Simplifying remote monitoring for haul trucks and heavy mining equipment

A haul truck’s health data can reveal early fault signatures for proactive maintenance.

U​​​​​​​nexpected downtime is a frustrating inconvenience, as well as a direct hit to production and profit. Haul trucks, bulldozers, shovels, and other heavy assets operate under extreme loads and harsh conditions, making them vulnerable to costly, sometimes catastrophic, failures. 

Traditionally, mines have relied on scheduled maintenance to prevent breakdowns. But as machines grow more complex and fleets more diverse, traditional approaches struggle to keep pace. This is where remote condition monitoring thrives, combining real-time data acquisition, intelligent analytics, and advanced notifications to transform how maintenance decisions are made. 

Most mining sites operate a mixed fleet of machines sourced from different OEMs — each offering its own proprietary monitoring platform, such as Cat^® MineStar™, Komatsu’s KOMTRAX™, or Hitachi’s Global e-Service. While these systems collect valuable data, they don’t always integrate easily, leading to information silos across a single site. As a result, maintenance teams are often left juggling multiple platforms, with fragmented data that’s hard to consolidate into a single, actionable view.  

Building a successful condition-monitoring system for a mixed fleet demands a way to collect data from different sources, convert protocols, and ensure the results are presented in a consistent, human-readable way. Without this, teams may spend too much time wrestling with data instead of solving problems on the ground.

Modern condition monitoring solutions — whether purchased off-the-shelf or developed in-house — aim to remove these hurdles and focus on three major capabilities: 

• Universal data acquisition: Gathering data reliably from many equipment brands and models. 
• Intelligent analysis: Turning that data into actionable information through algorithms, dashboards, and rules that align with maintenance practices. 
• Actionable notifications: Delivering the right information to maintenance teams early enough to plan a response, rather than react after a breakdown.

A well-designed solution should support standard protocols, be rugged enough for harsh mining environments, and include a secure path for data to flow into visualization platforms or existing maintenance systems.

One trend gaining popularity is preconfigured monitoring systems. Instead of requiring months or years of coding dashboards, writing algorithms, or developing alert systems from scratch, these solutions ship ready to deploy. For example, Monico’s mCore^®SDR data gateway is designed to capture, translate, and transmit data from a wide range of mining assets, while its companion mGuard^® MachineWatch platform uses preloaded algorithms to analyze the data. 

Advanced notifications — through email and a web-based Alerts & Notifications Hub — give technicians and managers actionable insights, including suggested responses, before small issues escalate. Since these systems arrive preconfigured and tested, mines can focus on their maintenance priorities rather than building monitoring tools from scratch.

By combining automated data analysis with advanced notifications, mines can shift confidently toward condition-based maintenance. Instead of reacting to breakdowns, teams can proactively plan repairs, coordinate spare parts, and schedule labor. 

This improves Mean Time Between Outage (MTBO), extends equipment life, and reduces costs tied to emergency repairs or unscheduled shutdowns. Even assets in remote sites benefit from buffered data and secure transmission options, ensuring critical information gets through despite inconsistent networks.

Not every operator will adopt an off-the-shelf solution. Many mining companies are developing their own data visualization tools, analytics, and dashboards tailored to their operations. A flexible, OEM-agnostic data gateway — like mCore^®SDR — can serve as the backbone for these in-house systems. By standardizing data collection across a diverse fleet, mines get a consistent, reliable feed for their custom dashboards, while avoiding the complexity of integrating multiple OEM-specific systems.

As machine complexity and cost pressures grow, the ability to understand, predict, and manage asset health will continue to define successful operators. 

By standardizing data collection, leveraging prebuilt analytics, and providing early actionable insights, modern monitoring platforms can transform how mines manage their most valuable assets — reducing surprises and increasing the confidence to keep material moving, shift after shift.