Inner Banner

An intelligent blend of data and advanced analytics can help miners balance higher productivity with energy efficiency and reduced cost of mining operations. Banking on Business Intelligence (BI) and Machine Learning (ML), Advanced Data Analytics provides information and insights that miners can leverage to identify trends, make predictions, and optimize results. Within the expansive domain of Analytics, Predictive Analytics helps mining companies reduce equipment downtime, increase reliability, optimize performance and reduce operational as well as maintenance expenditure. 

Benifit

Benefits

Features and USP

How it Works
How it Works
How it Works
How it Works
How it Works
How it Works
Integrated Performance and Condition Monitoring

<p>Advanced analytics can be applied to filter data for anomalies, diagnose problems, and make prognosis on a system's ability to sustain operational levels.</p>

Real-time benchmarking

<p>To identify and quantify the impact of different business drivers <br />  </p>

Value-based decisions

<p>Advanced analytic models can be used to generate alternative solutions to operational problems and evaluate each alternative's value impact.</p>

Dynamic identification of bottlenecks

<p>Real-time models enable miners to dynamically identify and predict bottlenecks, prioritize maintenance activities to minimize downtime, and automatic identification of opportunities for scheduling maintenance without affecting value-chain throughput<br />  </p>

Data validation and reconciliation

<p>Automated decisions about data quality and resolution of inconsistencies using a combination of multivariate techniques, models, and machine learning techniques.</p>

Reducing variance in mining processes

<p>Data-driven statistical analysis techniques can be applied to improve understanding of the causes of variability. Further, automated technology can be deployed to make consistent operational decisions.</p>

How it Works
How it Works
How it Works
How it Works
How it Works
How it Works