integration of Spark into continuous improvement processes.
"We gained 5 points on the scrap rate thanks to Spark"
Ibrahim, Engineer continuous improvement
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Frequent questions
How is our AI-powered automated inspection technology tailored to the specific requirements of machining metal parts for the automotive industry?
What are the features of our solution that enable the effective detection of defects in machined metal parts while maintaining optimal production times?
How does our solution ensure compliance with the strictest quality and safety standards in the automotive industry when inspecting machined metal parts?
How can our technology help reduce manufacturing costs and waste in the machining process of metal parts for the automotive industry?
What competitive advantages can automotive manufacturers expect from implementing our AI-driven automated inspection technology in their process of producing machined metal parts?