CUSTOMER CASE STUDY

Digital twins in mining operations and maintenance.

How a global mining and resources customer cut underground conveyor downtime by over 80% in a 120-day pilot — and scaled XMPro digital twins across 32 use cases and 42 million daily messages.

>80%

Conveyor downtime reduction (pilot)

10×

Return on investment

Production use cases live

42M

Messages processed per day

THE CUSTOMER

A global mining and resources customer.

A multi-national customer that leads the world in producing critical natural resources. They use the best technologies, responsible mining methods and an experienced team to stay on top.

The business has many high-quality reserves, has expanded over multiple years and runs a fleet of low-cost mines and processing plants. A vast, reliable distribution network — marine terminals, numerous distribution points and a large pool of owned or leased railcars — supplies their products to about 40 countries.

Their operations are backed by a digital transformation programme to increase production and cut costs through automated mining and digital technologies, prioritising safety, efficiency, cost-effectiveness, flexibility and environmental and social responsibility.

In 2022, they made more use of automated mining, boosting production by about 50% year on year. They also grew their predictive maintenance platform, using XMPro to foresee and prevent asset failures, with mobile sensors improving their monitoring abilities.

THE CHALLENGE

Cut underground long-conveyor downtime by 30% in 120 days.

In 2019, the customer launched an initiative focused on predictive maintenance and operations. The goal was to enhance production and run at optimal capacity across their mining ventures.

Multiple digital twin scenarios were considered. Reduction of underground long-conveyor downtime was chosen as the pilot project for XMPro iDTS, guided by XMPro’s Use Case Prioritisation Matrix framework.

The objective was a 30% downtime reduction for a specific failure mode over a 120-day trial.

THE APPROACH

Real-time data + 40 years of operator expertise, evaluated every two seconds.

XMPro iDTS amalgamated real-time data from sensors, historians and maintenance management systems. Expert guidelines from seasoned maintenance teams — some with over 40 years of experience in soft rock mining — were used as the benchmark for recommendations, with the real-time data evaluated every two seconds.

The pilot ran at a featured mine where the system oversaw more than 50 conveyor belts spanning over 80 km of underground network. The initial version was up and running and starting to deliver value within 30 days.

VISUALISATION

“Tube map” view of underground conveyors with predictive alert markers.

Underground conveyor tube map at the start of the pilot — At the start of the pilot

Underground conveyor tube map 120 days later — 120 days later

THE RESULTS

The pilot beat the target. The platform scaled.

The initial pilot was very successful, reducing downtime by over 80%. In the four-month proof of concept, the customer prevented 60 hours of borer downtime as a result of conveyor stoppage — equivalent to approximately 14,000 tons of product. The team identified a further 124 hours of preventable downtime, amounting to roughly 30,000 tons of additional product.

XMPro Recommendations effectively captured expert knowledge on maintenance best practices, transitioning the team from ad-hoc business-intelligence-style spreadsheet analysis to continuous scrutiny and alerts. Reliability engineers now had constant insights to prescribe the necessary actions, and recommended actions were incorporated into the customer’s predictive and prescriptive maintenance procedures.

Following the success of the pilot, XMPro was implemented across the other mining sites to tackle a variety of operational issues across eight asset classes. With 32 use cases live and the platform sending 42 million messages per day, the business reaped over a 10× return on investment on the project.

XMPro recommendations capturing expert maintenance knowledge

Have a similar problem on your plant floor?

We’ll walk you through how the digital twin pattern maps to your environment — conveyor reliability, asset performance, or another high-value failure mode you’re trying to get ahead of.

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