By Andrew Crose, Director of Sales, EMEA
The world is awash with sensors. On my wrist alone, I’ve got GNSS, barometer, altimeter, accelerometer, sleep monitoring, and HR monitoring. My watch probably knows more about me than I do.
Mining is no different. Many call it the digital era, which seems odd as I don’t remember people extolling the analog era. That aside, we are in an era of significant available data. The question we should therefore ask is, are we getting the most out of this data?
Full disclosure, I’m not a mining engineer. I studied (among other things) the art of information systems; basically, the fancy term for developing databases, understanding processes, and creating the reports that align to the KPIs of processes measured by data. While my studies began at the crossroads of analog to digital, flat files to relational databases, the underlying principles remain the same:
In the analog era, this creation of data was fairly straightforward. Binary On/Off, 4-20 milliamp, etc. supplied into industrial PLC systems with basic reporting out. Crude, but effective. Digital systems allowed significantly greater depth of data, beyond binary to continuous spectrum, time series, stored in queriable databases. What a great leap forward! But, are we getting the full potential from this data?
Here are a few examples of how, with a bit of creative thinking, secondary data can create as much, or nearly as much value as the original intent of the sensor.
The value of secondary sensor data
GNSS: Seemingly everything has a GNSS sensor on it today. My watch, my phone, my car, etc. In mining, GNSS is used on survey equipment, fleet management, collision avoidance, and more. One simple function that is frequently neglected from KPI monitoring is the auxiliary fleet performance. Graders, water trucks, dozers, and secondary waste fleets all still typically go about their work with little or no real-time digital oversight.
Tracking auxiliary equipment, such as a collision avoidance system, is a perfectly sound use of GNSS data.
However, in mines with GPS systems on their auxiliary equipment – from a collision avoidance system, for example – the tracking of that auxiliary equipment is a perfectly sound use of GNSS data. How many hours did that equipment run? How many kilometers did that grader grade? Apply additional data, say from a digital i/o, and you can track how much water the water truck sprayed or whether the excavator was digging or simply running.
Accelerometers: Many devices have accelerometers built into their system that you may not even realize. Accelerometers are relatively cheap to engineer into a device, so many manufacturers just add them without realizing their full potential. For example, an accelerometer can be used to awaken a dormant IoT sensor to reduce battery drain after it has gone into sleep mode to conserve power. Harness the power of an accelerometer as secondary data on a haul truck and match it with the GNSS location from another sensor, and now you know where your haul roads need improvement. Bumpy roads cause slow trucks, and this is an easy win from secondary data.
Tire pressure/Temperature, Engine RPM/Gear, Fuel Monitors: Generically speaking, these systems exist to warn the operator in real time whether the tire pressure and temperature are too high or too low. They allow immediate action to be taken to avoid tire damage and potential safety incidents. What is the engine RPM and should the operator shift gears? What is the fuel level, and when should the operator refuel? When matched with GNSS and haul road segments, these alerts can provide a wealth of knowledge. Is a road segment designed too steeply and causing inefficiencies in the equipment? Is the operator untrained and operating in the incorrect gear? Capturing this as digital data and analyzing the secondary benefits can reveal many potential improvements.
Time: Let’s never forget time, the original digital master (back to my watch). By measuring these sensors against time and across time correlations, theories can be tested and the effects of the time of day can be understood. One obvious example is measuring the performance of tasks in daylight versus night time: What an easy way to justify improved lighting! Additionally, how is performance this time last week, this day of the week versus other days (the Monday/Friday effect)?
Clearly, we are only just touching on the potential of digital data sources.
All of this is afloat in the vast sea of digital data being analyzed. After studying the use of data for several decades, we are still no where near the limits. The next generation of machine learning and artificial intelligence will only increase the usefulness of these data streams into new and meaningful ways that we haven’t even dreamed of yet!
I invite you to read Hexagon President, Ola Rollén’s discussion of our Xalt platform. I know we will be at the forefront of this revolution. It’s yet another reason I’m excited to be part of the Hexagon world, leading the digital strategies of those continuing to wonder what is next.
Andrew Crose, Director of Sales, EMEA
Andrew is a miner at heart and has participated in digital strategy, IoT, big data, and other technology initiatives with some of the world’s top mining houses. He is a Six Sigma Black Belt trained in process improvement on projects in the mining industry. Andrew brings more than 15 years’ experience in sales management and operations, with the last 10 years in the mining industry. He is responsible for the development, maintenance, and management of sales processes for the Operations’ product portfolio.