Thiess mines operational data with cloud dashboard
- 21 October, 2013 13:00
Workers at Thiess Australia are using a cloud-based dashboard to make sense of large mines of data critical to maintaining the company’s machines.
Thiess has 3000 employees and a $2 billion plant and equipment fleet, making it one of the world’s largest open-cut contract mining companies. It produces more than 100 million tons of coal, copper, gold and iron ore each year.
Each truck used by Thiess has more than 300 sensors that are used to measure the amount of diesel fuel in the trucks, the volume of coal and minerals extracted and more. The sensors are critical to maintaining the health and mechanical efficiency of the machines, according to Ben Willey, manager of mining technology and innovation at Thiess.
"We collect information on every person, machine, activity, location, delay, and consumable in the business,” he said.
“The data derived is used to assess operational performance, capture business process data at source and to supplement other data captured manually by other means.”
While Thiess already had an extensive database reporting toolset, Willey said the company wanted a method to provide a simplified and more graphical view. The company also wanted to be able to view the data on mobile devices, he said.
“Previously, analysis of reporting required all of the information to be assessed,” he said. “The adaptive tool provides a graphical representation of performance and highlights exceptions. This focuses decision makers on the issues quickly.”
Willey summed up the goal as “scalable, standardised dashboarding supporting operational decisions.”
A business partner recommended Adaptive Discovery, and Adaptive Planning was able to quickly demonstrate a transferable service, he said. Willey said the company was also intrigued by the promise of a cloud-based service.
“The cloud-based system provides key benefits in scalability, support effort and the enabling of an efficient mobility solution,” he said. “It will allow us to develop our application further including an external facing view.”
Implementing the Adaptive service took about half a year.
“We undertook a development project over a 6-month timeframe to build the data structures to accommodate our operating model and provide flexibility to scale the solution over time,” Willey said.
“As a contracting organisation we needed this and were prepared to take the time to get it right. Once we had the models completed the actual implementation of the Adaptive solution was simplified and adoption across the organisation was rapid.”
As hoped, the dashboard quickly crunches data into usable information, Willey said.
The service’s "capacity to conduct millions of calculations, obtain trends and then display the information as key performance indicators that are contextual and timely is a powerful advantage,” he said. “We have the latest data available just after each shift has closed."
The new dashboard showed its usefulness in the first week, identifying a mechanical problem that could have significantly slowed production.
"The Adaptive Discovery implementation essentially paid for itself by immediately notifying us of a problem where in the past the root cause analysis would have taken more time to identify,” Willey said.
Additionally, the mobile dashboard provided through an Apple iPhone app has been even more useful than expected, he said. The app is provided to all personnel who use the dashboards, which are mainly line and senior management who were already using company-provided iPhones, he said.
“We developed the requirements for the mobile application to provide a cut down view of the overall reporting platform,” he said.
“However, the solution ended up being quite comprehensive and provides a surprising level of detail without losing the efficiency expected from a mobile app.”
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