Quality Control & Industrial Automation

With AI solutions and sensors, you can achieve seamless testing and documentation of production steps and during acceptance in and out of goods. Optimize production, office, and logistics processes for efficient and scalable manufacturing processes.
Challenges
✕ Traditional quality control is labor-intensive, prone to human error, and inconsistent due to subjective judgments

✕ Complexity and speed of modern production lines can outstrip human capacity for oversight

✕ Detecting subtle or complex quality issues in real-time, resulting in costly recalls and damage to brand reputation
AI Solutions
✦ Integrating with industrial automation systems to enhance precision, consistency, and efficiency in quality control processes

✦ Analyzing images and sensor data in real-time to detect defects, anomalies, and quality deviations with high accuracy

✦ Learning from historical data to improve detection capabilities continuously

enabling proactive identification and rectification of quality issues.

✦ Automation can adapt to changes in production variables

maintaining high-quality standards across diverse and evolving product lines.

Business Impact
↑ Enhanced Product Quality

AI-driven quality control minimizes defects and inconsistencies, ensuring superior product quality.

↑ Increased Efficiency

Automation of quality inspections reduces the need for manual oversight, speeding up production cycles and lowering operational costs.

↑ Reduced waste

Early detection of defects allows for timely corrections, significantly reducing material waste and improving sustainability.

↑ Competitive advantage

Companies that implement AI in quality control and automation can deliver higher-quality products more reliably and cost-effectively, strengthening their market position.

Who is it for?

→ Manufacturing and Production Industries

Any sector that involves production, from automotive to electronics and consumer goods, can benefit from AI-enhanced quality control and automation.

→ Supply chain and logistics

Organizations within the Supply Chain can use AI to ensure the quality of goods through automated inspections and monitoring.

Projekt-Highlights
Project-Highlights
Project highlights
Projekt-Highlights
Projekt-Highlights
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AI for Sustainability Connect

zur KI Park Webseite
A mockup of the eigenmind application
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eigenmind

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AI for Sustainability Connect

The AI Connect for Sustainability programme aims to solve business challenges in the field of sustainability. It presents new AI prototypes developed by AI start-ups. The programme promotes innovative solutions for sustainable business.
to KI Park webseite
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Mappr
Datenableich mit KI

Read Mappr case study
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Netzsch Notify

Software that provides real-time information about machine problems and creates transparency in order to gain important insights from machine data.
Read Netzsch case study