Computer vision in manufacturing focuses on the creation of artificial systems that can capture visual inputs from the physical world (primarily factories and other industrial spaces), process and elicit appropriate responses and assist humans in a variety of production-related tasks
The earliest incarnations of computer vision, in manufacturing and other fields, can identify specific objects and trigger a response according to a rule-based principle, by identifying certain features in captured visuals and verifying whether they match a set. given parameters.
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Recent advances in AI, machine learning (ML) and deep neural networks have helped solve these problems, enabling manufacturing companies to enhance their computer vision systems with self-improving algorithms that can identify recurring visual patterns and relate them to certain items. experience
How is computer vision used in manufacturing?
In general, computer vision in manufacturing is used for production and quality inspection, construction monitoring, and tracking for damages or defects Cameras allow manufacturing plants to inspect their products for minor defects They are much more sensitive than the human eye and machine vision never gets tired.
1. Vision-Guided Robotic Systems
If Leonardo had known about the future role (and capabilities) of robots in manufacturing, he probably would have been surprised. Nowadays, computer vision-guided robots represent the cornerstone of any assembly line. In fact, they can easily locate and manipulate objects with mechanical arms or map their surroundings to navigate a manufacturing plant, making them a valuable tool for improving product yields and streamlining warehouse management and logistics.
These are some common tasks performed by computer vision-powered robots:
● Product processing and assembly
● Palletization, packaging, and sorting
● Heavy equipment cleaning
● Product labeling and tracking
● Warehouse monitoring for restocking
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2. Quality Assurance
Robots driven by computer vision are very precise, but something can go wrong in the production chain. Fortunately, computer vision systems can also be deployed to double-check product quality.
This advanced type of automated visual inspection involves scanning finished products with high-resolution cameras, processing data with
machine learning algorithms to detect anomalies, and ensuring that each item (including its packaging) meets all required quality standards
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3. Property Management
When it comes to identifying manufacturing defects and industrial asset anomalies, the devil is in the details. The good news is that computer vision systems, enhanced with machine learning for detecting anomalies, can deal with detail very well.
Indeed, these tools can inspect industrial machinery with cameras, infrared thermography, and other types of sensors to detect any anomalies (such as irregular temperatures and vibrations) that could be signs of malfunction and predict impending failures before they actually occur
General Motors, for example, has adopted a computer vision solution designed to analyze images from cameras mounted on assembly robots and identify failures affecting their components
4. Personnel Safety
Computer vision can be a guardian angel for machines and especially for humans, as predictive maintenance allows manufacturing companies to repair machines early and thus avoid dangerous situations. Moreover, it can be used to continuously monitor complex manufacturing operations in a variety of industrial environments.
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5. Improvement of after-sales service
Manufacturers understand that as important as their efforts to make sales are, their actions after sales are having a significant impact on their company's financial performance
A recent study found that 27% of the total revenue of manufacturing companies comes from service. Another report suggests that the average gross margin is 39% attributable to after-sales service. Undoubtedly, high-quality service is important for achieving financial success.
6. Customization of Products
The power shift from manufacturers to consumers described earlier will encourage investment in product customization capabilities, which are increasingly made possible by the use of big data, machine learning, and advances in advanced analytics.
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When manufacturers offer customized products, consumers provide extensive data about their preferences and behaviors that manufacturers can use to inform future product development Big data analytics enables companies to analyze customer behavior and develop methods to deliver products in the most timely and efficient manner possible.
Conclusions
Computer vision manufacturing, along with many other technologies involved in the digitization of industrial processes, have proven to be valuable allies for manufacturing companies, resulting in significant cost reduction, higher product output, increased quality, higher accuracy and increased staffing. Safety. Obviously, organizations should not take computer vision lightly, as its actual deployment may be trickier than expected.
However, with the right investments, retraining programs, workflow harmonization initiatives, and use case identification, computer vision-powered machines can spur industrial manufacturing just as they spurred artisans' love of beauty to create their products in past centuries The difference is that machines, unlike love, are not blind. No more.