Quality control is an essential part of every manufacturing business. But it is often a time-consuming and expensive task for your employees to detect any potential product defects, and let's face it, a person’s visual inspection isn't always accurate or precise and can get expensive quickly.
That's where AI-powered (Artificial Intelligence) defect detection comes in. Using machine learning and computer vision, you can automate your quality control process and speed up your production lines.
In this article, we’ll look at defect detection in manufacturing and how you can detect production defects in minutes using AI and PLC integration.
What is Defect Detection?
Your shop floor is already doing it. At its simplest, defect detection is all about ensuring product quality.
Identifying any potential product defects or imperfections is essential in helping you avoid unnecessary operational costs and customer complaints and credits.
In many cases, you have a person or a team taking samples of parts and inspecting them. In some cases, every part may need to go through an inspection. It is a laborious, potentially dull, and repetitive task for a person. Yet, it is essential to your company’s success and your reputation with your customers.
It is also a task that can be automated, freeing up your employees to focus on other areas of your shop floor that generate more value, while also increasing the efficiency and precision of your quality control process.
Machines are designed to make your life easier and your business more efficient. They never get bored, you don’t have to retrain them like you would every time you hire an employee, and their attention to detail never wanes.
How to Detect Production Defects in Minutes
The concept is actually easier than you might think. Using Computer Vision (CV), we can capture images of parts or components, both in a good quality state and in a defective quality state. Those images are loaded into the computer to “teach” it to distinguish between a good part and a defective one.
Providing the computer with multiple images that are analyzed by an algorithm is where machine learning comes into play. By feeding the computer both good and defective products and showing it the difference, the computer builds up a model that it can compare to subsequent parts from a production run.
Once the machine has “learned” to tell good from defective, the visual inspection of parts can then be automated.
During production, each part that comes off the production line passes the Vision AI camera system for automated inspection.
Those images are compared, using AI, to the computer’s database of good and defective parts to determine whether it passes or fails.
By integrating the automated inspection system into the machine controls, failed parts can be automatically ejected to scrap, or a re-check bin, from the line while the approved parts move on. This is the AI at work.
Integrating AI Vision Inspection into Your Production
If your machines have Programmable Logic Controller (PLC) modules, you can also integrate the AI Vision solution into your existing machine technology. If not, work cells and lines can still be augmented with a vision solution.
Depending on your existing automation, your machines are connected to the network through Wi-Fi, ethernet cable, or custom hard wiring.
With integration completed the computer can now receive the data, make the quality assurance inspection, and then inform the machine what to do with the part. This provides a verifiable record of inspection results, including images if needed, that you can use to assure customers of your quality.
As an added benefit, integration opens up many more possibilities. Production engineers can see potential production issues in real-time and make corrections quicker.
The machines can report on their own health and let you know in advance that an unscheduled maintenance issue may be brewing.
Your leadership will have entirely new and more detailed data streams that will allow better inventory control and customer fulfillment.
Is AI-powered Defect Detection Expensive?
The question that you really need to ask is “how much are my current processes costing me in labor and missed or late defect detection?”
Each business will have a unique set of challenges that require a unique solution. In many cases, an off-the-shelf solution exists as a starting point and customization can be kept to a minimum.
Once you do the math, you will very likely find that you can’t afford to ignore a digital defect detection upgrade.
Why Defect Detection Leads to Better Data Which helps Avoid Staffing Shortages& Supply Chain Challenges
Many people still talk about Industry 4.0 as if it’s the future of manufacturing when it’s actually the present.
If you haven’t connected your top floor to your shop floor or considered taking advantage of AI-powered machines, you are already behind the curve. The good news is, AI solutions such as this are more affordable and accessible than ever before.
The future of manufacturing lies in automation and the visibility of real-time data. Implementing AI-powered defect detection into your business is just one of the many examples of value.
Automation also provides a window into supply chain challenges, allowing leadership and staff to better predict, plan for, and mitigate issues before they slow down production or impact customers.
Easy and secure access to data has also resulted in an increase in production for the existing workforce. Achieving more with the people and resources you already have is the biggest step to avoiding staffing shortages.
When you can connect your entire organization together, you position your business to reduce unnecessary overhead, deliver your products more efficiently, and improve your relationships with your customers.
Want to Get Started?
The simplest way is to contact Software Insite. We can begin a conversation that will help you evaluate your current processes and find a path forward.
After reviewing your needs, we start with discovering if an off-the-shelf solution can work for you, and add in only the customization you need to make it work.
We take a holistic approach, too. For you, this means that our experts are going to find other areas where your investment will reap rewards. You won’t come away with only a new quality control process, but also other ways where this technology will easily integrate to improve your bottom line.