Intelligent mining new standard: 2026 mining excavator five intelligent system selection to avoid pit full strategy

Last month in Shanxi to participate in a smart mine seminar, encountered an interesting thing: two neighbouring coal mines, last year, both purchased “Intelligent Excavator”. A year later, the equipment of mine A has become a “model project”, but the equipment of mine B is basically in the “intelligent dormant” state – in addition to the basic GPS positioning, other intelligent features basically did not Enable.

In-depth understanding found that: A mine set up a five-member technical team before purchasing, and spent four months researching the match between the intelligent system and its own needs; B mine was attracted by the supplier’s “intelligent big screen” demonstration, and made a hasty decision. This comparison reveals the core of intelligent transformation of mining equipment – the right intelligence is more important than advanced intelligence.

I. Intelligent Hydraulic Systems: From “Throttling” to “Predictive” Evolution
Traditional excavator hydraulic system is “passive response”, while intelligent hydraulics is “active adaptation”. There are currently three technology routes on the market:

First generation: load-sensitive systems (universalised)
Adjusting the flow rate according to the joystick signal saves energy 15%-20% than the traditional dosing system. but the disadvantage is that there is a delay in the response and the composite action coordination is general.

Second generation: positive flow control system (mainstream configuration)
The displacement of the pump is proportional to the pilot pressure, and the response speed is increased by 30%. A national brand has added a “learning function” on the basis of this – the system records the habits of different operators and automatically optimises the flow distribution, so that the efficiency of operation for novices is increased by 25%. 25%.

Generation III: Electro-hydraulic Intelligent Synergy System (cutting-edge technology)
This is truly intelligent and the system contains three core modules:

Work condition identification module: identification of excavated material (soft soil, hard rock, ore) by means of pressure sensors

Adaptive control module: automatic adjustment of digging trajectory and force/velocity ratio

Predictive Maintenance Module: Predicts cartridge life based on hydraulic oil contamination trends

The application data of a domestic gold mine shows that the third generation system improves the excavation efficiency by 18% and reduces the fuel consumption by 22%. However, the purchase cost is $350,000 higher than the common system. Their experience is that if the annual utilisation rate of the equipment exceeds 4,000 hours, the payback period is about 1.8 years; below 3,000 hours, the economy is not obvious.

Remote control and autonomous driving: from “gimmick” to “practical” distance
Remote control and autonomous driving are hotspots, but the landing situation is very different. We researched 27 application cases in China and summarised three application tiers:

Tier 1: Remote Monitoring (Mature Applications)
Transmission of equipment data via 5G or private network for fault warning and operational statistics. This is the basic configuration, and the payback period is usually no more than 12 months.

Tier 2: Remote assisted manoeuvring (chosen with caution)
The operator carries out routine operations in the control room and switches to local control when encountering complex conditions. The key success factors are low latency (≤100ms required) and high definition (at least 1080p) of the video system. In one coal mine, network latency of 200ms led to a remote operation crash and the system was subsequently abandoned.

Tier 3: Fully automated driving (specific scenarios)
Currently, only simple scenarios with a fixed “load point – discharge point” route are applicable. Even then, it requires centimetre-level high-precision positioning and 3D modelling support. The application of a domestic open-pit mine shows that under ideal conditions, the efficiency of automatic driving is 15% lower than that of manual operation, but it can be operated continuously for 24 hours, and the comprehensive efficiency still has an advantage.

Suggestion for selection: Start with remote monitoring and consider upgrading after stable operation. Suppliers are required to provide 3 consecutive months of operation data of implemented projects, focusing on system availability (should be ≥99.5%) and false alarm rate (should be ≤1%).

III. Intelligent diagnostic systems: the leap from “informing about failures” to “predicting failures”
The electronic control systems of modern excavators can detect thousands of parameters, but the real intelligence lies in the depth of diagnostics. We compare four levels of diagnostics:

Level 1: Fault code display (basic function)
Fault codes are displayed and manual checking of the manual is required. This is twenty year old technology.

Level 2: Troubleshooting and advice (current standard)
Describe the cause of the fault and repair recommendations in Chinese, e.g. “Engine 3 cylinder injector circuit fault, recommend checking plug X12”.

