AIROPax™ is a multi-functional intelligent robotic system where unlike traditional industrial robots, has the capability of intelligently dealing with operational tasks.
Artintech’s Intelligent Robotic Operator is a unique solution to a variety of your operational issues. Without any major modification to your production line, this system helps you with Real-Time production line monitoring and control.
Using Image Processing and highly compatible IoT solutions, AIROPax™ reduces human errors and labor workload and increases the work safety and production speed.
Some industrial and agricultural products are graded based on their dimensions and quality. The grade is then used to sort them and distribute them across various sales channels. Higher grade and bigger products usually generate more revenue.
Grading was traditionally a human-driven process. As time went on, machines were developed to differentiate products based on their dimensions and weight. These devices remain in use today as reliable grading and sorting methods. As image processing algorithms developed in recent years, AI visual inspection techniques began to improve the process. These techniques have often been tuned manually and replaced the human eye, enabling them to detect significant defects which are difficult for humans to detect at faster speeds. A new generation of intelligent algorithms for sorting and grading is more accurate and capable than traditional visual analysis algorithms. This is because they can learn by themselves, resulting in detection rates that exceed what any trained expert could achieve.
Defining a defect using artificial intelligence is a further development of machine vision inspection solutions. It uses deep learning technology to capture and process images, just like the human eye. The system learns from experience, recognizes characteristics and anomalies, and differentiates between them. Human visual inspection is fault prone due to its repetitive nature. The advantages of AI-based systems are their accuracy and reliability. Ultimately, defect reduction, improved production, and positive results lead to quicker delivery to consumers, increased satisfaction, and increased profitability.
With the volume of data in supply chains and logistics increasing daily, the demand for more leading-edge processing solutions is becoming more crucial. Many companies are implementing AI computing techniques; Machine learning, deep learning and natural language processing. These techniques make it simple to examine large volumes of data efficiently, to deliver a sophisticated analysis and execute many other complex tasks.
Supply chain and logistics companies generate and can utilize a lot of data. AI requires extensive volumes of data to show its full power. With new types of data surfacing in the past several years, along with a progressive pace of data creation, AI is finally provided with enough to work to its fullest potential.
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