Russian steelmaker NLMK Europe is expanding its programme to monitor the health of critical assets after completing a successful pilot with new machine learning technology at its hot strip mill in NLMK La Louvière, Belgium. The company plans to roll out the SAM4 system from Dutch tech company Samotics across its other sites in Europe.
Samotics’ technology is based on electrical signature analysis (ESA), an approach to condition monitoring that is claimed to offer 'unique advantages', according to the company.
The SAM4 system captures electrical data remotely, in the motor control centre, so there is no need to install sensors on or even near the equipment.
“Most of our machines operate in extremely high ambient temperatures, where most sensors will just burn up.”Pavel Podyachev, R&M system development manager, NLMK Europe.
“Most of our machines operate in extremely high ambient temperatures, where most sensors will just burn up,” says Pavel Podyachev, R&M system development manager at NLMK Europe. “SAM4 finally gives us a way to monitor these assets.”
SAM4’s use of ESA technology confers two more benefits for NLMK’s overall asset monitoring strategy. All condition monitoring technologies detect a broad range of mechanical faults; ESA is the only one that can also detect electrical faults, which cause up to 30% of equipment failures. It is also the only technology that can report on energy efficiency. “SAM4 offers detailed energy and performance insights that will concretely help us reduce our environmental footprint,” says Podyachev. “This is a strategic objective in NLMK’s sustainable development goals.”
“We are proud that NLMK is offering us the opportunity to implement SAM4 across Europe,” says Simon Jagers, Samotics’ co-founder. “It’s a testament to the value that our industrial analytics technology provides on a day-to-day basis, and we are delighted to be part of making the steel industry safer, more reliable, and more sustainable.”