How the Internet of Things (IoT) will shape workforce development strategies
How IoT is reshaping the mining industry
There is no doubt that the Internet of Things (IoT) is going to reshape the mining industry and its workforce. Indeed, more and more operations are rolling out IoT projects; in 2018 it was only 2% of mines, now it is 65%! We are now finding that many of the start-up projects we are consulting with are considering just how IoT will affect their workforce development strategy.
With 5G networks (handling up to 20 gigabits per second of data) being rolled out, the possibility of data exchange between ‘things’ on a mine site in real-time without congestion means planning for a `smart mine’ needs to occur now.
But what does IoT look like in terms of training and workforce development? There are two sides to this. Firstly, we need to consider what a future workforce looks like and, secondly how IoT effects training and competency management. So, let’s peer into the future…
The future workforce and predictive maintenance
IoT is about data. That is, grabbing data from all parts of the operation and other sources through sensors and monitors. The data can be used however one can imagine but a key aspect is in predictive maintenance.
As a simple example, sensors on a water pump in the field can send data back to a computer at HQ so maintenance can see in real-time the condition of the pump. Furthermore, the system learns and determines what normal conditions are and when failure will occur. It could order a replacement for the worn component ahead of time, or even print one.
From a competency point of view, the maintenance team will need to understand (beyond moving a mouse around) the parameters, a basic understanding of pump components, alarms and response, back-up procedures and be able to communicate. But the same team could be monitoring 100’s of different moving components on the site (or multiple sites).
What this means is that these personnel will be generalists but with technical competencies as opposed to specialist pump maintainers who have traditionally been non-technical. They are the ones that drive out to the pump, set up their alignment and diagnostic gear, and use their 5 senses to gauge the condition. Skills that shouldn’t be discounted but take a long time to develop.
Training and workforce development
Given this scenario, if monitoring occurs remotely and predicting failures becomes computer or algorithm-based, then maintenance workers may not be required to be out in the field as often. This would mean that many of the `fringing’ competencies can be removed from their individual training and competency plans.
Additionally, the system will generate a component change out procedure that is specific, detailed and simplistic. No guess work or know-how is required. Therefore, the traditional 3+ year trades training does not necessarily apply, only basic mechanical maintenance principles coupled with the application of quality standards is required.
IoT and other technologies are really going to change workforce development strategies and, in most cases, reduce the lead times and training burden. As an example, it traditionally takes 2 to 4 years for a London Cabbie to be deemed competent. Now with Uber, it takes about 4 days! They both perform the same task, although quality standards may be another issue.