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Considered a branch of Artificial Intelligence (AI), Computer Vision aims to replicate functions conditioned on human vision. Systems using this technology can, in addition to capturing images, use them to collect and interpret data. Within the industrial sector, many processes can be optimized through systems that can be part of this technological constellation. Industry 4.0, also known as the 4th Industrial Revolution, has been a recurring topic in the field of exponential entrepreneurship. The idea works through the merging of several arms of AI that, gathered together, can make companies grow in reach. Among the most common branches are also Robotics, the Internet of Things, Machine Learning, and even the Machine to Machine system, M2M. Through automation and data interpretation within the production stages, Industry 4.0 has been revolutionizing traditional business models. Optimizing the productivity of various sectors, the branches of Artificial Intelligence (AI) can not only make processes more efficient but also make the means of production safer, since with the use of machines, employees are spared from dangerous tasks.
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Understand the transformation process
Applying technological mechanisms to industrial processes has led sectors to undergo what is known as digital transformation. Computer Vision is then starting to be one of the most far-reaching mechanisms of technology, making larger steps towards large-scale growth viable. With the use of a system powered by data, it becomes possible to recognize images based on numerical values. In this way, new doors are opened in terms of technological advancements; the system for counting items within a production chain, for example, is automated and now has an average accuracy of 98%. The traditional process of this work happens through human labor and depends on an employee's ability to manually count several similar items. Besides being inaccurate, the task becomes extremely exhausting. To exemplify the use of disruptive technologies in production chains, we have the Piracicaba unit of ArcelorMittal. The multinational, which previously performed the process of counting steel bar bundles through human labor, started using the Pix Counter, a Computer Vision solution from the Rio Grande do Sul startup Pix Force. The counting then became automated, fast, and accurate.
Industrial inspection through Computer Vision
In addition to application in counting chains, inspection systems also receive optimization through this branch of AI. Performing quality control manually, besides being a time-consuming process, also involves various types of technical professionals who are able to evaluate the necessary specificities. Once again, the situation becomes slow and subject to failure. With the use of Computer Vision, machines can be capable of doing a complete traceability process (understand more by clicking here), that is: they control a product through its origin and location in the production chain. In this way, specific failures can be found in record time, enabling the removal of some products from the production line, as well as calls for potential recalls. It is undeniable how much various industrial segments can benefit through the use of AI systems. In addition to saving repair time and the risk of employees being exposed to tiring situations, the technology is still capable of making these same employees strategically utilized within the company. Long-term repair costs, as well as the optimization of resources invested in production time, become lower, since the entire production chain gains speed and efficiency.
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
