Plant + Industry 4.0: the applications: Part 2
This is the second of our blogs looking at the applications of Industry 4.0 AI + IoT technology with plant - you can read Blog 1 here.
There are more applications for Industry 4.0 AI + IoT technology on plant than we could possibly list (but we're trying). Here's part 2 of our Industry 4.0 AI + IoT Plant Applications list:
Proximity alerts + real-time Permit to Work. Many injuries and plan failures occur because people are in the wrong place at the wrong time, doing something that they shouldn’t be doing (e.g., using plant close to electric cabling), or through an unforeseen failure resulting in an action, such as inundation, gas explosion or rock fall. An AI + IoT platform enables miners to, via the use of wearables and the real-time monitoring of plant and environment, aggregate data in real-time and identify when someone is going to come to harm, sending alerts to clear areas and stopping machinery before an injury occurs.
Plant, mine, factory and cross organizational analysis + data silo busting. The aggregation of data from multiple sources across an entire organization makes it possible to uncover best practices, identify superior plant (e.g. by brand, age, model etc.) and operational methods used by different individuals, highlight top performing personnel and teams, as well as identify areas for improvement based on much larger data sets. This works at the short-term, site level, but will also improve longer-term results by guiding optimizations (e.g. better staff training or plant configurations) 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 leverage the ability to operate machinery remotely and leverage superior skill sets is an obvious one. Through the use of detailed data analysis, it is 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 and be potentially put in harm's way on transport or other on-site activities (e.g. moving amongst unmanned vehicle operation). The centralization of expertise can be a business risk, but with the right technology and approach (e.g. the setting-up of a center of excellence to spread them), it can become a benefit.
Improved training opportunities. An integrated AI + IoT platform makes it possible to monitor the impact of workforce training initiatives, make simulations more realistic by utilizing more data sources, as well as spot individuals who need further support in particular areas of their role by comparing the performance of employees both before and after training via the use of productivity and safety score measures. With a strategic viewpoint, it’s possible to then identify types of training that do and don’t work, providing real data that makes it possible to improve regimes, schedules and optimize the time that workers spend away from production activities.
Process optimization (Digital Twinning). 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 plant 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. As long as there is a way of measuring success, then any scenario can be tested and it is through digital twinning (plus the application of multiple machine learning algorithms to uncover which is the best in predicting and optimizing plant operations) where Industry 4.0 status can truly be achieved.
Aggregated risk profiling + improved productivity measures. The operation of certain types of plant at very high temperatures isn’t a problem in itself, but it could be if the external temperature rises beyond norms or an external heat source, such as a welding torch, is applied in close proximity. Using an AI + IoT platform, it’s possible to 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; as well as model their impact on productivity and efficiency, thereby enabling production to be optimized.
Energy & Fuel Tracking + enhanced operational schedules. With large real-time data sets from plant, 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 it. 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 etc., as well as other potential applications including rescheduling of usage to prevent restarts and short stops. One study found that, through providing direct feedback to operators, it was possible to drop fuel consumption by 7% in just 8 weeks*.
Theft + loss protection. The theft and loss of plant is a significant cost to miners that directly affects the bottom-line through both OPEX and CAPEX - not to mention higher insurance premiums. The real-time monitoring of plant enables miners to set-up geo-fences, alarms and alerts that are triggered should a piece of plant be where it shouldn’t or if being used in a manner inconsistent with its rostering that may foretell its loss.
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 reporting burden, the retention of knowledge and freeing team members from repetitive work to focus on other aspects of their role. It also makes it easier for management to adopt competency-based risk management practices, ensuring that they have the full picture when it comes to plant performance and make better decisions that will enable them to achieve strategic goals.
The thing that all of these benefits have at their center, though, is the correct application of technology; namely an AI + IoT platform that has access to the right data in real-time from all potential sources via extreme interoperability, which is then coupled with in-field real-time sensors to, comms and networks, and other plant-related technologies.
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.
* Source: https://www.bcg.com/publications/2017/metals-mining-value-ai
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.