Manual inspection has been done for over 100 years.
…but it’s silently costing manufacturers millions. Many manufacturers have already realised why.
Manufacturers are switching to image analysis software at record pace — let’s look at the numbers behind this trend.
What You’ll Learn:
- What Is Traditional Inspection (And Why It Fails)?
- What Is Machine Vision Inspection?
- Machine Vision vs. Traditional Inspection: Comparing Terms
- Why Manufacturers Are Switching To Machine Vision
- Getting Started With Image Analysis Software
What Is Traditional Inspection (And Why It Fails)?
Traditional inspection involves employing staff members to manually inspect parts as they move along a production line.
Employees will look for defects, verify measurements, and flag defective products.
Simple.
…but when breaking down manual inspection it has a number of significant drawbacks that are difficult to overcome:
- Fatigue: Productivity and accuracy declines between 25-40% after hour 1 of inspection.
- Subjectivity: Every inspector is human. Two inspectors will never provide 100% identical results.
- Production Line Speed: Manual inspection is often the bottleneck on production lines.
- Microscopic Defects: Humans are incapable of catching defects consistently when they’re under 0.5mm.
Human inspectors incorrectly pass up to 20-30% of defective products on average. That means almost 3 out of 10 defective products are being sold as perfect.
There’s no telling how many dollars those defects cost manufacturers every year.
What Is Machine Vision Inspection?
Machine vision inspection is the use of computers, cameras, and image analysis software to automatically detect defective parts during manufacturing.
This software processes digital images of products as they move along the production line to verify each part is within specifications.
Machine vision inspection is fast. Machine vision inspection is consistent. Machine vision inspection isn’t affected by fatigue.
Advanced machine vision systems can process dozens, if not hundreds, of parts per minute while detecting surface defects, verifying dimensions, reading barcodes, inspecting product packaging, and more.
And the technology is getting better every year. AI-powered image analysis software learns as it goes, constantly improving its defect detection abilities without any additional programming efforts.
Machine Vision vs. Traditional Inspection: Comparing Terms
Below are some of the key terms to know when researching machine vision vs. traditional inspection and what they actually mean.
Accuracy
Automated inspection technology detects between 97-99.5% of defective products on average. Human inspectors catch roughly 60-80%. Automated inspection technology falsely rejects 3% of good parts. Human inspectors falsely reject between 15-25% of good parts.
Speed
Some modern automated inspection systems can measure components up to six times per second. Manual inspection takes between two to five minutes to verify complex parts.
Consistency
Two different inspectors will not provide 100% identical results. Machines will.
Cost
Inspection may seem inexpensive when only looking at employee wages vs. computer costs. But what about product defects that get shipped to customers? Rework time? Customer returns? Product recalls? Warranty repairs?
When accounting for all the hidden costs of manual inspection, the cost of a machine vision system starts to look cheap in comparison.
Scale
Traditional inspection processes can’t scale without hiring more employees. Automated inspection scales by…well, just automating more of the process.
Why Manufacturers Are Switching To Machine Vision
The machine vision market hit $14.1 billion in revenue in 2024. Analysts expect the market to grow to $26.7 billion by 2033.
Those numbers don’t lie. Manufacturers are ditching traditional inspection methods for machine vision because it works.
A machine vision system implemented by an automotive manufacturer detected 30% more defects while simultaneously cutting inspection time in half. A vision system deployed by a pharmaceutical manufacturer detected defects with 99.5% accuracy — a 10% improvement over their previous manual inspection process.
Machine vision technology doesn’t just improve existing processes by a few percent. These systems transform the way manufacturers do business.
…and most manufacturers don’t realize until it’s too late…
After going digital, manufacturers can continue to reduce their defect rates year-over-year by refining their inspection process. They also receive insights that can be used to improve maintenance schedules and production practices.
Machine vision technology doesn’t just pay for itself. It keeps on giving back.
Other industries that have been rapidly adopting machine vision inspection technology include:
- Automotive: Engine parts, body panels, electrical assemblies.
- Pharmaceuticals: Bottle inspection, labeling verification, contaminants.
- Electronics: PCB inspection, solder joints, component alignment.
- Food & Beverage: Packaging defects, fill levels, labeling accuracy.
Make sense?
Getting Started With Image Analysis Software
Switching to image analysis software is easy. Here are the steps to take to find the right solution for any production line.
Hardware/software combinations like VISIONx, Inc. inspection solutions are customized solutions built from the ground up for inspection applications. There’s no one-size fits-all solution for every manufacturer, so it’s important the solution chosen fits the production environment.
If the solution is checking for surface defects, ensure the camera resolution is high enough to detect the defects being looked for. Software is only useful if it can “see” the defects.
Verifying dimensions along a single axis? Ensure the system has proper lighting. Trying to measure holes? A system with features capable of recognizing cylindrical objects will be needed.
Here’s how to find the right solution for any manufacturing plant:
- Know What Needs to Be Inspected. Surface defects? Dimensions? Labeling? Know what needs to be inspected before searching for solutions.
- Know Where Parts Are Being Lost. Where are defects being shipped to customers? Where is inspection creating bottlenecks on the production line?
- Set Realistic Expectations. What kind of accuracy is needed? How fast does the line need to be inspected? Production line needs should serve as the base requirements.
- Ask For Examples. A reputable supplier should be able to provide case studies showcasing their previous work.
- Plan For Integration. Last but not least, the inspection system needs to integrate with existing MES and ERP software. Make sure it’s capable before purchasing.
Once a solution is in place, benefits will start to appear across the business. Fewer defects reach customers. Less time is spent on rework. Product consistency increases. And new opportunities to improve the process will become visible that weren’t before.
Wrapping It All Up
Let’s take a second to review.
- Manual inspection error rates can range from 20-30%.
- Machine vision inspection averages between 97-99.5% detection accuracy and has false positive rates below 3%.
- The machine vision market reached $14.1B in revenue in 2024 and is projected to grow to $26.7B by 2033.
- Adding machine vision into a production line doesn’t just improve the bottom line by reducing defects. It continues to pay for itself as visibility into the process increases.
- Image analysis software should be tailor made to the production environment.
The benefits of switching to machine vision far outweigh staying stuck in the past. Manufacturers who haven’t switched yet are already behind the curve.
