Artificial vision systems have become a fundamental tool for quality control within different kinds of industry. One of these systems’ missions is defect detection with artificial vision, which is essential on all production lines. In this post that we prepared at E2M COUTH, we are going to talk about how artificial vision inspection and rejection systems carry out this task.
What does defect detection with artificial vision consist of?
When we say defect detection systems with artificial vision, we mean a process that uses algorithms and image-processing techniques to automatically detect defects in products or materials in an industry. They can do all this by analysing images or videos taken of the objects in real time or during a production stage.
This defect detection process with artificial vision follows these steps:
- Image acquisition: The systems take images or record videos of the objects or products with digital cameras or other image-capture devices.
- Image processing: After this, the images taken undergo a series of pre-processing techniques, such as lighting correction, noise filtering, or contrast improvement, so as to obtain better-quality images and make it easier to detect defects.
- Characteristic extraction: The system extracts relevant characteristics from the images, such as textures, shapes, colours, and edges. It does all this with computer vision algorithms.
- Classification: Defect detection systems with artificial vision use automatic learning algorithms, like neuronal networks or support vector machines. This is all to classify the characteristics extracted as normal or defective. These algorithms are trained previously with a set of labelled data that contain examples of normal and defective objects.
- Decision-making: Lastly, based on the results of the classification, a decision is made as to whether the inspected object is free of defects or an anomaly has been detected. This may entail activating an alarm, rejecting a product, or generating a report for later analysis.
Industrial sectors where defect detection with artificial vision is necessary
Systems devoted to detecting defects with artificial vision can be found in different industrial sectors. These sectors are:
Defect detection with artificial vision is being used in different industrial sectors. This includes parts manufacturing, where it can detect any defect, no matter how small and not visible to the human eye. We also see it in electronic production, for component detection and plate assembly inspection.
In this regard, we also see that they are used in quality control for products like textiles, tyres, glass, plastics, and ceramic. In addition to detecting flaws, these systems also learn from them.
This technology is being used most to detect defects in metal parts. To this end, it combines different lighting and image processing techniques that can detect defects not visible to the naked eye. These defects include cracks, pores, or holes that can affect the quality and durability of the end product. What is more, these imperfections can be detected much faster and more precisely than with human visual inspection.
The use of defect detection systems with artificial vision is also growing in the food sector. They are very useful in quality and safety inspections for mass food production. One example would be that they detect foreign particles in liquid or packaged foods, hair in meat, and broken eggs in a box. With the inspection systems we have at E2M COUTH, they can detect the proper level for liquids or products in a container. These systems can also verify labelling and other tasks.
This way, you can guarantee at the plant that the product is high quality and meets all necessary safety standards. Additionally, using these systems can increase productivity, since it saves time on manual food inspection.
How do defect detection systems with artificial vision work?
Artificial vision systems that are designed to detect defects must draw support from certain elements to work correctly. We will tell you what these elements are:
The lighting system is essential for a defect detection system with artificial vision to work. Good lighting allows the camera to capture clear, sharp images, which leads to greater precision in defect detection. It is important that lighting adapt to each case’s specific conditions, since there may be external factors that affect the quality of the images taken.
Selection of the right vision camera is fundamental to ensure that the defect detection system works correctly. You must select a camera with the right resolution and capture speed to correctly identify defects. You must also take other factors into account, like lens size, focal distance, and orientation to make the system more effective.
Image processing is an essential part of operation for a defect detection system with artificial vision. The images taken by the camera must be processed so that they can identify defects with different techniques. Digital processing algorithms are applied to detect, classify, and segment objects of interest in the image and eliminate undesired elements.
Identifying and marking defects
Once the images have been processed, defects must be identified and marked. To identify defects, the patterns in the image are compared with pre-established patterns created beforehand. The purpose of marking defects in the product is so that the machine can easily identify them in case they need to be eliminated.
Discover the advantages of defect detection systems with artificial vision
As we already mentioned throughout this post, artificial vision systems are increasingly present in many different kinds of industries. For this reason, we are going to show you the different benefits of having these systems to detect all kinds of flaws:
Precision and reliability
Algorithms for defect detection with artificial vision are designed to be highly precise in defect detection. They are even able to identify the smallest or most subtle defects that may go unnoticed in manual inspections. This leads to greater reliability in flaw detection and reduces the risk of defective products reaching the market.
Artificial vision provides fast, automatic product inspection. Vision systems can analyse images or video in real time, which accelerates the inspection process in comparison with manual methods, which may be slower and more prone to error.
Detecting defects with artificial vision can help to reduce costs associated with manpower and doing later work. By automating the inspection process, you eliminate human error and the need to hire and train manual inspectors. What is more, by detecting defects early, you avoid additional costs associated with the production of defective products.
Flexibility and adaptability
Artificial vision systems are highly flexible and can adapt to different kinds of products and defects. They can be set to detect multiple kinds of defects and easy adapt to changes in inspection requirements. This makes them ideal for manufacturing settings that produce a wide range of products, ensuring that each and every one of the items that leaves the plant is of excellent quality.
Artificial vision provides inspections in real time during the production process. This means that defects can be detected and corrected immediately, which reduces inactivity time and waste. Moreover, the ability to constantly monitor helps to identify quality problems and improve manufacturing processes. There will be no pauses of any kind on your production line because a product is defective.
Registration and traceability
Artificial vision systems can capture and store images or videos of inspected products. This provides a visual log of the product’s quality and facilitates traceability in the event of complaints or quality issues later on. In this regard, since you can check how it was when it left the plant, you can determine whether the defect came from the place of origin or occurred during the time it was travelling to reach the client.
Non-destructive inspection capacity
Artificial vision inspects products without damaging them. This is especially important in sectors like electronics or medicine, where products are sensitive, and any damage could be costly or jeopardise their operation. This way, you can guarantee the utmost quality for certain products that can be very sensitive during handling.
Scalability and adaptability
Defect detection systems with artificial vision are highly scalable and can be adapted to different production volumes. From small operations to large production lines, artificial vision technology can be used and adjusted to meet each case’s specific needs.
What is the future of defect detection with artificial vision?
With all the aforementioned, defect detection systems with artificial vision have become an essential part of all industries that want to be competitive today. For this reason, some of the future challenges this technology will face are leaning toward improving capacity to detect and correct different defects in the production process.
All these innovations are focused on adding new artificial intelligence and deep learning features, with the aim of improving detection speed and precision. Some innovations are development of object recognition algorithms so that the system can differentiate between similar objects and detect specific patterns with greater precision.
Moreover, predictive analysis techniques are being used more and more to improve systems’ ability to anticipate and correct defects. Another important innovation is the incorporation of deep neural networks in artificial vision systems. The purpose of these networks is to improve the limitation of human abilities in visual processing. With these techniques, systems can identify, classify, and correct defects with greater speed and precision.
Get the best artificial vision systems at E2M COUTH
As you have seen throughout this post, defect detection systems with artificial vision, also known as rejection systems, are a key part in all kinds of industries. They are able to detect any kind of flaw or anomaly in the product or part to remove it from the production line and keep it from reaching the client.
At E2M COUTH, we also have different kinds of artificial vision systems with a wide variety of vision types. These include systems that orient containers and products, that mark, that inspect and, as mentioned, that reject defective products.
At this point if you would like to learn more, if you would like to get one of these systems, or if you have any more questions, please contact us and we will be delighted to help you.