Mining & Metals
A mining and metals group was looking to improve the operational reliability of their facility and reduce maintenance downtime.
PREDICT was able to provide a solution that would assist the client in reducing facility downtime, improving maintenance scheduling, identifying equipment failures months before they occur and, access to an easy-to-use web-based platform to monitor the facility.
5.5 months Prognostics
Anticipated the failure of hot air generator system 5.5 months in advance
Implemented a wide range of indicators to monitor multiple facility systems
Improve operation capability
Reduced the downtime by timely prediction of failures and drifts
The mining company was looking for a solution that could
- Provide an easy-to-use monitoring solution
Having no pre-existing system for detecting asset failures and, with limited data analysis tools, the client required PREDICT to provide them with an easy-to-use platform that enables quick and accurate understanding of the health of their assets and, analyse the changes in the asset’s performance through visualisation of data.
- Analysis of multiple systems within the facility
The client’s facility consisted of multiple systems – all vital for smooth operation. This required PREDICT to analyse and formulate condition-based monitoring and predictive analytics for an oil-hydraulic system, water-cooling system, hot air generation system, pneumatic transport system etc.
- Provide visual tools that all work teams can understand
Any Predictive Maintenance solution needs to encompass a visualisation platform that would help different work teams comprehend the analysis and take necessary actions. PREDICT provided the client with appropriate visualisation tools that not only the engineers but also the maintenance personnel can interpret and, identify the alerts easily.
- Reduce downtime and assist with maintenance scheduling
If key equipment in the facility failed, production is stopped until a maintenance intervention is performed, which could incur significant revenue loss. PREDICT’s goal was to reduce maintenance downtime through early detection of drifts, lower maintenance costs and assist with the planning of scheduled maintenance to improve the operational capability of the facility.
PREDICT supplied the client with Kasem, a web-based monitoring platform. This platform enabled the client to have a centralised view of the facility, visualise the asset behaviour over time and, monitor the health of their equipment easily.
To ensure extensive supervision of each equipment and process in the facility, PREDICT developed a wide range of indicators and causality trees, by a thorough engineering study to gain a better understanding of the facility’s operations.
The algorithms developed by PREDICT were able to detect 24 equipment failures that would have led to facility shutdown if maintenance was not performed on time. PREDICT also assisted the client in analysing the failures and planning of maintenance to resolve it on time.
One of these 24 failures was predicted 5.5 months in advance. The client was proactive in organizing a maintenance intervention before the predicted failure time, could prevent a huge downtime and, improve the operational availability of the facility.
The client was greatly satisfied with the outcome of the project. The collaboration between the client and PREDICT’s team played a vital role in understanding the facility and developing an accurate Predictive Maintenance solution.