Industrial Robotics Training courses - Burraq
Companies are constantly looking for ways to improve their current operations, optimize production processes and reduce overall carbon dioxide (CO2) emissions. The use of operational technology (OT) and information technology (IT) has helped companies better manage their operations by managing valuable assets, reducing repetitive and routine tasks, and improving quality control. Burraq Academy offers 75+ different robotics training courses including Basic Programming, Advanced Programming, Maintenance & many others. However, IT and OT have traditionally developed separately, without the ability to use operational and production data to make more informed decisions to optimize workflows and well-planned production and maintenance processes.
Operational technology (OT)
Operational technology (OT) and information technology (IT) have helped companies better manage their operations by tracking valuable assets, reducing repetitive and routine tasks, and improving quality control. However, IT and OT have traditionally developed separately, without the ability to use operational and production data to make more informed decisions to optimize workflows and well-planned production and maintenance processes.
Transmit them to OT systems
With the advent of the Internet of Things (it) in recent years, the line between these two systems is blurring, leading to converging solutions. Iota devices belonging to the IT domain can collect operational and production data from the field and transmit them to OT systems.
The convergence of IT and OT
The convergence of IT and OT will enable workers to do more and drive their improvements further, finding the right balance between business costs and strategic technology investments. In addition, this convergence will enable companies to accelerate their digital transformation and optimize existing workflows without the need to rapidly expand their capabilities.
Automation of robotics
One of the technologies that best represents IT-OT convergence is operations management using robotic automation. With automated processes, companies can analyze data, gain valuable insights, and gain greater insight into the performance of their manufacturing facilities, helping them make data-driven decisions. However, the development of robotics has traditionally been very complex and demanding. As demand for robots is expected to grow rapidly, the current pace of innovation can be accelerated with appropriate hardware and software offerings.
The rise of robotics
In general, the use of robots has introduced new roles for these devices aimed at improving worker safety, reducing burdensome and dangerous tasks for human workers, speeding up e-commerce processing and delivery, and increasing business flexibility and resilience. These new capabilities require the deployment of high-precision sensors that meet functional safety and risk prevention requirements, cameras for detection, localization, and navigation, and robotic middleware for application embedding. In recent years, there have been significant advances in robotics hardware that allow OEMs to develop robots that can see and sense their environment:
Computing processors
Computing processors have become more powerful in recent years, allowing robot manufacturers to run resource-intensive applications directly on the robot. For example, graphics processing units (GPUs) have proven ideal for performing data processing based on machine learning (ML) algorithms that enable robots to perform object recognition and sensor fusion. Progress has also been made in the development of application-specific integrated circuits (ASICs) suitable for specific ML applications such as video processing and speech recognition.
Edge computing
The ability to process the information on industrial gateways and servers in the field means that robots can collect process and store information at the edge of the system. Sensor Technology – Advances in sensors such as two-dimensional (2D) and three-dimensional (3D) cameras, 2D and 3D light and distance sensors (Lid AR), inertial measurement units (IMUs), and proximity sensors enable highly accurate machine vision and sensor fusion algorithms. A typical autonomous ground robot may be equipped with multiple high-definition (HD) cameras, 3D depth sensors, and Lid AR sensors. Along with the continuous improvement of 3D depth sensors.