The Device Chronicle interviews mining product management and machine data expert Kristy Garland on the impact of IoT and embedded software / hardware on the mining industry.
Kristy is a product management expert who understands the impact of IoT connectivity on the mining industry. She currently consults for Coleman Research. Kristy is also a subject matter expert within the expert network for mining and heavy equipment concerning IoT sensors, networks, filtration, and application SaaS. She also has extensive experience in IoT product management from her time at Komatsu.
Use cases for IoT connectivity & embedded hardware/software
Kristy begins by explaining that IoT sensors are in different pieces of mining machinery. The goal is to optimize process operations. These sensors collect real-time telemetry, location and position information, and fault information. This data underpins the here-and-now analyses of what operations and mine management can do and what this data shows as the next actionable item the operator should take.
Although the IoT sensors produce the raw data, an application, such as a productivity or machine maintenance program, analyzes it. Many visualization programs also help take this vast array of data and turn it into actionable information.
The frequently asked question is: Why would a mine invest heavily in this type of technology? Kristy answers “It's all about the data. If there is a problem, it can have catastrophic results: such issues could include a truck running off the road and an operator getting injured, causing severe financial damage. So, mine operators look for this data for several reasons. “
The first reason is root cause identification. Reliability engineers can pinpoint specific problems and implement targeted solutions by analyzing the data from these various sensors. This proactive approach extends the machinery's lifespan and optimizes operational efficiency, ensuring the equipment remains in peak working condition for extended periods. There's also condition monitoring. And so, what that is is continuous monitoring of the condition of the component rather than relying solely on time or operating hours to go ahead and perform scheduled maintenance. By facilitating this early detection of potential failures, the operator can address them before they escalate into significant problems. The reverse is true, as well. Asset owners want to get the maximum life out of these components. Another perspective is that they don't want to replace components that still have a lot of usage left in them.
Kristy explains that many third-party programs will allow mines to set customizable alarms and collect data. “They're looking at a specific project, or they're looking to optimize the usage of these machines. In that case, the mines can set specific parameters for monitoring the anomalies and the conditions beyond what the OEMs typically provide.” An example is detecting abnormal vibrations in a hall truck's engine so the operator can alert the maintenance people for corrective action. The operator can apply this "uniqueness" to the mine's location, operating conditions, and current fleet.
Also, by collecting all this data, the mines can have a comprehensive data asset for all machines. It can provide detailed information on how they react during loading, hauling, and even your non-production machines, such as water trucks, dozers, graders, drills, and other light vehicles. Regardless of the OEM, the system will consistently provide a basic level of information so that you can look for trends. “Are you having an operating issue at this particular place on the hall route? Is one operator operating these differently than another? Is somebody hitting the fuel pedal too hard, and the velocities sharply increase? How even is the payload distribution from machine to machine and operator to operator? Of course, there are many, many more scenarios.” Overall, the uniformity in the data collection helps streamline fleet management and operational planning.
Edge devices used in data collection
Kristy defines “Edge devices” as devices on the machines themselves, instead of a computer connected to an office building that gets that information via the cloud.
She describes four different types of edge devices:
The first one is intelligent sensors. These are the "eyes and ears" of the mining machines. “They are the ones who do the heavy lifting and monitor the conditions, for example, around the machines, such as temperatures, pressures, humidity, air quality.” A good example is temperature sensors, which can detect the overheating of machine parts when you're looking at them from the machine's perspective. And they can trigger an alarm or even cause a shutdown if there is an impending catastrophic failure. Similarly, air quality sensors can detect harmful gasses or dust particles, ensuring the safety of the workers and compliance with environmental regulations. These sensors generally connect to a network, enabling real-time monitoring and data analytics at the edge.
The second one is intelligent actuators, “like the muscles in your body.” They convert all these computer signals into physical actions. “A smart actuator would adjust the coolant flow based on data from the temperature sensor, thereby preventing the machine from overheating.” Another great example is a hydraulic actuator that can control the movement of a drill or an excavator based on the operator's commands. These actuators also provide feedback to the control systems, enabling your closed-loop control for more precise and efficient operation.
The third one is the IoT gateway: these are the communication hubs for the machines themselves. They collect all this data from the various sensors and actuators and then transmit it back to the network. Some of these will perform initial data processing, such as data aggregation, filtering, and data compression, reducing the amount of data that needs to be transmitted and improving the network efficiency. Moreover, they also implement security measures, such as encryption and device authentication, to protect the network from cyber threats. And lastly, you'll see edge controllers. These are the "brains" of the mining machines. They combine real-time operating systems with a general-purpose operating system, such as Linux, and allow the systems to handle both the time-critical tasks, such as controlling actuators and the non-time-critical functions, such as data analysis and communications.
The fourth one is edge controllers which can also process and transmit data in real-time, enabling analytics and optimization deployments at the edge of containers.
