Pickling lines: cleaning and chemical processes under control

During hot rolling, impurities often form on the surface of the steel, such as mill scale (oxide skin). In the pickling line, this layer is removed using acids or mechanical means,...
Pickling lines: cleaning and chemical processes under control

During hot rolling, impurities often form on the surface of the steel, such as mill scale (oxide skin). In the pickling line, this layer is removed using acids or mechanical means so that the surface is clean and suitable for further processing or delivery.

The pickling process is intensive and complex: the material moves through a series of rollers and baths with circulating chemicals. This requires precise monitoring of both the mechanical and chemical components to ensure quality, safety and continuity.

Recommended IoT sensors for the pickling line.

1. Pressure/vacuum sensors:
The circulation of acids and rinse liquids is through pumps and pipes. A deviation in pressure or vacuum can indicate blockages, leaks or pump failures. This can lead to incomplete cleaning, material damage or even dangerous situations due to chemical leakage. Sensors continuously monitor the pressure in pipes and baths so that deviations are immediately detected and the process remains safe and stable.

2. Infrared temperature sensors: The effectiveness of the mordant depends greatly on temperature. Too low temperatures reduce cleaning power, while too high temperatures can upset the chemical balance or cause material damage. Sensors measure bath temperatures and ensure optimal chemical performance and process safety.

3. Ampere/consumption sensors: The rollers and pumps in the pickling line are in constant motion. Changes in power consumption can indicate wear, blockages or overload. Early detection prevents downtime and equipment damage. Sensors measure the power consumption of motors and pumps so that abnormalities are quickly detected and maintenance can be scheduled in a timely manner.

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Jeroen Frantzen

Our specialist

Jeroen Frantzen

predictive maintenance | iot sensors
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