How to Achieve Sustained Value From Your Mining Data
Mining data is a massive opportunity area
In 2015 McKinsey Global Institute estimated a $370B opportunity for mining digitization by 2025. 70% of this value was projected to come from improvements in Operations Management - essentially using data to make better operational decisions.
Although this large opportunity exists, the Mining industry is still struggling to capture it. Recent research from Boston Consulting Group's Digital Acceleration Index shows that Mining is 30-40% less digitally mature than comparable industrial sectors including Automotive and Chemicals.
Mining companies recognise the potential of technology to create significant value for their businesses, but that they are not currently achieving much of that value.
The possible benefits that most operations are missing out on are in the range of 5-10% increases in throughput and 2-5% increases in yield and recovery. Solving the problem of effectively implementing technology solutions for the Mining industry therefore represents a huge opportunity space with a lot of value on the table.
The key to improving Mining Operations Management is a good operational data model
To make better operational decisions. You need to know how much your decisions are going to decrease unit costs or increase overall throughput.
The most critical piece of technology that Mines need is a platform that connects all operational parameters and decisions with dollar impact.
This isn't a new concept. We've been trying to do this forever under many different names - Mine-to-mill optimisation, Digital Twin, Value Chain Modelling etc.
This can be complex because the model needs to account for the entire value chain in order to function correctly for any part of it. For example, spending millions on speeding up drilling won't increase revenue if you are bottlenecked by the SAG mill anyway.
However, most models today are not delivering sustained value
Due to this complexity, bespoke models are often developed that are only useful for testing the viability of one decision at one point in time. They then sit on the shelf and are rebuilt all over again the next time.
This means that the value is often lost as soon as conditions change. The model no longer produces optimal results once geology changes or a new piece of equipment is introduced.
Additionally, these models are often developed and operated outside of the day-to-day tools used by engineers and operators meaning extra work is required to maintain them and implement their outputs.
This combination of factors often leads to lack of adoption on site and therefore a lack of sustained value being delivered.
Mines need real-time data being captured through existing day-to-day tools
Sustained value can only be achieved when a model is continuously being calibrated to recent data. Continuously calibrating a model with recent data is only practical if it's embedded into day-to-day workflows.
Manually updating data adds significant amounts of work to engineers, operators and commercial teams. This is a major reason why these initiatives often fail.
Automating data collection through integrations with all operational data sources and design platforms is the only way to ensure frictionless implementation of a continuous improvement value chain model.
Additionally, model outputs - optimized decisions and design parameters - need to be integrated with day-to-day tools. Focusing on the end-to-end user experience of decision makers is key for ensuring the value of the calibrated model is actually realized.
This is also critical for laying the foundations for more automated design and decision making processes that can unlock major productivity benefits.
New technologies are rapidly changing the mining, extraction, and construction industries, empowering them in ways never before possible. Make sure you're taking advantage of the best tools available.
Check out our 2 Free E-books on AI applications for the drilling, blasting, and mining industries to see all the amazing advances that are available.
AI Guide for Drilling and Blasting
AI Guide for Mining
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