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Author's profile photo Rahul Prakash

BIG DATA in the Mining Industry- A challenge

BIG DATA in the Mining Industry- A challenge


With the rapid advancement in technology and the extensive amount of information that are being collected, why is BIG DATA analytics becoming so important in the mining industry?


The BIG DATA analytics can turn mines into an intelligent mines of the future that would be safe and have ZERO impact on the environment. This can also help to maximize productivity and improve performance.


Rio Tinto’s Pilbara Iron ore operation for example is generating nearly 2.5 terabytes of data every minute. The major hindrance to mining companies is, how to handle the huge volumes of data as they may have different size and meanings. The problem
with BIG DATA is the difficulty of gathering and analyzing so much information so quickly to achieve real time results.


Harnessing the capacity of BIG DATA in Mining


The data present in silos needs to be brought together to solve the problems of the various business processes. For example by applying strong competencies in operations and logistics management at the mine site could improve the following supply chain infrastructure.


  • Mine to Rail/Road to Port to Customer (M2RPC)
  • Mine to Rail/Road to Customer (M2RC)


High performing mining companies in today’s scenarios are just not following their traditional low cost mine production process but also they are looking ahead to improve performance across the extended supply chain. They do operational efficiency improvements at the mine site.


Predictive analysis can create an impact especially in the current supply-constrained market, where each incremental tonne of throughput can make a significant difference to the bottom line.


The analysis of data points of the production patterns of the customers can also help reducing mining company inventory cost.

Mining supply chains must excel at accurately forecasting available capacity to effectively plan infrastructure investment. In mining it can be particularly challenging to accurately forecast production past the short term, however can be of help to capitalize on the strong market.


Geological conditions and weather can significantly affect mine output and they require good communication, transparency and a robust forecasting process so that resources can be planned effectively.


Another objective is to influence the level of shipping arrivals to align with the available supply chain capacity, so that vessel queues are kept at an optimal level and demurrage costs minimized.


The Capacity Balancing System (CBS) is an effective short term measure to efficiently allocate scarce  supply chain capacity across the industry.


The main data bands that mining companies have to worry about are maintenance and asset information, geological and geospatial, environmental, process control and automation, production and throughput/tonnage and then the usual financial, supply chain.


The BIG DATA can assist mining industry in the following ways:-


  • Mining feasibility study with mobile GIS mapping and scanning machines
  • Tweaking the flotation process which may increase the recovery of rich metals like Gold trapped in the ores like copper concentrates
  • Providing the real time field information from the site like tracking a particular transportation  route of a truck in order to optimize the route distance and wear and tear of the truck tyres
  • Understanding the operational capabilities towards forecasting on the returns over the mine construction
  • Identifying a flaw in the machine or process that can be tightened up to ensure greater savings and productivity increase
  • Helping in procurement and supply chain processes for e.g. one mine site can have many suppliers for a single material, imagine the waste there, rather they can have one major contract across all sites.



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