5 AI Secrets to High-Quality Products & Less Waste

CREDIT:

ROCKWELL AUTOMATION

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

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.”

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.

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.