In a data-rich industry, IoT sensors are the logical next step for mining truck fleet management, says Jamie Milne at World Wide Technology.
Big Data projects take place at the intersection of business, science and technology. For miners, who have long weathered tough environments in both business and nature, staying abreast of the latest connected technology can often provide the key to greater efficiency and better margins.
Miners have been collecting data and looking for an edge since the moment the sector became industrialised. However, identifying new opportunities can present a challenge, especially when trying to re-imagine facets of the mine operation that have not been overhauled in a long time.
When trying to deploy new technologies, outcomes must be at the forefront of any project manager’s list of priorities. When implementing a Big Data project, the primary source of value comes from the distillation of vast quantities of data into previously unknowable intelligence, so it is extremely important to know how each element, from hardware deployment to data analysis to business outcome, forms part of a larger whole.
Avoiding unscheduled downtime plays a major role in the smooth running of a mine truck fleet. A broken-down truck on a well-used road can cause massive headaches, as operations are forced to a halt. Fortunately, it has been possible to make progress in our ability to keep trucks on the road via the deployment of connected sensors and complementary Big Data analytics.
Engines, transmission, torque converters and differentials are all examples of haul truck components that can be linked to a data logger via a sensor array. It is true that trucks have been running for decades without this kind of technology, without collecting all of these forms of data. However, in neglecting these potentially insightful data points, it is not possible to obtain the clearest picture of what is happening to crucial equipment.
In order to enact change within a maintenance regime it is essential to gather a cache of data which can be projected into the future. A cache of recent data gathered from the quotidian activity of a mine truck can be used to forecast potential points of failure in the near-future. Oil changes, part changes and other maintenance actions can be carried out before a costly breakdown takes place. Broader insights, from the efficiency of specific truck models to how changes in operations effect model performance, are available through deeper analysis of gathered data.
Turning other data into action and ensuring an outcome
Beyond the maintenance of individual units, there is the potential to gain fleet-wide insights related to haul cycles as GPS data is captured. For example, problems with site roads, reported via sensors attached to the haul trucks, can be identified and swiftly dealt with before delays are caused.
Truck operators too can benefit from insights related to the most efficient paths through a site and the correct gear choice in any given location. Readings from these sensors are fed back and interpreted by data scientists who can advise crews on more efficient operational practices.
It really is a case of untapped opportunities at the moment in the mining world, as data is both plentiful and applicable to range of business-critical processes.
The problem that miners often face is that bringing projects from inception to business outcome is a path laden with obstacles. The infrastructure that is needed to process various disparate data flows is rarely present in a conventional mining setting.
Therefore, it is essential to understand what will be required to move each step of the project towards the goal of achieving quantifiable business outcomes. Technology partners who can offer testing and compute services alongside the large-scale deployment of connected technologies greatly multiply the odds of success.