In a remarkable stride towards bolstering workplace safety, Magnitogorsk Iron and Steel Works has embraced cutting-edge technology to create a safer working environment for its employees. By leveraging machine vision and AI driven solutions, MMK has successfully implemented a system designed to prevent personnel from entering hazardous areas within its coke plant.Working collaboratively, specialists from the coke plant and MMK's Occupational Health and Safety Directorate identified areas where employees might be exposed to workplace hazards. To mitigate these risks, innovative measures were introduced, including the installation of specialized sensors on coke machines. These sensors are capable of determining an employee's proximity to operating equipment.The system's functioning is ingenious: when an employee is detected in close proximity to a coke machine, a vibration signal is transmitted to the RFID tag assigned to that employee at the start of their shift. Simultaneously, light and sound alarms are triggered on the coke machine, and its mechanisms are instantaneously immobilized. This proactive approach, further enhanced by personal RFID tags applied to helmets, ensures quick and accurate identification of employees.MMK's prioritization of occupational health and safety is evident in this initiative. By integrating state-of-the-art technology, the company is mitigating risks associated with workplace accidents and potentially dangerous actions on the part of employees. The underlying technology powering this safety enhancement is the Digital Worker software platform. This platform combines global and local positioning systems, data processing from wearable devices, video surveillance, and advanced video analytics. The amalgamation of these features empowers the system to process data from numerous devices and systems concurrently, presenting the information through a 3D digital twin of the industrial environment. Remarkably, the system also boasts the capability to analyze data and identify potential threats and risks of injury.
In a remarkable stride towards bolstering workplace safety, Magnitogorsk Iron and Steel Works has embraced cutting-edge technology to create a safer working environment for its employees. By leveraging machine vision and AI driven solutions, MMK has successfully implemented a system designed to prevent personnel from entering hazardous areas within its coke plant.Working collaboratively, specialists from the coke plant and MMK's Occupational Health and Safety Directorate identified areas where employees might be exposed to workplace hazards. To mitigate these risks, innovative measures were introduced, including the installation of specialized sensors on coke machines. These sensors are capable of determining an employee's proximity to operating equipment.The system's functioning is ingenious: when an employee is detected in close proximity to a coke machine, a vibration signal is transmitted to the RFID tag assigned to that employee at the start of their shift. Simultaneously, light and sound alarms are triggered on the coke machine, and its mechanisms are instantaneously immobilized. This proactive approach, further enhanced by personal RFID tags applied to helmets, ensures quick and accurate identification of employees.MMK's prioritization of occupational health and safety is evident in this initiative. By integrating state-of-the-art technology, the company is mitigating risks associated with workplace accidents and potentially dangerous actions on the part of employees. The underlying technology powering this safety enhancement is the Digital Worker software platform. This platform combines global and local positioning systems, data processing from wearable devices, video surveillance, and advanced video analytics. The amalgamation of these features empowers the system to process data from numerous devices and systems concurrently, presenting the information through a 3D digital twin of the industrial environment. Remarkably, the system also boasts the capability to analyze data and identify potential threats and risks of injury.
