Eastern Mining Company (VGK) (iT Pro: BI.Qube)

2020: Developing a tool to address typical mining challenges

The goal of the project was to develop a tool to solve typical problems in the mining industry, such as optimizing the loading of dump trucks and minimizing downtime of excavators. Analytical tasks were solved to correlate the efficiency of each driver with the performance of the entire fleet of equipment, to identify and prevent the causes of losses caused by violations in the service regulations, incorrect rhythm of related processes, and other factors.

An important part of the project was the digitalization of machine management based on telemetry data (IoT), which BI.Qube extracts online from remote areas, consolidates with accounting system data, transforms and prepares for various use cases. Our customers receive: up-to-date, with an update every 15 minutes, analytics on the numerous processes that accompany production. Consolidation of processes that did not appear in accounting systems. Holistic perception of the current state for each technological process.

Since the data refresh rate is 15 minutes, automatic partitioning mechanisms in both cubes and storage have been effectively worked out. Thanks to the implementation in Azure, the solution works in a mode close to real time (an event in analytics appears a maximum of 15 minutes after being fixed in the accounting system), it is economically profitable to lack a ground infrastructure and the ability to scale flexibly.

The solution is ready for replication for mining enterprises that consolidate data on the production processes, transportation of minerals (coal, ore) and waste rock, data on blasting, drilling, crushing, downtime, cargo turnover, machine changes, etc. Source data can be taken from both accounting systems and entered through MDS. This tool solves the problem of the lack of up-to-date analytical information about production processes in remote areas.

Technologies: A customized solution. BI Qube includes building the process of loading and transforming data based on Microsoft Integration Services, analytical, data stores Microsoft SQL Server multidimensional data mart Microsoft Analysis Services and interactive visual reports. Microsoft Power BI Filling of planned and non-system data is implemented on the basis of. Microsoft Master Data Services Architecture: at Azure IaaS. Key features of the system: Corporate Data Warehouse, structuring and combining information from heterogeneous system sources, and enriching with non-system accounting data. with - Integration MES system - regular receipt of operational indicators for productions the following processes is organized: Production, Opening, Truck Handling, Coal/Opening Distance, Equipment Downtime. All reference information (contractors, employees, machinery, loading/unloading points, rocks, etc.) is automatically kept up to date; Integration with the accounting-weight transport system - reference and operational data are regularly transmitted to QCD the coal processes transportation in the port. Integration with the Automated Fuel Accounting System was carried out in order to collect information on the fuel and lubricants balance. The result is end-to-end accounting of fuel and lubricants.

The possibility of non-system entry of information on processes that are not recorded in the company's information systems (crushing, drilling and blasting, coal shipment by ships) through the standard MDS web interface or through Excel has been set up. The components of the transformation and data processing pipeline are deployed, with a frequency of 15 minutes receiving all changes recorded in information systems - data sources. A relational data store layer is organized with reference book management as a Data Vault model. Multi-dimensional OLAP displays are implemented, which allow you to receive analytical information in any necessary sections in Self-Service BI mode. Daily summary reports for the company's management and detailed visual interactive reports in individual areas are implemented in Power BI.