Like so many industries, mining and metals enterprises are going through huge changes. I recently connected with Emerson’s Thishen Naidoo, a heavy industries marketing leader for the machine automation solutions portfolio. Here is our exchange of his interesting and problem-solving take on the current state of mining.
Jim: Thishen, what would you say are the driving issues in mining today?
Thishen: Mining, like all major industries, faces the need to balance shareholder value and sustain profitability with an increasingly stringent environment and societal pressure to operate more sustainably, as well as the all-too-familiar rising skills gap and fluctuating market demand. It’s a tightrope.
The skills gap continues to widen as many experienced personnel approach retirement and exit the industry, while the current societal perception of mining has made it even more difficult to attract and retain a new and younger workforce. Mining operations are becoming increasingly remote to compound this issue, and mining enterprises realize that automation is the key. Remote operations centers are becoming more relevant for continuous operation and paving the way for fully autonomous mine operations.
But deciding the most efficient, cost-effective, risk-free way to automate and future-proof that automation investment are the questions every mining enterprise needs to ask.
Jim: And should they be thinking outside the box?
Mining generates a huge amount of data from sensors on machines and widely distributed systems. This data could and should be informing everyday decisions. Better data connectivity and analysis lead immediately to improved operational uptime and asset utilization, enhancing productivity and product quality. The question is how to do it in this industry characterized by remote locations, disparate assets, and complicated connectivity.
The solution is familiar and remarkably simple. Edge technology.
Traditional programmable logic controllers (PLCs) have typically formed the front-line operational technology (OT) automation platform used throughout mining operations. These devices are commonly used for real-time control, but only more recently have been tapped for implementing higher-level IIoT communications and analysis. This change is enabled by improved IT computing methods which are merging with OT platforms, resulting in capable edge-located IT/OT controllers. Data available at the operational edge is now easily accessible and able to be processed and transmitted, paving the way for analytics and optimization deployments.
While edge technology is available from simple gateways to edge computing systems that can be added to existing PLC-controlled machines, one of the most interesting advances is the edge controller. An edge controller combines a real-time operating system (RTOS) with a general-purpose operating system (OS) like Linux. The RTOS provides direct deterministic control and monitoring of field equipment, much like a PLC or RTU. In fact, edge controllers can be used just like PLCs, even if users do not immediately take advantage of additional features, providing a future-proof design.
The general-purpose guest OS enables capabilities such as advanced computing, analytics, and data storage. In addition, the general-purpose OS offers much more capable communication options, even over the low-bandwidth connections commonly encountered with mining operations. This means that hard-to-capture data can be collected and analyzed in the field, while pertinent results are sent to central control or even enterprise levels. Edge controllers can be integrated into existing systems to provide new capabilities without disrupting proven operations. Or, edge controllers can provide complete control, monitoring, and analytical solution for new installations.
Jim: Can you give us some examples of how edge technology can solve specific problems for mining?
Thishen: Managing ore characteristics and variability are a key challenge after it is extracted from the ground because optimal downstream processing is very much dependent on ore size and quality. The initial material handling and conveying processes use large mechanical equipment which can be prone to failure if large fragments of ore pass through the system undetected. Therefore, the ability to track ore size as it progresses through processing helps mine operators identify conditions that could potentially cause downstream blockages or mechanical breakdown of equipment, resulting in hours of unplanned downtime.
By leveraging a combination of sensors, instrumentation, and edge controllers, the ore loading on conveyors can be analyzed. Live parameters, like conveyor belt tension, can be monitored and analytically compared with historic data. Potential deviations can be quickly identified, and the control system can intervene to prevent a downtime incident. This is an example of taking the huge lake of big data and transforming it into “little data,” highly informative analysis pertaining to one problem that drives smarter decision-making to achieve incremental value across a particular system or the entire mine site.
You can optimize energy or analyze vibration the same way, as an individual edge control problem.
Solve enough specific problems with edge control and you have automated and optimized a mining operation!
Bottom line is that edge architecture is a smarter way to automate for mining companies. As the industry continues to shift to integrated and remote operation centers, any useful technologies must be suitable for these conditions and provide extensive communication options. Edge controllers are built for this OT environment and have the latest and most secure IT computing and networking features. Edge controllers are especially compelling for this service because they can gather and store data locally, process and analyze it, directly inform operational logic of optimal settings, and relay the most essential information to higher-level systems. That’s thinking at the edge.