How does machine vision play a role in manufacturing?

Let’s examine a working example of machine vision to gain a better understanding of it.In this context, we highlight its use in the most common industrial application: the automatic detection of defective products. The process begins when a sensor detects the presence of an object on the production line and activates a light source that illuminates the area. The camera captures images of bright products at a rate measured in frames per second, or “fps.” In most cases, a digitising device, called a frame grabber, converts the image into a digital output that can be transferred to and stored on a host PC. Special software on the PC compares the image to a predetermined set of criteria to detect defects. If defects are found, the product fails inspection and is physically removed from the assembly line. These vision systems can identify defects in the location, colour, size, or shape of a product or detect the presence or absence of objects in the field of view.

Machine vision applications in manufacturing

Manufacturing companies must use various types of heavy equipment to produce large quantities of goods. Some equipment requires regular monitoring to prevent equipment downtime. Manually inspecting every piece of equipment in a manufacturing facility is time-consuming and expensive. The idea is to fix the device only when it breaks or something goes wrong. However, retrofitting equipment using this technology can have a significant impact on operator productivity, manufacturing quality, and cost.

On the other hand, what if manufacturers could predict how their machines will perform and take proactive steps to prevent breakdowns? Consider a situation where some production processes take place in high temperatures and harsh environments where material degradation and corrosion are prevalent. As a result, the equipment becomes deformed. If not addressed immediately, it can result in significant losses and disruption to the manufacturing process. Machine vision systems can monitor equipment in real time and predict maintenance based on multiple wireless sensors that provide data on a variety of parameters. If deviations from measurements indicate corrosion/heating, the vision system can alert the appropriate supervisor who can take proactive maintenance action.

Manufacturing companies can use machine vision systems to detect defects, cracks, and other defects in physical products. Additionally, when manufacturing products, these systems make it easy to verify accurate and reliable part or component dimensions. Images of objects are captured by a machine vision system. A trained machine vision model compares these photos to acceptable data limits and then passes or rejects the object. Any errors or omissions will be communicated through appropriate notification/warning. Therefore, manufacturers can use machine vision systems to perform automated product inspection and precise quality control to increase customer satisfaction.

By adding advanced capabilities like optical character recognition (OCR), optical barcode recognition (OBR), and intelligent character recognition (ICR) to their machine vision systems, manufacturers may automate the entire scanning process.Such as OCR text on photos. You can search for labels, packaging or documents and check them against our database. This way, products containing incorrect information are automatically identified before they leave the factory, limiting the room for error. This approach can be used to apply information on pharmaceutical packaging, beverage bottle labels, and food packaging information such as allergies or expiration dates.

Machine vision inspection systems are used on production lines to perform tasks that would otherwise be difficult for humans. From there, the system uses high-resolution images to create a complete 3D model of the components and connector pins.

Vision systems use photos captured from different angles as items move through the manufacturing facility to produce three-dimensional (3D) models.These images are combined and fed into an AI algorithm that detects incorrect threading or small deviations in the design. This technology has a high level of reliability in manufacturing industries such as automotive, oil and gas, and electronic circuits.

The most widely used technologies for die cutting in the manufacturing process are rotary die cutting and laser die cutting. Rotaries use hard tooling and steel blades, while lasers use high-speed laser light. Laser die cutting is more precise and difficult to cut hard materials, but rotary cutting can cut any material.

To cut all types of designs, the manufacturing industry uses machine vision systems to make rotary die cutting as precise as laser cutting. After providing the vision system with a design pattern, the system instructs a laser or rotary die cutting machine to make precise cuts.

Read Also : Examples of Using Machine Vision in Manufacturing

Conclusion

Machine vision can transform the efficiency and accuracy of the manufacturing industry with the help of AI and deep learning algorithms. Combining these models with controllers and robotics makes it possible to monitor everything from assembly to logistics in industrial supply chains with minimal human interaction. This eliminates errors arising from manual procedures and allows manufacturers to focus on higher cognitive activities. As a result, machine vision has the potential to transform the business of manufacturing companies/units.