Business insights garnered from an IoT platform
Kristy explains that IoT sensors are revolutionizing mining because they provide the underlying data for actionable insights. They fall into several buckets, with the two most important ones being operational efficiency and preventative maintenance.
For operational efficiency, the goal of the mines is to have these mining machines available most of the time. Kristy explains “Mining machines are very expensive. They are in the tens of millions (of US dollars) for some machines. It's not uncommon to see the "golden girls" out there. These are the pieces of machines that are 20 and 30 plus years old by the manufacture date, but they're still running production.
The mines are also getting forced to increase output with either what they have currently for their fleets or even sometimes with less because a machine may have a fatal error that's going to take some time to repair, or they may need to take a piece of machinery and have it be "on loan" to a sister mine because that mine's particular operation is more profitable than say another one.
The mines are trying to do less with more, and trying to understand how to fine-tune processes. They ask "what can they tweak to get an extra 2%, 5%, 10%, 12% more production from the same machines?”
Kristy explains that you'll see the mines looking at hang times at the queue for haul trucks. They ask questions such as how long does the haul truck wait before that shovel is free to start loading that truck? They'll look at how long it takes to refuel a particular truck because when you're refueling it that truck is not in operation.
Mines also look at some of these safety requirements. For example, they will look at how often a particular operator falls asleep at the wheel. “Now, this isn't drunk driving - somebody's out for 5 minutes. Rather, these are little micro maps. These events last fractions or even up to a couple of seconds. Suppose you're looking at a haul truck, and that operator shows signs of falling asleep. In that case, that can create a very, very hazardous situation for that operator and operators around them who might be passing them on their haul cycles.”
Unplanned maintenance is an important use case for IoT sensors because maintenance is expensive. On one end of the spectrum, you'll have people who will do it only when there's a catastrophic event—an engine blown or seized, or a haul truck tire exploded. That means the maintenance people have to stop what they're doing, figure out where that truck or piece of machinery is, and then repair it immediately.
Predictive maintenance is much more beneficial, including when you see temperatures rise or fuel filters plugged, so you can take that machine out of operation when it's most convenient instead of shutting it down. There's nothing further you can do. The other side is that you always want to avoid - replacing components too far ahead of time because your manual says you need to do this after so many hours.
Device cybersecurity from the cloud to edge in mining
Kristy recalls that there have been news releases where “mine XYZ has shut down because it suffered a cybersecurity attack or somebody got in and turned off the machines or stole data.” Kristy then elaborates on the security challenge for mines: “Now, one of the particular struggles the mining companies are handling is that digitizing these operational technology networks is far less mature than what one would expect in their corporate IT networks. What the mines are all doing is coming up with ways to prioritize threat detection and response, and what they're looking at is they can correlate threat indicators and continuously analyze the network environment to look for user behavior anomalies. An example is multiple attempts to get into a network on an off shift, or - somebody coming in through a third party sensor or breaking into the network other ways which can cause huge ramifications, such as shutting down production.
Mines are now building up their own internal cybersecurity expert pool. “These experts will work with other experts from either the same mines or different mines to see what best practices are emerging. Unfortunately, there are still many interpretations of different guidelines, which makes this all a bit fuzzy for them.”
As the industry matures, Kristy believes that there will be more funding, and more groups will form to minimize these attacks. “Right now, you'll hear Microsoft talking about zero tolerance, which means that you don't trust anybody trying to get into the network, and you verify that they do have the credentials to be there.” The zero trust frameworks hold the premise that you do not allow everybody the “keys to the kingdom”. Access should be restricted to the highest levels to only those who must have and need access. Of course, beneficial things, like data backup, have been done for many years. By monitoring the networks and fostering these cyber cultures, the best defense against cyber attacks is the people themselves.
OTA software updating
Kristy cautions that one of the potential significant sources of downtime has been caused by deploying software updates for the mining machines, and this can be anything from the machine controllers themselves to subsystems such as engines and drivetrains; and third-party systems from Komatsu Mining, Caterpillar, Liebherr, and Hexagon, for example. Kristy believes what has to happen is there is this desire for OTA updates because you don't have to take the machines out of production and wait for the next maintenance rounds. And this risk reward has to be weighed against the nature of those updates. “Can the networks be secured enough to go ahead and do those updates? The older the systems, the more likely they could be attacked, so the mines need to do a risk assessments. Mines cannot handle having extended periods of downtime, as it is very exepnsive. One of the kind of surprising numbers is for a diamond mine - an hour of downtime can cost the mine upwards of $70,000 USD dollar per hour, whereas, in a coal mine, that number may be in the $40,000 to $50,000 USD dollar range. The goal is to update the machines quickly and can the mine networks handle that.”
Still, Kristy concludes that there is the move to OTA while being cognizant of the vast cost and how quickly they can add up when you take the machine out of production. “We need technologies to do the remote updates securely and robustly while optimizing the uptime of the machinery.”
Reach out to Kristy on LinkedIn.