The CELSA UK & Russula teams have commissioned three Computer Vision Sensors for the rebar & wire rod mill in Cardiff in UK. The Computer Vision Sensors solutions automated areas of the mill that had previously required manual intervention or were difficult to automate. By establishing Computer Vision Sensors in key positions, the mill is able to automate the control of the lateral position of the peel bar, furnace billet discharge, and two-strand looper. After implementing computer vision, tasks previously operator driven, are now fully controlled by the PLC, even using the same video stream that operators used to look at from the pulpit. Almost every task in the mill controlled by the human eye is now liable to be automated by a Computer Vision Sensors.Double strand loop control and pusher discharge from the furnace are common matters in many mills. When discussing how to address them with CELSA UK, w Russula decided to use computer vision to automate these two tasks. Previously, furnace operators discharged billets from the furnace in the same way video games used to be played, look at a screen and move a joystick. As entertaining as this method might have been, it required extensive manual intervention. By employing computer vision solutions, the position of the billets inside the furnace was determined, which allowed the PLCs to properly position the peel bar and automatically command the furnace pusher to discharge billets, thus avoiding continuous intervention by the furnace operator.Likewise, an existing scanner for the two-strand loopers was not functioning correctly. A Computer Vision Sensors was installed to measure the loop height. Computer Vision Sensors algorithms analyze the video feed to determine the height of the loop of each strand, which can be used to control the speed of the line. The loop control module in the existing PLC was modified to use the new input from the Computer Vision Sensors.Russula supplied the Computer Vision Sensors, electrical, software and HMI integration and onsite services including installation supervision, commissioning, and production support. The existing furnace camera was connected to the CV-Sensor. New cameras were supplied and installed for the furnace discharge and looper applications. The three computer vision applications were implemented in October 2021. Three computer vision systems are installed in the furnace and wire rod repeater areas at CELSA Steel UK in Cardiff. After capturing images, several CV algorithms extract measurements from those images and send the results to the automation system via Ethernet.CELSA Steel UK plant is the largest reinforcing steel producer in the United Kingdom. The Cardiff facility consists of a meltshop and two rolling mills: one for reinforcing steel and wire rod and the other for merchant bars and light sections. Annual production is 1.2 million tonne per year delivered to the UK and Ireland markets.
The CELSA UK & Russula teams have commissioned three Computer Vision Sensors for the rebar & wire rod mill in Cardiff in UK. The Computer Vision Sensors solutions automated areas of the mill that had previously required manual intervention or were difficult to automate. By establishing Computer Vision Sensors in key positions, the mill is able to automate the control of the lateral position of the peel bar, furnace billet discharge, and two-strand looper. After implementing computer vision, tasks previously operator driven, are now fully controlled by the PLC, even using the same video stream that operators used to look at from the pulpit. Almost every task in the mill controlled by the human eye is now liable to be automated by a Computer Vision Sensors.Double strand loop control and pusher discharge from the furnace are common matters in many mills. When discussing how to address them with CELSA UK, w Russula decided to use computer vision to automate these two tasks. Previously, furnace operators discharged billets from the furnace in the same way video games used to be played, look at a screen and move a joystick. As entertaining as this method might have been, it required extensive manual intervention. By employing computer vision solutions, the position of the billets inside the furnace was determined, which allowed the PLCs to properly position the peel bar and automatically command the furnace pusher to discharge billets, thus avoiding continuous intervention by the furnace operator.Likewise, an existing scanner for the two-strand loopers was not functioning correctly. A Computer Vision Sensors was installed to measure the loop height. Computer Vision Sensors algorithms analyze the video feed to determine the height of the loop of each strand, which can be used to control the speed of the line. The loop control module in the existing PLC was modified to use the new input from the Computer Vision Sensors.Russula supplied the Computer Vision Sensors, electrical, software and HMI integration and onsite services including installation supervision, commissioning, and production support. The existing furnace camera was connected to the CV-Sensor. New cameras were supplied and installed for the furnace discharge and looper applications. The three computer vision applications were implemented in October 2021. Three computer vision systems are installed in the furnace and wire rod repeater areas at CELSA Steel UK in Cardiff. After capturing images, several CV algorithms extract measurements from those images and send the results to the automation system via Ethernet.CELSA Steel UK plant is the largest reinforcing steel producer in the United Kingdom. The Cardiff facility consists of a meltshop and two rolling mills: one for reinforcing steel and wire rod and the other for merchant bars and light sections. Annual production is 1.2 million tonne per year delivered to the UK and Ireland markets.
