The safety considerations and implementation methods of industrial robot and human-robot collaboration are the key to ensuring the safety of people and robots coexisting in the production environment.
In the human-robot collaborative application of industrial robot, the relevant safety standards must be strictly followed first. It provides clear safety guidance for the design, installation and use of collaborative robots. In addition, standards such as EN ISO 10218 also specify the safety requirements of industrial robots to ensure that robots will not cause harm to people in human-robot collaborative environments.
In order to achieve the safety of human-robot collaboration, an effective safety monitoring system must be installed. These systems usually include laser distance sensors, safety light barriers, vision systems, etc., which are used to monitor the activities of people in the robot's working area in real time. When people enter the dangerous area, these systems will immediately trigger the safety mechanism to stop the robot from moving or reduce its speed to avoid collision and injury.
Speed and separation monitoring is one of the important technologies to ensure the safety of human-robot collaboration. This technology monitors the distance between people and robots in real time and adjusts the robot's operating speed according to the distance. When people approach the robot, the robot's speed will automatically decrease to reduce the potential risk of collision. This technology combines the concepts of speed control and spatial isolation to provide higher safety for human-robot collaboration.
In order to prevent the robot from causing harm to personnel, the robot's output power and force must be limited. By adopting special sensors and control systems, the force applied by the robot on the object can be monitored in real time, and the robot's movement can be stopped immediately when it exceeds the preset threshold. This power and force limitation technology helps prevent the robot from causing harm to personnel in unexpected situations.
Safe skin technology is a non-contact safety perception detection solution that detects approaching objects or personnel by installing special sensors on the surface of the robot. When a person or obstacle approaches the robot, these sensors immediately trigger a safety mechanism to stop the robot from moving. Safe skin technology has the advantages of fast response speed, large coverage area, and strong anti-interference, providing higher safety protection for human-machine collaboration.
In addition to technical means, personnel training and safety awareness enhancement are also important links to ensure the safety of human-machine collaboration. By conducting comprehensive safety training for operators so that they understand the working principle of the robot, safe operating procedures, and emergency response measures, the probability of accidents can be greatly reduced. At the same time, improving the safety awareness of personnel is also the key to preventing accidents. They should always be vigilant and avoid entering the dangerous area of the robot.
In a human-machine collaborative environment, safety assessment and improvement is a continuous process. Regularly conduct safety inspections and assessments on the robot system to promptly identify and correct potential safety hazards. At the same time, make necessary adjustments and improvements to the robot system based on changes in the production environment and personnel needs to ensure that it always remains in the best safety state.
The safety considerations and implementation methods of industrial robot and human-machine collaboration involve many aspects, including compliance with safety standards, application of safety monitoring systems, speed and separation monitoring technology, power and force limitations, application of safety skin technology, personnel training and safety awareness enhancement, and continuous safety assessment and improvement. These measures together constitute a solid guarantee for the safety of human-machine collaboration.
