Data Islands to Digital Gold: A Practical First Step Toward Integrated Mining Operations

Here is how a conveyor downtime story might unfold. An emergency stop was triggered, an operator looked at the error and realized that the system could not be restarted from the control room. A field engineer was sent to the location and started the troubleshooting process. As the troubleshooting process went forward, the engineer needed to ask three different persons to find the conveyor’s historical data: data trends prior to breakdown, last maintenance performed, accumulated runtime since last down time.

I admit, I did overdramatize the story. However, I would argue that it does feel like things can be better. What if the engineer can just ask the same operator all the questions he had? However insignificant it might feel, it does give a sense that the workflow can improve. What if the operator could provide more context to the engineer when he reported the down time in the first place. The moral of the story is, if you would bear with me, data is often available but spread all over your organization. Addressing this issue has a potential improvement in operational efficiency.

Mining operation is comprised of so many moving parts and each involving equipment, each with their own system. Integrating data between these parts can transform operations. Organizations can start to look into safety enhancements, predictive maintenance, operational optimization, better resource management, environmental compliance, and ultimately strategic decision making. All industries are now pushing for industry 4.0 and digitalization efforts. These efforts ultimately aim for this data integration. In the mining setting, location and environment situation can present different challenges compared to other industries. Therefore, choosing the right path towards data integration should be done strategically.

Start small, think big

It is not wise to just buy the latest technology or the hottest trending technology. We should always look at what we have first. This will keep the effort grounded and help us identify and prioritize on parts we want to integrate. We can ask ourselves what equipment do we have, what data points are available, and what is the most critical data to get first. Different equipment come with different system components and data availability. One equipment might have controllers of a certain brand or even their own OEM controller. There might also be different supported communication protocols. These assessment questions will dictate what technology we can use further on.

The assessment will provide us with information on what data acquisition strategy we should have. One option would be to retrofit sensors if you have old equipment that don’t have outputs we can utilize. You can add vibration sensors, temperature probes, proximity sensors, or other sensors that might fit.

If your equipment support industrial protocols like modbus, profinet, OPC classic, or OPC UA, then you are in a slightly better position to integrate your data. A main ventilation fan controlled by an industrial programmable logic controller (PLC) can have its data extracted relatively easy as long as its data is well documented and OEM support is available. Otherwise, a well-planned observation and reverse engineering can also be done.

In the mining industry, it is not rare to have the site located in a remote area. Edge devices that act as a gateway to a centralized server is also one solution to overcome the remote area location. The device can be equipped with remote connectivity, protocol conversion and data buffering.

The next step after your priority data is acquired would be to choose the integration platform. You might not need to look too far. It is possible that you already have a decentralized control system (DCS) or supervisory control and data acquisition (SCADA) available on a certain area. If you do, it just a matter of expanding it. The constraint would be the number of licenses available, you might need to purchase more licenses. The main characteristics of a platform software is its capability to acquire data from the field (your equipment), store them in a certain way, and have them accessible to your IT system. In fact, there is now a SCADA platform with such characteristics which doesn’t have tag license limit so you can expand your platform with only your server hardware as its constraint. The platform is called Ignition SCADA by Inductive Automation. The integration platform should also have analytics and visualization features.

These two steps should put you in a good position to further drive your data integration and digitalization efforts. Data integration and digitalization can be challenging if we take too big of a step initially and don’t get all stake holders on board. Starting small can be a solution to this issue. There are also cybersecurity risks that need to be mitigated properly. Lastly, you need to choose the correct team and partner to accompany you at every step of the effort, all the way to the finish line. 

By integrating and digitalizing our operational data, we can eliminate situations where critical information remains fragmented across systems and teams. Returning to the earlier conveyor downtime scenario, we can imagine operators and engineers accessing equipment history, maintenance records, and performance trends from a single trusted source, enabling faster troubleshooting and allowing us to address operational disruptions before they escalate into costly downtime. Instead of pursuing large-scale transformation from the outset, we can start by prioritizing the data that matters most, leveraging existing infrastructure, and expanding integration step by step, gradually transforming isolated data into actionable insight. With the right strategy, technology, and implementation partner, we can build a connected data environment that supports safer, more efficient, and sustainable mining operations, ultimately turning our data islands into digital gold.