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WWT's Jamie Milne: Connected Fleets and the Smart Mine

In a data rich industry, IoT sensors are the logical next step for mining truck fleet management, says Jamie Milne of World Wide Technology.

Jamie Milne, Big Data Engagement Manager at WWT, authored an article in the August issue of Mining Global magazine focused on how big data is changing mining truck fleet management.

Posted by Mining Globalon August 9, 2017:

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 knowable intelligence, so it is extremely important to know each element, from hardware deployment to data analysis to business outcome, forms part of a larger whole.

Predicting Disaster

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.

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