The manufacturing industry has been adopting various automation solutions as part of Industry 4.0, the next revolution in manufacturing. To change the way products are produced, 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 etc in. Specifically, artificial vision has taken center stage and has revolutionized various segments of the manufacturing process with its intelligent automation solutions.
Benefits:
Implement automated quality control to increase manufacturing accuracy, improve productivity, and produce better quality
Implementation of monitoring solutions to reduce inspection time, minimize safety risks, improve operator productivity and increase profitability
Reduce human involvement to protect workers from hazardous environments
Examples of the use of machine vision in manufacturing
Additive Manufacturing
The manufacturing process that builds 3D objects by adding layers of material is known as additive manufacturing regardless of the type of substance.
Computer vision additive manufacturing is the use of a computer, 3D modeling software (computer-aided design or CAD), and machine vision to combine layer machine output data with visual input data to accurately reproduce design.
Predictive Maintenance
Predictive maintenance is critical for businesses that rely on machinery to assemble physical components or provide services.
Thus, computer vision in manufacturing is the system by which machine learning and IoT devices monitor incoming data from machinery and sometimes individual components through sensors. Sensors identify signals that trigger alerts informing you to take corrective action before an asset is completely lost or an accident occurs.
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Package Inspection
Sometimes it is imperative that pharmaceutical companies count the number of tablets and capsules that go into any form of packaging. Computer vision for quality control in automated manufacturing systems can significantly assist in this task by checking for broken or partially formed tablets. As the medicine moves down the production line, photographs are taken and transferred to a dedicated computer that processes the image using a set of established algorithms designed to check whether the tablets are the correct colour, dimensions and shape.
Reading Barcodes
It is difficult for humans on their own to identify, understand and process barcodes on the scale we use in our daily lives. Every trip to the supermarket adds to this count. The human eye cannot achieve the level of precision that an automated system could achieve. For speed, you'll need to use machine learning in conjunction with computer vision to analyze barcodes.
Product and Components Assembly
High-volume, precision product manufacturing plants must ensure that products and components coming off the assembly/production line meet strict quality and safety guidelines set by the regulatory authority. Computer Vision-based systems help companies ensure their products and components are assembled to standard.
Defect Reduction
Companies justifiably want the components that come off their production line to be error free. Achieving this at any significant scale can present several problems for manual efforts. Computer vision, on the other hand, is the ideal technology to help companies automate a solution to this problem.
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Improving Safety
Machine vision is not just limited to production lines in manufacturing plants. Machine vision is also used in more diverse environments, such as mines and large-scale construction.
A combination of real-time live streaming from cameras and video analytics algorithms allows equipment to run with greater efficiency and enhanced security. The idea is to use AI based on deep learning to track the movement of people and predict where the machines will be to avoid dangerous interactions.
Machine Vision Guided Die Cutting
Rotary and laser die-cutting are the most adopted technologies to perform die-cutting in the manufacturing process. The rotary uses steel blades and hard tools, while the laser uses high-speed laser light. Although laser die cutting is more precise, cutting hard materials is challenging and rotary cutting can be used to cut any material.
The manufacturing industry can implement computer vision systems to make rotary dies to be as precise as laser cutting to cut any type of design.
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Inventory management
Computer vision systems can help count stocks, maintain inventory status in warehouses, and automate and alert managers if any material required for manufacturing falls short of demand. Computer vision systems can prevent human error in stock counting.
Conclusion
Computer vision is by no means a nascent concept. The idea has fascinated the minds of innovators since the advent of early robotic technologies. Nonetheless, computer vision in manufacturing still has significant room to grow, and the number of possible applications will only grow over time.
The idea that AI has the same ability to make decisions based on visual input without manually entering data is spectacular. But since the AI will work based on the training data provided, it's best to connect with a certified machine learning service provider to avoid any unnecessary hiccups.
Artificial intelligence services have modernized many companies in recent times. As the largest and leading Artificial intelligence development company in Frisco, USA and UAE, USM Business Systems has provided best-in-class AI solutions and services that meet our clients' business needs.
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