MachineMax: Drilling into data tracked from mining and construction equipment with Google Cloud and Google Maps
About MachineMax
A subsidiary of Royal Dutch Shell, MachineMax produces equipment management platforms that maximize profitability and cut the carbon output of off-road fleets used in mining and construction operations worldwide.
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About Localyse
Google Cloud Premier Partner, Localyse, helps businesses to optimize their operations using Google Cloud and Google Maps.
MachineMax’s equipment management platform tracks and monitors off-road equipment, often operating in remote parts of the world, to boost efficiency, profitability, and sustainability.
Google Cloud results
- Cuts downtime and aids scheduled maintenance by tracking utilization
- Boosts asset efficiency and productivity
- Reduces idling and fuel consumption, making customers’ operations more sustainable
- Integrates data collected from any source across all sites on a single platform
- Enhances health and safety
Locating and tracking off-road equipment for optimal use
The metals, mining, and construction industries rely on heavy off-road equipment for drilling, digging, and transporting goods and people in often remote and difficult to access parts of the world. If this equipment is poorly maintained, is used inefficiently, or even not used at all, it is not being used cost-effectively, which negatively impacts productivity. It could also result in the burning of excess fuel and unnecessary carbon emissions, plus it could lead to expensive repairs that could have been less severe if they were picked up earlier.
A subsidiary of Dutch energy company Royal Dutch Shell, MachineMax, produces equipment management platforms that connect to sensors positioned on various parts of off-road equipment to monitor its location, usage, and condition. “We connect all the heavy equipment assets that tend to be used in mining and construction to build complete remote visibility of what's happening on-site through a single user interface,” explains Jennifer Thomson, Chief Growth Officer at MachineMax. “Operators can plug into the real-time data that we collect and use it in a smart way to understand what’s happening on-site and then take steps to improve the performance of their equipment and drive sustainability, efficiency, and profitability.”
“We chose Google Cloud and Google Maps Platform because they can scale with us and cover the globe, and also because we knew what we wanted to build and the tools that we needed to do it and Google had them all, so we could use them from the start.”
—Lina Alagrami, Lead Engineer, MachineMaxSeeking out technology that could grow with MachineMax
MachineMax launched in 2018 with global ambitions. Aware that its target clients were based in some of the most remote locations on Earth, it needed to partner with a technology company that could reach these isolated regions and had the capacity to scale with the business. Google Cloud demonstrated that its serverless solutions could meet these requirements and that it had the products that MachineMax needed to deliver its offering.
“We chose Google Cloud and Google Maps Platform because they can scale with us and cover the globe, and also because we knew what we wanted to build and the tools that we needed to do it and Google had them all, so we could use them from the start,” says Lina Alagrami, Lead Engineer at MachineMax.
Building an infrastructure on Google Cloud
MachineMax was born on Google Cloud. Dataflow was integrated on day one and handles all of the company’s data processing. Cloud Bigtable powers its entire system and stores the bulk of the company’s raw data. Cloud SQL is the main domain database that powers the MachineMax web app and is used to store the aggregates and calculations, while IoT Core securely manages all of MachineMax’s device management configuration.
“In Cloud IoT, we have registries for each of our sensor types, we add our sensors to the relevant registry’s device manager, which includes third-party devices, and if we receive data from a device that is not on that list, Cloud IoT Core will not authenticate it or accept that data. If we want to tell a sensor to turn off, we do it with Cloud IoT Core too, it shows us which devices are out there and allows us to pull data from them,” explains Alagrami.
The development team uses Google Kubernetes Engine (GKE) and Cloud Run to schedule frequent requests, writing the code, building a Docker image, and deploying on Cloud Run within minutes. If this is done from a command line it takes about one minute, says Alagrami, adding: “It’s also super easy to scale Cloud Run up and down as we need it, and because we only pay for what we use, it helps us manage costs.”
“We chose Google Maps Platform because it made sense to work with another Google product, its functionality seemed to outperform its competitors, and from a usability perspective, people are familiar with its tooling, but most importantly it integrates with a large number of APIs for geometry, drawing, places, and visualization.”
—Riccardo Rizzo, Lead React and iOS Engineer, MachineMaxMapping out an integrated future
As geopositioning is such an integral part of MachineMax’s offering, it also needed to launch with a suite of tracking tools that would integrate with Google Cloud, and Google Maps Platform was the obvious choice.
“We chose Google Maps Platform because it made sense to work with another Google product, its functionality seemed to outperform its competitors, and from a usability perspective, people are familiar with its tooling, but most importantly it integrates with a large number of APIs for geometry, drawing, places, and visualization,” explains Riccardo Rizzo, Lead React and iOS Engineer at MachineMax.
To provide a true representation of what is going on in a specific location, MachineMax uses a variety of APIs to show its customers the coordinates of where their off-road equipment is located, its condition, where it is in relation to other equipment in the field using geofences and to provide a visual picture with satellite imagery.
“With tools such as Heatmap Layer we can show, for example, excessive idling. This is where a vehicle or multiple vehicles are sitting with their engines on, burning fuel, emitting CO2, and being unproductive. And, we might even be able to show that this is happening because a load of dump trucks is backed up waiting to be loaded,” says Kate Stephen, Head of Product and Design at MachineMax.
Getting data from remote areas
Although MachineMax implemented its Google Cloud and Google Maps solutions in-house, it wanted to further improve the accuracy of its GPS. Google suggested it call on the support of Google Cloud Premier Partner, Localyse to help it with this specific issue.
“We needed to try and increase the accuracy of our GPS, and there are several factors that can influence this, but the biggest factor is the number of satellites in view,” says Rizzo. “Localyse helped us to filter out all the GPS points that use a low number of satellites and also to use machine learning to reproduce a point from a previous point to help create a more accurate picture.”
“We know that with the support of Google Cloud and Google Maps, we can drill even deeper into the parameters of the data that we collect to help our customers become more profitable, more efficient, and more sustainable.”
—Jennifer Thomson, Chief Growth Officer, MachineMaxMining data to optimize operations in the field
MachineMax now hopes to use its picture of what’s happening in the field to inform its machine learning models, so that it can continually optimize its customers’ operations. “We are now looking at how we can enhance the way that people use our data,” reveals Kate Stephen, Head of Product and Design at MachineMax. “Take shifts, for example, if you have complex work shift structures, you can start viewing your productivity data by shift rather than just by day, to see if a particular shift leads to more fuel consumption, loading, or idling.”
Thomson concludes: “We know that with the support of Google Cloud and Google Maps, we can drill even deeper into the parameters of the data that we collect to help our customers become more profitable, more efficient, and more sustainable.”
Tell us your challenge. We're here to help.
Contact us
About MachineMax
A subsidiary of Royal Dutch Shell, MachineMax produces equipment management platforms that maximize profitability and cut the carbon output of off-road fleets used in mining and construction operations worldwide.
About Localyse
Google Cloud Premier Partner, Localyse, helps businesses to optimize their operations using Google Cloud and Google Maps.