Mining ESG Industry 4.0 AI + IoT use cases: Part 3 - Holistic operational analysis.
This is the last in a series of three blogs examining the different applications of Industry 4.0 technology in solving the mining sector's SDG and ESG goals.
In this final blog in the series, we look at the strategy and analytical advantages of using an Industry 4.0 AI + IoT platform that's capable of both adaptive and predictive analysis of your complete operations - all in real-time.
Holistic operational performance:
Complete environmental performance transparency + accurate carbon accounting. Through the use of an Industry 4.0 AI + IoT platform, mining companies are able to more accurately monitor and track their carbon (and any other material’s) environmental footprint through leveraging data from in-field devices, advanced plant, and business systems. This can be enabled to provide real-time insights, compared to benchmarks, and through the use of machine learning, future performance predicted across assets, personnel, sites and entire operations.
Improved Environmental + Social Impact Assessments (EIAs & SIAs). The collection of accurate data from multiple sites and the monitoring of environmental performance over time based on different operational factors enables miners to leverage historical data to better establish baselines for future EIAs and SIAs. Not only this, by leveraging exploration data and modelling, as well as future operational plans, an AI + IoT platform can provide miners more accurate predictive insights that allow them to better plan their operations and post-closure remediation efforts.
Process optimization (Digital Twins). Current best practices in mining are reliant on doing the same thing, day after day; with every individual following the same steps, processes, and patterns. This makes the analysis of deviations in current practice in an attempt to find better ways of operating difficult because those are the very behaviors which are trying to be avoided. With digital twinning, it is possible to test new models or set algorithms with the task of analyzing all the current variables and finding better ways of functioning without risking harm, efficiency or productivity. This enables miners to explore low-impact mining techniques and impact of different rehabilitation efforts risk-free -as long as there is a way of measuring success, then any scenario can be tested.
Plant, mine, country + cross organizational analysis. The aggregation of data from multiple sources across an entire organization makes it possible to uncover best practices, identify superior assets and plant (e.g.by brand, age, model etc.), as well as identify areas for improvement based on much larger data sets. This works at the short-term, site level, but also will improve the environmental results being made via longer-term optimizations (e.g. better staff training) and takes away the barriers that sometimes exist between departments and business units.
Remote operations + superior skill set identification. The application of industry 4.0 technologies to achieve the ability to operate machinery remotely and leverage superior skill sets is an obvious one. Through the use of detailed data analysis, it is also possible to examine individuals’ performance who conduct similar functions in a business. By doing this, organizations can understand what it is that makes them better so that they can upskill a wider workforce, or even set-up remote control and operations rooms that enable top performers to conduct their highly-skilled roles across multiple sites without ever having to visit sites, again reducing secondary and schedule three environmental impacts.
Aggregated risk profiling. The operation of certain mining techniques might not be an immediate environmental hazard in itself, but it could be if the external temperature rises beyond norms or wind speed reaches a certain measurement. Using an AI + IoT platform you can create algorithms that can explore the impact of certain activities and provides the ability to create accurate, aggregated risk scores that can’t and mightn’t be foreseeable.
Improved emergency performance. Using an AI + IoT platform, it is possible to analyze how previous incidents occurred and the effectiveness of previous responses. By creating a score for each individual aspect, businesses can analyze where improvements can be made and decrease the likelihood of a spill becoming a major environmental event in the future.
Long-term performance pattern analysis. An Industry 4.0 AI + IoT platform makes it possible to analyze data sets across sites to identify and predict environmental performance. Through identifying patterns (such as how long it takes for an asset to start or whether it does better at a certain time of day), you can use these insights to further enhance environmental outcomes by changing shift patterns and ensuring that the correct personnel or skills are on-site at the right time.
Improved training. It’s possible with an AI + IoT platform to monitor the impact of workforce training initiatives, identify what does and doesn’t work, as well as spot individuals who need further support with environmental compliance by comparing the performance of employees both before and after training via the use of real-time monitoring and the aggregation of data from other sources, such as productivity and output measures.
Energy & fuel tracking + enhanced operational schedules. With large real-time data sets coupled with pertinent other data (such as outside temperature, operator action, maintenance regimes etc.) it is possible to utilize machine learning within an integrated AI + IoT platform to spot patterns and uncover the most efficient ways of operating individual pieces of machinery and entire operations. Taking this a step further, the insights delivered can be directly inputted into automated plant to seize benefits, via instructions and alerts to operators (in real-time) to slow down, for example, as well as other potential applications including rescheduling of usage to prevent restarts and short stops.
As the trend to mine lower grade, larger tonnage deposits continues, the application of these and other Industry 4.0 AI + IoT platform use cases will be critical in enabling the mining sector to achieve their ESG and sustainable development goals.
There are numerous other applications and potential benefits that can be derived from the use of Industry 4.0 technology, such as reducing the manual and error-prone reporting burden, the retention of knowledge and freeing team members from repetitive work to focus on other aspects of their role -making it easier for employees to consider environmental risks and apply best practice correctly. It also makes it easier for management to adopt competency-based risk management practices, ensure that they have the full picture when it comes to real-time environmental performance and make better decisions that will enable them to achieve zero harm, zero waste and zero carbon goals.
See the 1st part of this blog here for Enhancing operational performance use cases.
See the 2nd part of this blog here for Real-time personnel, environment & plant monitoring use cases.
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.
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.