TLT Service is a Belarusian supplier of integrated industrial solutions that has developed a hardware/software system for Condition Monitoring of the mining equipment for one of the world’s largest producers of potash fertilizers. Applied Systems helped the Customer to implement a control software for the monitoring system of the hoisting shaft.
The key task was to develop a convenient data analytics toolset that would help to identify the damage risks, find the root causes of abnormal behavior of shaft equipment, and increase the performance of maintenance procedures. The use of the integrated Condition Monitoring solution should reduce downtime and optimize the efficiency of the hoisting shaft facility.
The challenge was to ensure the running smoothness, achieve a certain, desired speed of skip along the mine shaft and identify the problem areas. The designed solution had to provide the following functions:
• Process and analyze the data streaming from the accelerometer, gyroscope, position transducer and other sensors for Condition Monitoring of the facility during mining and maintenance periods;
• Carry out the statistical analysis of the historical data for the last 24 hours to detect the most problematic areas of the mine shaft;
• Find the root causes of abnormal behavior of shaft equipment;
• Help improve the business processes of the organization and plan the maintenance checks of the mining equipment.
The core of the solution - platform Propheto provides all generic functionality for acquisition, storage, processing, and visualization of data. We extended the platform with a set of specialized add-ons oriented to specific domain problems and integrated a new module with other system components. Applied Systems offered the customer a two-stage scheme that ensures a consecutive improvement of the situation.
The first stage - development of the analytics module for analyzing the results of daily measurements. Our developers implemented a system of statistical analysis and proposed visualization tools that help the personnel plan and perform daily maintenance operations.
The second stage - preparation of the structured data warehouse and analytical tools for analysis of long-term trends. System capability: number of channels for persistent data storage - 80-120; measured results are stored in the database for 5 years.
The analysis of a large amount of data obtained from diagnostic equipment and winding machine combined with data obtained from the service log will enable to use Predictive Maintenance methods to optimize the workflow management and improve the efficiency of mining equipment.
The project was implemented within the planned time. The integrated solution provides machine operators and maintenance engineers with information to schedule maintenance checks, improve machine efficiency and reduce downtime.
The usage of analytical toolset demonstrated the following results:
• Increased usability, navigation through the process data in a fast and intuitive manner;
• Greater visibility into the hoisting shaft equipment performance;
• Ease of training;
• Improved key operational workflows like maintenance tasks.