Material process flow plays a big role in the mining value chain. This includes analyzing impact of unscheduled events owing to mechanical breakdowns of LHDs, trucks and critical transportation
medium, queuing time, and such overheads. There are a number of other causal variables that can be analyzed for impact on production throughput on a daily/monthly basis using techniques such as Machine Learning, Continuous Pattern Matching and Statistical Predictive Model.
Big Data Analytics Platform, equipped with these models, can leverage the value, volume, velocity and variability of data, delivering several benefits across extraction, intermediate transportation and final transport to plants.
Top 10 Use Cases For Big Data In Mining, Courtesy Of Mining Journal - 2015 February
05 Dec 2014 - Mining Journal Feature
Exclusive Mining Big Data Guide now available
The first comprehensive Mining Big Data Guide, just published by Mining Journal, suggests results of a survey by MJ in the first half of 2014 was on the money: big data, and big data analytics, will be transformational for the industry over the next 5-10 years.
You can download the guide from the web page
Big Data Benefits in Mining Industry
By CIO Review, 17 March 2014
1. The connected mining enterprise – the internet of things
2. Mining for millions – procurement
3. No more surprises – predictive maintenance
Updated 26 February 2017, 26 February 2016