An important issue in the development of smart manufacturing is human-computer collaboration, and true human-computer collaboration does not only mean cooperation and coexistence. As the frequency of man-machine operations working together in the same workspace is getting higher and higher, many sensors are also appearing to assist in monitoring and preventive control.
Industrial robots use a large number of sensors to achieve good operation and control in industrial automation production processes. For example, collaborative robots integrate torque sensors and cameras to ensure the best perspective and safety. What sensors are integrated with industrial robots?
Industrial robots can more quickly and handle large-scale mass production work. So far, nearly half of the industrial robots in the world are used by automobile factories. Let's understand the advantages and disadvantages and applications of industrial robots.
Automation technology accelerates the development of the industrial robot industry. In order to maintain and improve productivity, the manufacturing industry accelerates the introduction of unmanned and industrial automation technology. Industrial robots have become a long-term rigid demand.
After more than ten years, South Korea has continuously promoted machines to target South Korea smart cities. It has achieved remarkable results in the field of industrial robots and has gradually moved towards commercialization in the field of service robots. Industrial intelligence that enhances industrial competitiveness extends to the realization of the vision of coexisting humans and robots to intelligent life.
The world has entered the era of Industry 4.0. robots assist human manufacturing, emphasizing the use of "human-machine collaboration" to move toward smart production. In recent years, the population aging problem faced by developed countries has caused the production costs of industry and manufacturing to increase year by year. Enterprises have deployed automation equipment to improve production efficiency. Various industries have also undergone tremendous changes in this intelligent wave.
Information is power. Information can not only adjust decision-making but also help discover market opportunities. Use advanced motion control technology to optimize the performance of automated machines.
Artificial intelligence has brought in a new generation of robotics technology: Robotics 2.0. The principal challenge is the transformation from original manual programming methods to true autonomous learning. Faced with this challenge for innovation in AI robotics, how can Taiwan's manufacturing industry best seize the opportunity?
Robotic behavior is often built as a computational graph, with data flowing from sensors to computational technology, all the way to actuators and back. To gain additional performance capabilities, robotic computing platforms must efficiently map these graph-like structures to CPUs, as well as to specialized hardware including FPGAs and GPUs.
Robotic process automation (RPA) is a technology that mimics the way humans interact with software to perform high-volume, repeatable tasks. RPA technology creates software programs or bots that can log into applications, enter data, calculate and complete tasks, and copy data between applications or workflow as required.
A service robot is defined as improving the quality and convenience of human life. It provides semi-automatic or fully automatic services through the combination of a mobile base and a robotic arm and is equipped with a controller device.
Underwater robotics is not only used in rescue and search, it has already been used in marine resource exploration, seabed topographic mapping, and the construction and maintenance of marine engineering structures.
Industrial robot system integrators are located at the downstream application end of the robot industry chain, providing application solutions to end customers. It is responsible for the secondary development of industrial robot applications and the integration of peripheral automation equipment and is an important part of industrial robot automation applications.
In recent years, due to the high demand for customized orders and small and diverse production, the production line must frequently replace molds and adjust lines. Mold replacements often take 2 to 3 hours, and production line adjustments may even stop production for a few days, resulting in production delays and making production capacity impossible. How can we effectively replace molds, adjust production lines, reduce downtime, and quickly respond to customer needs?
Artificial intelligence has brought in a new generation of robotics technology: Robotics 2.0. The principal challenge is the transformation from original manual programming methods to true autonomous learning. Faced with this challenge for innovation in AI robotics, how can Taiwan's manufacturing industry best seize the opportunity?
Information is power. Information can not only adjust decision-making but also help discover market opportunities. Use advanced motion control technology to optimize the performance of automated machines.
The world has entered the era of Industry 4.0. robots assist human manufacturing, emphasizing the use of "human-machine collaboration" to move toward smart production. In recent years, the population aging problem faced by developed countries has caused the production costs of industry and manufacturing to increase year by year. Enterprises have deployed automation equipment to improve production efficiency. Various industries have also undergone tremendous changes in this intelligent wave.
The world has entered the era of Industry 4.0. robots assist human manufacturing, emphasizing the use of "human-machine collaboration" to move toward smart production. In recent years, the population aging problem faced by developed countries has caused the production costs of industry and manufacturing to increase year by year. Enterprises have deployed automation equipment to improve production efficiency. Various industries have also undergone tremendous changes in this intelligent wave.
The behavior of robots is frequently modeled as a computational graph, wherein data flows from sensors to computational technology, extending to actuators and then looping back. To enhance performance capabilities, robotic computing platforms need to adeptly map these graph-like structures to CPUs and specialized hardware, such as FPGAs and GPUs.