As part of Industry 4.0, the next manufacturing revolution, the manufacturing industry has been implementing various automation solutions. As part of industrial automation, the manufacturing industry is adopting various advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), computer vision, robotics, and so on to change the way products are produced. Computer vision, in particular, has taken center stage, revolutionizing various segments of the manufacturing process with intelligent automation solutions.
Automation and Computer Vision Can Transform the Manufacturing Industry
1. Product Assembly
In the manufacturing space, computer vision applications play an important role in product and component assembly. The majority of the manufacturing industry has been implementing computer vision as part of industry 4.0 automation to conduct fully automated product assembly and management processes. It is widely known, for example, that close to 70% of the Tesla manufacturing process is automated. Computer-aided software creates 3D modeling designs. The computer vision system precisely guides the assembly process based on these designs. Computer vision systems constantly monitor and guide the assembly line’s robotic arms and employees.
2. Defect Detection
In the manufacturing industry, computer vision applications play an important role in product and component assembly. The majority of the manufacturing industry has been implementing computer vision as part of industry 4.0 automation to conduct fully automated product assembly and management processes. It is widely known, for example, that close to 70% of the Tesla manufacturing process is automated. Computer-aided software creates 3D modeling designs. The computer vision system precisely guides the assembly process based on these designs. Computer vision systems constantly monitor and guide the assembly line’s robotic arms and employees.
3. 3D Visualization System
A computer vision inspection system is used in a production line to perform tasks that humans find difficult. In this application, the system creates a full 3D model of components and connector pins using high-resolution images.
As components pass through the manufacturing plant, the computer vision system captures images from various angles in order to generate a 3D model. When these images are combined and fed into AI algorithms, they detect any incorrect threading or minor deviations from the design. This technology is widely used in industries such as automotive, electronic circuits, oil and gas, and energy.
4. Computer Vision-Guided Die Cutting
The most widely used technologies for performing die-cutting in the manufacturing process are rotary and laser die cutting. Rotary machines use hard tooling and steel blades, whereas laser machines use high-speed laser light. Even though laser die cutting is more precise, cutting tough materials is difficult, whereas rotary cutting can cut any material.
To cut any type of design, the manufacturing industry can use computer vision systems to perform rotary die cutting that is as precise as laser cutting. Once the design pattern is fed into the computer vision system, the system will direct the die cutting machine, whether laser or rotary, to perform accurate cutting.
5. Predictive Maintenance
Some manufacturing processes take place at high temperatures and in harsh environments, so material degradation or corrosion is common. As a result, the equipment deforms. If not addressed promptly, this can result in significant losses and the halting of the manufacturing process. As a result, manufacturers hire corrosion engineers to ensure machine health and prevent corrosion as part of predictive maintenance. Manufacturers manually monitor their equipment on a continuous basis. Computer vision systems, on the other hand, can continuously monitor the equipment based on a variety of metrics. If any deviation from metrics indicates corrosion, computer vision systems can alert respective managers to perform proactive maintenance activities.
6. Safety and Security Standards
Despite the fact that manufacturing companies have cameras installed to monitor employee movement in the plant in order to ensure safety standards, it is largely a manual monitoring process in which an employee must sit and constantly monitor the video stream. Manual processes are prone to errors, which can have serious consequences. A computer vision powered by AI could be an appropriate solution. This application continuously monitors the manufacturing site from the entry point, through the site, and out the exit point. Even if there is a minor violation of compliance, the system reports it to the appropriate manager and notifies the employees. Manufacturing companies can ensure that their employees follow safety and security standards in this manner.
7. Packaging Standards
It is necessary in some manufacturing companies to count the number of manufactured pieces before packaging them in a container. Manually completing this task can result in numerous errors. This issue is more common in pharmaceutical and retail products. Using a computer vision system to count the number of pieces during the packaging process ensures that packaging standards are followed.
Once the items have been properly packed, another application for computer vision is inspecting the packaging for damage. It is critical that products reach customers safely and intact. Damaged packaging puts the product inside at risk. Computer vision systems can prevent damaged packaging from leaving the plant.
8. Barcode Analysis
Another critical factor is barcode verification. The majority of products have barcodes. The packaging department should double-check the accuracy and legibility of the printed barcodes. Manually cross-checking barcodes on thousands of products takes a significant amount of time and is both error-prone and costly. Computer vision systems can easily verify barcodes and divert any products that have faulty barcodes.
9. Inventory Control
Computer vision systems can assist in stock counting, maintaining inventory status in warehouses, and automating and alerting managers if any material required for manufacturing is in short supply. Computer vision systems can eliminate human errors in stock counting.
Stock is difficult to locate in large warehouses. These systems can assist inventory managers in locating products by using a computer vision system based on barcode data.