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Manufacturers are already changing how products are produced, leaning towards automated processes and incorporating cutting-edge technologies like AI. One of the areas with the most potential for leveraging AI automation solutions is Computer Vision (CV). CV is a field of Artificial Intelligence that trains computers to understand and analyze the visual environment. By using digital images and training through the method of “learning,” the system can more precisely recognize and categorize objects or information and respond accordingly.

Use cases of computer vision in manufacturing

There are several ways how manufacturers can employ computer vision within the enterprise to generate tangible benefits. Computer vision can be used for product quality assurance, automation, failure predictions, and safety. The purpose of computer vision-powered technology will vary greatly depending on the project, manufacturing space and limitations, and many other factors. As a rule, manufacturers do not implement such technologies in-house and turn to computer vision development services instead, to successfully incorporate computer vision in their specific manufacturing workflow. Below are some of the most common ways in which computer vision is applied within manufacturing. 


  • Ensuring  a safer environment 

The pre-programmed computer vision algorithms allow for quick object detection, which aims to improve the safety of workers and boost their productivity in the workspace. For instance, computer vision can check if safety equipment on the manufacturing floor is properly maintained and make sure that employees are using protective gear like helmets and safety glasses. Because computer vision can be deployed 24/7 it will assist manufacturing employees on the shop floor or in other departments to carry out their duties efficiently. If the system senses any deviation from the norm, it sends real-time alerts to security officials.

  • Securing the plant perimeter

Computer vision can also be used to secure areas that are dangerous for humans to be in. The automated algorithms of computer vision promote both employee safety and quality control. How? Computer vision-powered cameras can monitor employees and plant perimeter and alert in case of a hazardous situation. This can boost employee productivity, maintain quality control, and improve security for manufacturing companies.

Quality assurance 

Computer vision algorithms are flexible and can be tailored to meet specific needs, making it a useful tool for quality assurance. It is often used for detecting defective products, because computer vision can spot even the subtle inconsistencies in the quality of products and remove defective products, making the entire process more efficient. 

  • Deep learning for quality assurance 

It was tested with different AI algorithms, including YOLOv3, Faster-RCNN, FPN, and a single-shot detector (SSD) neural network. Compared to machine vision, deep learning is much more robust and flexible, making hardware less costly.

  • 3D vision systems for defect detection

A computer vision inspection system is used in a production line to carry out responsibilities that humans struggle with. The system uses high-resolution images to build a full 3D model of components and their connector pins. As components run through the manufacturing plant, the computer vision system captures various images from different angles to generate a 3D model. These images, when combined and fed to AI algorithms, identify any faulty threading or minor deviation from the design. This technology is very credible in manufacturing industries like automotive, electronic circuits, oil and gas, energy, and so on.

Predictive Maintenance

Predictive Maintenance is the process of using machine learning and IoT to assess when asset management is needed. This allows the manufacturer to optimize the lifetime of the equipment and reduce performance. For example, an industrial supplier manufacturer developed a software program that gathered photos from cameras connected to 7000 robots in 38 smart factory factories. Together with the metadata, this image collection can detect and prevent 72 component failures.

Package Inspection

A computer vision-based inspection system can be your eyes and hands in the production chain. If any detail is found to be defective, the system sends a signal to reject it at the last stage of packaging. The computer vision-powered system can investigate whether the details are the right color, size, width, and length. The main goal is to remove the possibility of producing defective goods.

Reading Text and Barcodes

Due to Natural Language Processing (NLP) and Optical Character Recognition (OCR) computer vision solutions can recognize and read barcodes and text. Industries are incorporating technology to make real-time data in the image machine useful and readable. Hardware or software vendors are implementing advanced text recognition technologies increasingly, such as Optical Mark Recognition (OMR), Intelligent Character Recognition (ICR), Barcode Recognition (OBR), and other image processing technologies to enhance the functionality of existing computer vision systems.

Ways Computer Vision Can Transform Manufacturing Industry with Automation

Computer vision has revolutionized various segments of the manufacturing process with its intelligent automation solutions. By incorporating advanced technologies such as AI, computer vision enables manufacturers to automate repetitive tasks, allowing manufacturers to optimize their operations, increase efficiency, and reduce costs. 

Product Assembly

The widespread adoption of computer vision in the manufacturing sector has facilitated the automation of many aspects of product assembly and management. 3D modeling designs are created through computer-aided software, and these designs serve as a guide for the assembly process. The computer vision system uses these designs to direct the assembly with great precision. The system constantly monitors and directs the robotic arms and human workers in the assembly line. This combination of automation and human workers allows for a more efficient, accurate, and cost-effective production process. By implementing computer vision, the manufacturing industry has been able to significantly streamline its operations and achieve greater results.

Inventory Management

Computer vision systems are indeed helpful in managing warehouse inventory and ensuring that the manufacturing process runs smoothly. They are able to accurately count stocks, keep track of inventory levels, and alert managers if there is a shortage of any necessary materials. This eliminates the risk of human error in stock counting and ensures that the inventory is always at optimal levels. Furthermore, computer vision systems based on barcode data can help inventory managers quickly locate products within the warehouse. By automating these processes, computer vision systems can reduce the workload of inventory managers, increase efficiency, and minimize the risk of errors and stock shortages. 


Machine vision is being integrated into manufacturing processes to enhance their development and detect opportunities for improvement. The image-processing technology that allows for automated scanning and object detection has proven to be highly valuable for the manufacturing sector. Factories are installing cameras on their production lines or cells to monitor processes in real time, inspect products, sort items, and guide robots.

As machine vision systems continue to decrease in size and increase in speed, accuracy, and resolution, their popularity is expected to grow significantly in the coming years due to the increasing demand for efficient and effective industrial processes.