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Where to start with Industry 4.0 technology to achieve mining ESG goals.
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SDG and ESG goals can be both broad and specific - Industry 4.0 technology can help with them all, but knowing where to start can be difficult.

 

The first step is to Identify a particular objective or function that needs improving which can be used to test efficacy, as well as an individual (or small multi-disciplined team) who will be capable of championing and running the project.

For example, a common place within the mining sector to start with Industry 4.0 technologies in ESG is with real-time environmental monitoring and predictive analytics. The reason for this is that it can prevent the breaches that can turn into long-term stewardship difficulties, plus enables miners to start collecting the complete, authoritative data sets that are needed to model future optimizations, compare outcomes from different activities, enhance EIAs and SIAs, as well as plan better for the future.

From there, it’s important to explore the use case for Industry 4.0 technology. With real-time environmental monitoring and predictive analytics, it would be best to pick a particular activity and site, before then identifying all of the potential variables that impact the use case and where the real-time data gaps are, such as with the real-time collection of noise, dust, smell, subsidence, vibrations, gas release, light (etc.) data. Is there certain data that cannot be collected at this stage? Is all the data needed readily accessible in real-time? What’s the internal skills gap when it comes to the necessary technology, implementation or data analysis and use of AI?

At this point, if it’s not already occurred, it is prudent to look for the right suppliers. Critical to developing an Industry 4.0 footing is an AI + IoT platform, so this should be the starting point. Utilizing someone that has an understanding of mining operations and good cross-functional technology and data science expertise is going to be critical, as many providers are industry agnostic or lack the in-depth understanding of a sector to add value during solution development. 

The next step would be to further explore the technology stack that is going to be needed. Central to this will be the in-field devices needed, integrations with systems (both internal and external), as well as the networks and comms necessary to transmit data to the AI + IoT platform and then carry back to the Edge the instructions that are directed as a result of its real-time analysis (if Edge processing is not being leveraged). What’s more, it’s also important to begin developing (or buying) the machine learning algorithms that are going to be used to predict environmental performance -there will be multiple options.

Once the full technology stack is identified, it’s about the deployment, roll-out and internal communication/transition plan. Every site and piece of plant is unique, but there are commonalities across classes, mines and operations that can be applied to every situation and across projects.

The best approach is to start small and scale. Pick an easy-to-monitor use case without too many variables, where improvement can be clearly measured, and look to apply it to a single site. This enables the rapid deployment of technology (sometimes in weeks), reduces costs and risks, and provides a pilot program through which data is beginning to be collected (bigger data sets = faster optimizations and quicker success).

Once making a measurable impact, it’s time to scale across other on-site activities and multiple sites to capture bigger data sets from across operations. By scaling at this point, it will be possible to utilize the learnings from the pilot to find efficiencies and enhance the optimization loop almost instantly. What’s more, by working with a partner that can work over the longer-term and, critically, knows how to scale will reduce costs, speed-up the deployment process, and reduce further development cycles.

Work with someone who is a digital native, can explore your operations in relation to your business objectives, who understands the sector, knows the current technology, and has a global network of best-in-class partners who can provide you with the future-proofed technologies that you need to create complete Industry 4.0 solutions.

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I4 Mining is a suite of digital mining solutions built on our world-leading data consolidation and AI + IoT platform, Dynamix, designed to help miners quickly adopt Industry 4.0 technology and succeed with key strategic goals. Featuring pre-built sector-based logic, AI and enterprise-level functionality; our solutions can be deployed and performing in the field in weeks, enabling miners to begin their transformation ready for a 'zero' future.

Speak to us today to discover how our fast-to-deploy, highly-flexible & commercially viable at-scale digital mining solutions can deliver your business with measurable results now and ensure profitability into the future.

1516837264925

Phillip McBride

CSO & Technologist @ Rayven
phillip@rayven.io
LinkedIn

Want to know about industrial AI + IoT more broadly?

 

If you'd like to find out more about the technology that underpins all of our digital mining solutions, other industrial uses of AI + IoT, or are eager to get into the detail of precisely what AI and IoT technology are then visit the Rayven blog.

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