Level III: Healthiness assessment (advanced systems)
Health scores for key subsystems, such as “hydraulic system health 87%, main pump wear needs attention”. A national brand’s system can predict hydraulic pump failure 200 hours in advance, with an accuracy of 92%.

Level IV: Maintenance programme generation (top technology)
The system not only diagnoses the fault, but also generates a complete repair programme containing a list of parts, repair steps, and estimated man-hours. It can even call on AR technology to display the disassembly sequence on the repairer’s glasses.

Cost-performance analysis: The incremental cost of the Horizontal Three system is about $80,000 to $120,000, but it reduces unscheduled downtime by 30%-40%. For an excavator with an hourly production value of $5,000, avoiding 5 days of unscheduled downtime per year will pay for itself.

IV. Data management and analysis platform: upgrading from “data stacking” to “decision support”
The data generated by the device is only valuable if it is transformed into a basis for decision-making. A good data platform should have three capabilities:

Capability 1: Multi-device collaborative analysis
The management platform of a large mining group can simultaneously analyse the synergistic efficiency of excavators, mining trucks and drilling rigs. They found an interesting phenomenon: when the excavator’s operating efficiency increased by 15%, the waiting time of the mining truck increased, and the overall efficiency decreased by 3%. the platform automatically suggested adjusting the fleet ratio, which ultimately led to the optimisation of the system.

Competency 2: Energy efficiency benchmarking analysis
The platform has built-in industry energy efficiency benchmarking data and displays equipment energy efficiency rankings in real time. After using this feature, a coal mine in Shanxi, through operation training and parameter optimisation, the energy efficiency of all excavators in the mine was improved from the industry’s bottom 30% to the top 20% within six months.

Capability III: Life expectancy prediction and replacement recommendations
Based on the actual working condition data, it predicts the remaining service life of key components and provides early warning three months in advance. After applying this function, an iron ore mine changed its maintenance mode from “fault maintenance” to “predictive maintenance”, reducing maintenance costs by 28%.

Key point for platform selection: require vendors to open up their data interfaces to ensure you can export raw data. Some vendors enclose data in their own cloud platforms, which is a straitjacket on future data analysis capabilities.

V. Human-computer interface: from “complex and difficult to use” to “simple and intelligent” transformation
A more advanced system is a design failure if the operator is unwilling to use it. There are four characteristics of a good HMI:

Feature 1: Contextualised display
The display automatically switches according to the stage of operation: digging depth and slope are displayed when digging, track tension status is displayed when travelling, and maintenance tips are displayed when servicing.

Feature 2: Personalisation
Allows the operator to save three sets of personalised parameters (Novice mode, Standard mode, Efficient mode) and switch between them at the touch of a button.

Feature 3: Voice Interaction
In a noisy environment, voice commands are safer than touch operations. The current level of technology has been able to recognise Mandarin with a local accent, with a recognition rate of ≥95%.

Feature 4: AR-assisted
The AR glasses display animations of parts disassembly and assembly during maintenance, reducing the time for complex repairs by 40%.

A mine did a comparative test: let two operators with the same experience use the traditional interface and intelligent interface respectively, after one month, the operator using the intelligent interface efficiency increased 12%, and said “operation is easier”.

VI. Intelligent Configuration Selection Decision Matrix
In the face of a dizzying array of smart configurations, we suggest the following decision matrix:

Intelligent Systems Incremental Investment Annual Benefits Applicable Conditions Priority
Basic Remote Monitoring $80,000-$150,000 Reduced Downtime 5-8% All Mines Mandatory
Intelligent hydraulic system 25-40 million yuan Energy-saving 15-22% Annual work >3500 hours High
Advanced Diagnostic System $100,000 – $200,000 Reduction in maintenance cost 20-30% Number of equipment >10 Medium
Remote control 500,000-800,000 RMB To solve special working condition operation High altitude, hazardous area Specific
Autonomous driving $1 million or more Continuous operation capability Simple fixed route Pilot
A final word of advice: Intelligence is not an end in itself, but a means to an end. Before selecting a model, be sure to identify the specific problem to be solved: is it to reduce fuel consumption, improve safety, reduce downtime, or optimise management? Choose the configuration with the problem, in order to avoid the waste of “intelligent for the sake of intelligent”. The best intelligent system is often those who “use hard, can not be separated from the system, the effectiveness of the system, rather than the most gorgeous technical parameters of the system.