Mining machines are subject to considerable wear and tear. Preventive maintenance is therefore important to avoid unplanned machine downtime.
Mining is becoming increasingly important in the age of growing demand for ores and rare earths. It is estimated that an increase of 7,000% in the yield of copper ore alone will be required to achieve the goals of electromobility.
As machines in opencast mining are subject to heavy wear and tear, unplanned downtimes mean considerable costs due to long waiting times for spare parts procurement and repairs. Predictive maintenance can be used to minimize downtimes due to unplanned repairs. This involves constantly measuring the most important wearing parts and calculating the degree of wear. This data can be used to calculate and plan a maintenance date. Spare parts and maintenance personnel are then available in a coordinated process.
Example 1: Conveyor belts
In large opencast mines, conveyor belts with a length of 10-20 km are sometimes used. These conveyor belts are made of vulcanized rubber with steel inserts. Some of the material being conveyed consists of pointed and sharp-edged stones that fall from a tower onto the conveyor belt at a certain height. Sometimes these stones cut through the conveyor belt, causing a crack. If this crack is not noticed and repaired, it can expand due to the forces acting on the belt and eventually cut the belt completely open. As the plant continues to run for a while, the rock then builds up into a mountain and the plant has to come to an unplanned standstill. This often means that the downstream processing operations also come to a standstill. Such an accident is associated with high costs.
SOLUTION: Inline monitoring of the conveyor belts with QuellTech line laser
3D laser line sensors from QuellTech are used for the non-contact detection of cracks. The sensors project a laser line perpendicular to the direction of movement of the conveyor belt onto the underside at the point where the rock falls onto the belt. If a stone cuts through the belt, this surface change is detected in 3D by the sensor and recorded. Depending on the size of the defect, an alarm is triggered and, if necessary, the system is shut down in a controlled manner and repaired immediately. At another point, the surface of the conveyor belt is measured for wear using QuellTech 3D laser line sensors. As the belt is running at this point without conveyed goods and has been cleaned, the belt thickness and gradual wear can be measured at individual points. As the fault location is also recorded, a repair can be carried out precisely at the points found as part of predictive maintenance. This allows the service life of a conveyor belt to be extended in a controlled manner. The use of highly robust conveyor belts, which are sometimes 10 times more expensive, can thus be avoided.
Example 2: Wear detection in mineral processing
In mineral processing, heavy machines are used to crush and grind rocks and raw materials to prepare the extraction of the valuable materials and minerals. A significant opportunity to reduce energy and emissions sits within comminution, which is the process that turns big rocks into small particles. This process is responsible for at least one-third of an average mine’s energy use and CO2 emissions and globally consumes around 3% of the world’s electrical power. One of these machines in the flowsheet are so called high pressure grinding rollers (HPGRs). HPGRs are commonly found in the tertiary or quaternary processing plant of mining operations. Essentially the HPGR creates micro cracks and fractures into a bed of particles which move within the gap between two counter-rotating tyres. HPGRs enables the user to reduce particle sizes from >85 mm down to a micron-sized product. During the grinding process, the tyres wearing down considerably over time.
SOLUTION: Inline monitoring of roller surface with QuellTech line laser
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Stefan Ringwald
Technical Consultant
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