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PREDICTIVE MAINTENANCE

Part 1: Introduction to predictive maintenance in cement plants

First, let's learn about the cement production process including 6 basic steps:
+ Step 1: Extraction of raw materials
+ Step 2: Squish, Proportional division And Mix
+ Step 3: Before putting in the Rotary kiln
+ Step 4: Stage in rotary kiln
+ Step 5: Complete cooling and grinding
+ Packing and shipping

The production is based on the performance of the service equipment. The downtime associated with these devices is the most costly for the company. Therefore, it is important to monitor the motors, conveyors, fans, blowers, gearboxes used in the process.

The factory needs to have monitoring equipment because:
- Expensive repair and replacement costs.
- Bearings are replaced regularly to ensure equipment is always in working order.
- Over-maintained equipment for greater productivity.
- The device operates in harsh environments.
- Ensure safety for workers and avoid accidents.

Typical problems in a cement plant are:
Loose nuts, bolts, springs, plates, spring rods, flywheels, bearings, shafts, coupling housings, hammer rotors
- Engine failure, conveyor belt failure, broken bearing, broken pull rod, broken separator blade
- Broken fan bearing, fan out of balance
- Gear knocking, gear tooth wear, gear deformation, gear injection and firing
- Broken main shaft, damaged crusher bearing, broken belt
- Move the disc liner
- Damaged pipes, broken pumps, broken wheels

For the cement industry, the savings in operating costs are directly related to keeping equipment running longer and more efficiently, reducing the risk of unexpected shutdowns, and optimizing operations. preventive maintenance. In particular, the furnace shell must be closely monitored. Smart sensors can provide live temperature data on the oven case as it rotates. They allow control room operators to place furnace housings under 24/7 high surveillance and alarms are generated when thresholds for critical parameters such as hot spot detection, coating loss or tire slippage are reached. out of range.
Therefore, various advanced techniques including infrared thermal imaging, vibration analysis and oil analysis can be used for fault prediction. This is predictive maintenance (predictive maintenance, preventive maintenance,...) For example, if your business uses mechanical equipment and electrical systems, thermal infrared imaging can Scan, visualize and analyze the device's temperature. You can actually see what parts of the device are “running hot,” which is invaluable information for both manufacturers and field service technicians.

Predictive maintenance of cement plant equipment used for crushing and crushing equipment, material conveying systems, ball and roller mills and material separators including: air compressors, conveyors, Fans and blowers, rollers, motor bearings, vertical and horizontal mills.

Part 2: Benefits of predictive maintenance in cement plants

Predictive maintenance can help technicians:
- Device vibration readings can be collected.
- On the basis of real-time three-axis oscillator, a trend can be obtained.
- Details can be generated that can be reviewed during weekly or scheduled maintenance. Deeper analysis of insights can speed up decision-making.
- If any abnormality is detected, it can be sent to the maintenance team as SMS and email.
- Take timely remedial measures to prevent incidents, avoid production loss and ensure labor safety.
- Predictive maintenance can be scheduled accordingly. Corrective measures such as centrifugation, oil filling, oil change, bearing/gearbox inspection can be carried out.

Part 3: How is maintenance appropriate?

Predictive maintenance methods include:

- Vibration analysis: For heavy machinery, manufacturers can apply vibration sensors to detect signs of deterioration during operation. For example, the shafts and bearings in pumps and motors will move differently when they are damaged.
- Create heat maps: Also known as infrared techniques, to detect high heat points in the device during operation, which means that those parts are subject to too much friction. These findings often alert manufacturers to potential problems requiring maintenance.
Acoustic and ultrasonic analysis: This technique uses acoustic signals to detect small cracks and broken welds before they become visible and cause gas or liquid leaks.
Oil Analysis: Oil analysis checks for the amount of debris in oil-using equipment. The greater the amount of metal debris, the greater the sign of wear. Besides, this technique can also find leaks and check oil cleanliness.

Besides the above methods, predictive maintenance can also apply emission testing and condition monitoring techniques to enhance performance analysis. The right combination of different methods, integration with Machine learning and complementary tools like CMMS, will help minimize breakdowns and maintenance workload. This leads to a reduction in the total amount of time and budget spent on maintaining equipment.

Vibration analysis is arguably one of the most accurate techniques for identifying problems in machinery, and is the best advanced predictive maintenance tool for optimizing plant performance.

This tool analyzes the spectrum used to measure different frequencies in the vibration data. To determine machine condition, vibration severity is compared with a standard severity table. Fast Fourier transform (FFT) spectrum analysis is widely used to develop a unique predictive analysis technique for monitoring device health.
End users get relevant information on the dashboard. They receive email/SMS notifications of any violation of the configured alert limits. They can view FFT error frequency reports, spectrum, and analyze these FFTs to predict errors in advance.
When data is required to verify compliance, it is available and instantaneous when needed, minimizing production delays and ensuring work can proceed as expected.

Industrial Data Management's patented edge computing vibration monitoring system (IDE) remotely captures triaxial vibrations, noise, and temperature of any mechanically rotating equipment in real time. It allows the Maintenance team to monitor machine uptime, reduce unplanned downtime, and combat impending damage to equipment. Furthermore, an end-to-end solution with intuitive indicators ensures maximum machine availability, reduces spare parts inventory and maintenance costs, and adheres to safety and physical distancing guidelines due to Government directed. It not only helps to reduce fixed maintenance costs at a time when reducing costs and manpower is an urgent need. 

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