Computer Vision has become the most popular and benefited several industries over the past decade, especially in the manufacturing industry. Technology is making a significant impact at every stage of the manufacturing process, from using computer vision in warehouses to modern robotics in R&D labs.
These technological advances in the manufacturing field have helped to reduce production defects, improve product quality, increase flexibility, reduce time and cost, and achieve higher productivity.
In this article, I would like to give you an overview of some of the best uses cases of Computer vision in the manufacturing industry.
Predictive Maintenance
In the worst-case situation, parts or equipment malfunction, and production is halted. Any company that relies on physical components should think about keeping the appropriate machinery or equipment in good working order. Predictive maintenance is described as the process of determining when asset management is required utilizing machine learning and IoT. This allows the manufacturer to optimize the lifetime of the equipment and reduce performance.
By utilizing time-series data, machine learning algorithms fine-tunes the Predictive Maintenance system to analyze failure patterns and predict possible issues. When sensors track such parameters as moisture, temperature, or density, these data are collected and processed by a machine learning algorithm. There are several machine learning models that are able to predict equipment failure.
Reading Text and Barcodes
Recognizing and reading barcodes and text is not an easy task to do each and every day. To solve this problem, future factories will witness the growth of modernized computer vision systems and industrial automation. By implementing a computer vision solution, Printed Circuit Boards (PCB) manufacturers can drive the savings of business.
Industries are incorporating Optical Character Recognition (OCR) 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), and Barcode Recognition (OBR), and other image processing technologies to enhance the functionality of existing computer vision systems.
Safety and Security Standards
Employees in the manufacturing business labor in extremely hazardous conditions, putting them at a substantially higher risk of harm. Failure to follow safety and security guidelines can result in serious injury or even death. Even though manufacturing companies have cameras installed to monitor employee movement in the plant to ensure safety standards, it is largely a manual monitoring process where an employee must sit and constantly monitor the video stream. The manual processes are error-prone and this error could result in serious consequences.
An AI-powered computer vision can be an appropriate solution. This application constantly monitors the manufacturing site right from the entry point, into the site, and exit point. Even if there is a minor violation in compliance, the system reports to a respective manager and alerts the employees too. This way, manufacturing companies can ensure their employees adhere to safety and security standards.
Packaging Standards
Counting the number of manufactured components before packaging them in a container is significant in some manufacturing organizations. Manually completing this operation can result in numerous problems. Pharmaceutical and retail products are more prone to this issue. Using a computer vision system to count the number of pieces during the packing process ensures that packaging standards are maintained.
Once the items are properly packed, another use case for computer vision is inspecting any damage on the packaging itself. It’s important that products get to customers safely and in one piece. Damaged packaging risks damage to the product inside. Computer vision systems can proactively divert any damaged packaging before leaving the plant.
Defect Detection
If you are running the production line, you want to produce flawless components or products! Computer vision is the technology that helps businesses acquire this. Productions lines often fail to achieve 100% accuracy while detecting the present or potential defects in the manufacturing processes. These defects can cause a loss to the manufacturers and customers. It can also increase customer dissatisfaction that can prove fatal for the business.
Machine vision is helping manufacturing units to prevent such situations by detecting the macro and micro level defects in the production line. Making investments in computer vision-based defects detection systems can help industries to make their production lines free from any kinds of defects. AI-based computer vision systems can help with cameras and algorithms that can prevent any mishappenings due to defects.
The Way Forward
Manufacturing industries from all over the globe are implementing modern technologies in their processes with an open heart. They all are working to make the manufacturing processes free from risks, unnecessary costs, and energy-efficient. Computer vision is capable of much more than we once thought. At the same time, each of these diverse applications is powered by one powerful technique: Data annotation.
Using professional annotation services can provide Manufacturing AI innovators with a variety of distinct benefits. Professional annotation services, such as TagX, rely on their teams of annotators to ensure that datasets are of high quality. Annotation work can be handled by experienced managers, which relieves AI businesses of this load.
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