How can and will computer vision transform manufacturing

Computer vision systems can analyse product images in real time to detect defects, inconsistencies, or deviations from specifications.By automating the quality inspection process, manufacturers can ensure that only high-quality products reach the market, reducing rework and increasing customer satisfaction.

1. Product assembly

In the manufacturing sector, computer vision applications play a critical role in production and component assembly. Industry 4.0 automation involves the extensive use of computer vision in production for fully automated product assembly and management. For example, it is well known that approximately 70% of Tesla's assembly process is automated. Computer programs help create 3D models for use in planning and presentations. Computer vision systems follow these blueprints to properly assemble components. Here, computer vision 

systems guide robotic arms and production line workers as needed.

2. Supply chain optimization

Manufacturing facilities can streamline supply chain processes to reduce costs and increase customer satisfaction. Improvements in computer vision have enabled machines to monitor many aspects of the supply chain, in some cases eliminating the need for human supervision. Many manufacturing companies have adopted computer vision applications for use in areas such as warehouse management, inventory management, and improving overall productivity. For example, retail giants like Amazon and Walmart are experimenting with drone inventory monitoring. For example, thanks to real-time processing of video data, empty containers can be identified for appropriate refilling.

3. Lean manufacturing

Lean manufacturing is a manufacturing method that aims to reduce inefficiencies and increase production in the manufacturing sector. The data-driven approach to decision-making and automation through advanced sensing technologies in Industry 4.0 technologies is developing lean processes in business. Industry 4.0 technologies, such as computer vision, are essential for the digitalization of factories. Use cases for computer vision systems in the manufacturing industry include measuring process efficiency, providing analytics to identify defective equipment, and optimising workload for every worker on the factory floor.

4. Identify errors and omissions

Computer vision systems can detect many types of defects, improve image processing, and generate digital defect certificates.

Because of the need for fine-grained defect monitoring systems, manufacturers rarely achieve 100% defect-free product detection rates (e.g., poor threading monitoring). If these defects go undetected after manufacturing is complete or delivered to the customer, production costs increase and buyer dissatisfaction occurs. These risks are far greater than the investment required to implement an artificial intelligence-based computer vision impairment detection system.

Applications based on computer vision collect data from cameras in real time, process it with machine learning algorithms, then use the data to compare against quality standards, detect discrepancies and report them as percentages. This information can be used to identify and resolve problems that arise during manufacturing. This ensures an efficient and error-free manufacturing process. Remember, “the cost of not finding a problem is much greater than the cost of finding it.” Alternatively, investing in a computer vision-based defect detection system may be a financially sound move.

5. 3D vision system

On assembly lines, computer vision inspection systems take on tasks that humans would find difficult. In this scenario, technology is used to create a complete 3D model of the components and connecting pins using high-resolution photos. Computer vision systems take pictures from different angles as parts move through the factory to create 3D models. When these pictures are fed into an AI algorithm, even the slightest threading error or design deviation is immediately revealed. Automotive, electronic circuits, oil and gas, energy and similar manufacturing sectors all gain great reliability from this technology.

6. Predictive maintenance

Products are produced in factories using special machines. As a result of continuous operation, wear and tear of these devices can lead to defects in the final product and financial losses. Deterioration or corrosion of materials occurs more frequently in some manufacturing processes because it occurs under critical temperature and environmental conditions. This causes the machine to bend. Manufacturers hire corrosion experts to monitor equipment condition and develop strategies to prevent corrosion as part of preventative maintenance. Manufacturers continuously and manually monitor all machines. But when it comes to detecting these changes in manufacturing machines, computer vision technology is far superior to human observation. Defects in very small mechanical parts are detected in real time using CV. As a result, malfunctioning components that slow down production are detected in a timely manner and corrected without stopping production. For industrial machinery, deep learning is used for prediction, leak detection, and problem diagnosis. Intelligent fault diagnosis systems are developed using machine learning techniques. Computer vision systems can monitor machines in real time using a wide range of parameters. A computer vision system can alert appropriate managers to perform preventative maintenance if deviations in measurements indicate corrosion.

7. Physical protection and security provisions

Workplace injuries are common among industrial workers. Production is linked to the health and well-being of the workforce, so protecting workers is a top priority for every company. Because it is difficult for one person to observe multiple displays simultaneously, manual monitoring procedures are generally inadequate. When these mistakes occur in a manufacturing organisation, they are likely to have a serious impact on employees and the business. Using computer vision technology, any issues related to employee safety precautions can be quickly identified, reports are generated on dashboards, and alerts are sent. In the event of an accident, an alarm is automatically sent so administrators can take appropriate action without delay. Computer vision systems are used to identify employees wearing protective equipment.

Read Also : Computer Vision Use Cases in the Manufacturing

Conclusion

Companies in the manufacturing sector around the world are enthusiastically adopting the latest technologies. We hope this information sheds light on why computer vision is so important in the industrial sector. Over the years, factories around the world have adopted new methods of mass producing products. Everyone is doing their part to make our products as safe, affordable and efficient as possible. Therefore, there are many benefits to integrating computer vision systems into factories. This method can help you take your manufacturing company to the next level.