Artificial vision systems are presented as an opportunity to optimize quality and detect errors in your manufacturing processes. This technology employs the use of cameras and image detection sensors. Next, we present some benefits of artificial vision in manufacturing serial parts. The following functions characterize an image analysis system:
- Identifying defects with a high level of precision
- Controlling product quality in real-time
- Easy and fast adaptability to any system
- Automatization of the inspection process to reduce resources
Elaborating on a good product without deteriorating quality is possible using the appropriate optimization methods. In this publication, we will delve into industry 4.0 systems. In the same way, you will know its various applications in the manufacturing industry.
Artificial Vision and quality control in Manufacturing
In quality control, consistency will be the key to the entire process. But, many times, this depends on the criteria of the operator. Machine vision systems collect information, process, and identify possible production errors. This methodology allows you to make better decisions, adjusted to the quality standards of your product.
Vision technology applies computer vision systems to establish objective criteria. In this way, it is guaranteed that your product will always have the same quality. Due to their great capacity for adaptability, they even allow the incorporation of new functions to improve the production process.
If you have a vision system, it will be effortless to identify the imperfections of a product. Integrating artificial vision into your production system will allow you to: verify the dimensions of a product and confirm if they have the proper shape. For any alteration that affects the production line, the system will throw an alert notifying the machine operator.
Artificial Vision and Industry 4.0
Companies seek better results daily thanks to advanced production processes and intelligent technologies. Industry 4.0 makes use of technologies such as:
- Cognitive technologies
- Artificial vision
- Nanotechnology
- Robotics
- Artificial intelligence
These advanced technologies allow for a continuous flow of information. The data collected serves as a guide to provide criteria and better decisions. These decisions will cause fundamental changes to production problems to be generated.
Traceability allows correct control of product labeling. Through data transmission, artificial vision associates a product with its respective label. This technology guarantees a proper labeling process. In addition, it allows reading printed characters at high speed, such as barcodes and images.
Machine vision and industrial automation
Carrying out tasks faster and more accurately is only possible through artificial vision. Industrial automation allows the production of many products at the best possible time. Now, what happens when we send the customer a defective product? This mishap will generate:
- Reputational crisis
- Ioss of money
- Loss of raw material
- Increase in expenses
Industrial automation improves when it can detect errors and solve them. None of this would be possible without integrating an artificial vision system. This system collects and analyzes data. This sets a precedent and takes the necessary corrective measures so that the same problems do not occur again.
Cameras and intelligent vision devices are involved in improving quality control and traceability procedures. These improvements help to reduce costs, streamline processes and deliver a product of optimum quality.
Artificial intelligence and machine vision technology
Artificial intelligence technology and computer vision combine to predict the quality of a product. By identifying the elements that affect quality, you can improve the accuracy and efficiency of the production line.
One of the most common errors in manual processes is the classification of the product. As there is no uniformity, it isn’t easy to establish an objective criterion. Computer vision can train an artificial intelligence system to classify a product based on its database.
Artificial intelligence also optimizes production processes. Data collection and machine learning technology allow understanding of the production line. This tool analyzes mistakes and learns from them to improve the process.
Conclusion
Machine vision for quality control in the manufacturing industry continues to evolve and improve each process. On the one hand, it takes control of all production. Inspection and prevention determine which variables are not consistent with the production line. This detail will help to produce a product with uniform characteristics and properties.
There are various applications of artificial vision in the manufacturing process. But we consider fundamental the adaptability that this technology has to any project. If we want the system to adapt to your production needs, you must instruct and program it based on your objectives.
Optimize your production with artificial vision systems
Customers seek the best of your products. Many of them are disappointed when they discover imperfections. This generates dissatisfaction, return of the merchandise, and in the worst case, the definitive separation from your company.
Why risk running manual verification methods when you have practical technological tools? At AMN Quality Solutions, we understand that quality control processes cannot be taken lightly. That is why we offer you innovative solutions adapted to your company’s needs. Contact us now!
