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5 AI Secrets to High-Quality Products & Less Waste

See what you've been missing with AI machine learning tools for vision inspection.

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Pallets of stacked products on a factory assembly line are being scanned with an AI artificial intelligence vision inspection camera, FactoryTalk Analytics VisionAI

Quality control methods differ by industry and are specific to each manufacturer and product. But when it comes to actual product inspections, most manufacturing quality processes look similar. Trained inspectors visually evaluate each unit and decide to pass or fail it.

Of course, people are efficient at their work. But we’re also prone to making unintended errors, getting fatigued or distracted when performing repetitive tasks. Plus, we take breaks, go on vacation and even retire.  

So, manufacturers have been automating quality control processes and augmenting inspectors with cameras, lighting and machine vision systems for decades. While many machine enhancements improve inspection speed and volume, their capabilities may be limited.

As result, manufacturers are seeking the next level of artificial intelligence (AI) and machine learning tools – such as FactoryTalk® Analytics™ VisionAI™ – to improve their quality inspection process.

Carl Lewis, Senior Product Manager at Rockwell Automation explains, “Our AI-driven quality control solution lets manufacturers see what they’ve been missing. We’ve built a no-code approach to vision inspection to improve quality, maximize yield and gain critical insight from real-time production data.” The AI vision inspection system provides data that translates directly into helping produce better quality products. Lewis says, “It helps manufacturers reduce product defects and waste, production downtime and operating costs.”

This new generation of AI-driven visual inspection and machine learning system can learn and dynamically adapt to changing conditions, plus gather, organize and communicate quality data 24-7.

The data helps quality personnel and plant operators quickly understand and address production issues. “The impact can be significant,” says Lewis. “The system helps identify automotive assembly line defects to consumer product defects that could lead to recall issues. And there are countless industrial use cases – from identifying dimensional defects, packaging anomalies or other quality issues before they leave your facility. This AI and machine learning vision inspection tool delivers tremendous value.”

5 Top Benefits to AI & Machine Learning Inspection Systems

  1. AI Learns Like a Human, But Never Gets Tired: AI machine learning vision tools provide continuous defect detection 24-7. AI algorithms can detect defects and inconsistencies with higher precision than manual inspections. AI inspection systems monitor production processes in real-time, allowing for fast identification and correction of issues, minimizing waste and helping prevent downstream consequences.
  2. Find the Smallest Flaws and Defects: Machine vision provides greater inspection accuracy. Automated inspection solutions perform tasks the same way, every time. AI vision systems can find the smallest flaws, spot new defects with anomaly detection and evaluate items against extremely tight tolerances.
  3. Get Data at Your Fingertips: Manufacturers can receive real-time production reports, accessible anytime, from anywhere‍. Cloud-connected visual inspection systems add traceability and transparency to the entire production process. They can even provide an audit trail to address disputes or minimize waste in the event of a recall‍.
  4. AI Delivers Measurable Return on Investment: Get fast time to value. Cloud-based visual inspection solutions are quick to set up, configure and update. They can be repurposed around the manufacturing floor in a matter of hours. They also free up personnel to perform higher-value tasks, making employees more efficient.
  5. Save Operational Costs: The data gathered from automated inspections can provide valuable insights to all manufacturing teams, addressing process improvement. Plus, the solutions help reduce defects, waste and recalls – translating to significant cost savings.

The new generation of AI-powered technologies improves the inspection process and makes it faster and better. For manufacturers, this helps translate into higher yields, better quality, less downtime, less waste and ultimately – higher profits.

To learn more about implementing a next-gen AI-powered visual inspection system, visit FactoryTalk Analytics VisionAI.

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What is the Artificial Intelligence (AI) vs. Machine Learning Difference?

Artificial intelligence (AI) and machine learning are not the same thing, but they are closely connected. Here is the AI vs. machine learning difference:

  • AI is the broad concept of using a machine or system to sense, learn, reason, interact or adapt like a human.
  • Machine learning applies AI to a machine to extract knowledge from the machine’s data and then learns from it.

By combining AI and machine learning to quality control inspection tools, manufacturers automate vision inspection tasks and generate real-time data to improve product quality, production rates and profits.

Published April 23, 2025

Topics: Optimize Production Data Science & Industrial Analytics Artificial intelligence Digital Transformation Production Operations Management Household & Personal Care Food & Beverage Automotive & Tire FactoryTalk Analytics

Carl Lewis
Carl Lewis
Senior Product Manager, Rockwell Automation
Carl specializes in AI and machine vision technologies. He drives the development and commercialization of intelligent vision solutions that power industrial automation. With over 25 years of experience in AI, cloud-enabled automation and manufacturing systems, he brings a strategic and technical lens to product leadership.
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