Saiba como criar um caso de negócio para a monitorização do estado das suas bombas submersas.

16x alertas precoces para rolos em degradação poupam 650 mil euros em perda de produção

By consistently detecting developing faults in its roller conveyors well ahead of failure, this hot strip mill is keeping production on track while spending less on maintenance and repairs.


In hot strip mills, hundreds of rollers make up the conveyor line that transports the hot steel slab through every step of the rolling process, from where it leaves the furnace all the way to the coiler at the other end. A damaged roller can harm product quality and even bring production to a stop. Early warning of developing problems is important to avoid unplanned downtime and product discarding.


At a hot strip mill, SAM4 Health is installed on the rollers in the production line conveyor. Over a ten-month period, SAM4 alerted the customer to 16 developing faults.

In each case, SAM4 detected an increase in spectral energy at frequencies corresponding to system components. The customer inspected the roll in question and performed the relevant maintenance: in ten cases, replacing a worn, damaged or missing component; in two cases, tightening support structures that had come loose; and in one case, cleaning a very dirty roll. After maintenance, SAM4 confirmed a return to healthy behavior in each case.

laminador gráfico de tiras a quente sam4 1400w
SAM4 data for one of the 16 fault detections. The customer was alerted at the first blue line; after they performed maintenance (at the red line), SAM4 confirmed a return to healthy behavior at the second blue line.


Thanks to SAM4’s consistent early alerts, the customer became aware of developing issues before product quality was affected. This early notice also made it possible to plan and perform maintenance at a time when it would not disrupt production. Depending on a roller’s position in the conveyor, it may be easier or harder to reach; the time required to service a roll can therefore vary from 2 to 16 hours. For the fault detections in this case study, the customer saved €650k by avoiding unplanned downtime.

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