Tackling hidden downtime in underground mines

Idle time has long been one of the most persistent and underestimated challenges in underground mining.

While often hidden in the margins of shift logs and post-shift reports, it represents a significant drain on productivity - and, by extension, profitability.

Deep underground, a bolter may sit idle as crews wait for the next task or equipment is delayed upstream. Nothing moves for 30 minutes. Multiply that pause across multiple crews, machines and days, and the cumulative impact becomes clear.

If we better understand the scale of this issue, we can better understand how digital technologies are helping mines respond.

Taking the cumulative effects of idle time

A face sitting idle for 30 minutes might seem minor, but across multiple shifts and sites, it becomes a real opportunity cost. Over a quarter or year, you’re talking about thousands of lost production hours and millions of dollars in value.

Historically, idle time was difficult to track in real time. Most mines relied on manual shift reports and handwritten logs, which often missed context or failed to capture smaller but recurring inefficiencies.

With digital systems, idle time is now visible in real time, broken down by crews, machines and tasks. That visibility changes the whole conversation because it turns what was once guesswork into actionable intelligence.

MST’s HELIX Dispatch is one such platform that connects live data from equipment, personnel and IoT devices across the mine, automatically detecting and logging delays as they occur.

Context is important

But visibility is only part of the equation – the real power lies in understanding why the idle time is happening. This involves capturing not just when a delay occurs, but which crew was working, what task was in progress and what events triggered the slowdown.

This level of context is what enables more informed decisions. Supervisors aren’t just looking at data – they’re seeing the full picture of what’s happening in the mine, moment to moment.

With this information, shift planners and supervisors can make dynamic adjustments. If a task is completed early, the next crew can be mobilised immediately. If a loader is delayed, downstream activities can be rescheduled on the fly to minimise the ripple effect.

This kind of real-time coordination reduces the stop-start nature of underground operations and keeps the whole shift running more smoothly. Rather than working off outdated assumptions, crews are always operating with live information that tells them exactly what’s ready and what isn’t.

Flow on benefits of live data tracking

This shift toward real-time responsiveness also impacts culture. For frontline workers, it reduces frustration and uncertainty. Crews gain clarity around scheduling and are less likely to spend time waiting without clear direction.

When crews can trust the information they’re getting, the whole workplace becomes more efficient and less stressful. It improves morale because people know their time isn’t being wasted.

Looking to the future

While the current benefits are clear, the future potential is even more significant. As connected systems become more sophisticated, the next step is predictive operations – using data trends and automation to prevent idle time before it happens.

For example, if a truck is consistently late to a loading point, the system could flag that automatically and adjust schedules in advance. We’re moving toward a world where data doesn't just inform decisions – it drives them.

For an industry that runs on tight margins and high operational costs, even small improvements in efficiency can deliver outsized returns. Tackling idle time is one of the most accessible ways to unlock value from existing assets – no need for new trucks or larger crews.

Idle time may be a hidden cost, but it’s not an unavoidable one. With the right tools, mines can take meaningful steps to reduce downtime and get more out of every shift.

In underground mining, every minute matters, and with growing digital visibility, operators now have a clearer path to making each one count.