インテリジェントマイニング new benchmark: 2026マイニング digging machine 5 インテリジェントシステムの選択は、ピットフル戦策略を避けるために

Last month, whilst attending a smart mining seminar in Shanxi Province, I encountered something rather interesting.“Intelligent Shovel”One year later, the equipment at Mine A became a 'model project', while that at Mine B remained essentially in a state of 'intelligent standby'.

Mine A established a five-member technical team prior to purchase, spending four months researching how intelligent systems could be tailored to their specific requirements. Mine B, however, was swayed by a supplier's demonstration of an 'intelligent big screen' and made a hasty decision. This comparison highlights the core principle of intelligent mining equipment: appropriate intelligence is more crucial than advanced intelligence.

I. Intelligent Hydraulic Systems: From 'Throttle' to 'Predictive' Evolution
The hydraulic systems of conventional hydraulic excavators are “passive reactors”, whereas intelligent hydraulic systems are “active adapters”. Currently, three technological approaches exist in the market:

First Generation: Load-Sensitive System (Universalisation)
Adjusting flow rates according to joystick signals saves energy compared to conventional dosing systems. However, the drawback is that response times are delayed, and compound operation adjustments are commonplace.

Second Generation: Positive Flow Control System (Mainstream Configuration)
The pump displacement is proportional to the pilot pressure, with a 30% improvement in response speed. National brands have built upon this by incorporating a "learning function". The system records the operating habits of various operators and automatically optimises flow distribution, resulting in a 25% improvement in operational efficiency for novice users. 25%.

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

Operational Condition Identification Module: Identification of excavated materials (soft soil, hard rock, ore) via pressure sensors

Adaptive Control Module: Automatic adjustment of excavation trajectory and force/speed ratio

Predictive Maintenance Module: Predicts cartridge lifespan based on hydraulic fluid contamination trends.

According to applicable data from domestic gold mines, the third-generation system has increased excavation efficiency by 18% while reducing fuel consumption by 22%. However, its purchase cost is $350,000 higher than conventional systems. Based on their experience, the payback period is approximately 1.8 years when annual equipment utilisation exceeds 4,000 hours; below 3,000 hours, the economic viability is not evident.

Remote operation and autonomous driving: bridging the gap from novelty to practicality
Remote operation and autonomous driving are hotspots, but their endpoints differ significantly. Having examined 27 application cases in China, we have summarised three application layers:

Tier 1: Remote Monitoring (Mature Applications)
For fault alerts and operational statistics, equipment data is transmitted via 5G or private networks. This constitutes the fundamental configuration, with a typical payback period of less than 12 months.

Tier 2: Remote Assist Manoeuvring (Please select with care)
Operators conduct routine operations from the control room, switching to local control when encountering complex situations. Critical success factors include low latency (requiring under 100 milliseconds) and high-resolution video systems (at least 1080p). At one coal mine, network latency reached 200 milliseconds, leading to remote operation failures, after which the system was abandoned.

Tier 3: Full Autonomous Driving (Specific Scenarios)
At present, only simple scenarios with fixed 'load point-discharge point' routes can be implemented. Even in such cases, centimetre-level high-precision positioning and 3D modelling support are required. When applied to domestic open-pit mines, under ideal conditions, the efficiency of autonomous operation is 15% lower than manual operation. However, it enables 24-hour continuous operation, maintaining an overall efficiency advantage.

Selected proposal: Commence with remote monitoring, with upgrades to be considered once stable operation is achieved. Suppliers must prioritise system availability (99.51% or above) and false alarm rate (11% or below), and are required to submit operational data from three consecutive months of implemented projects.

III. Intelligent Diagnostic System: The Leap from 'Fault Notification' to 'Fault Prediction'
The latest excavator electronic control systems can detect thousands of parameters, yet true intelligence lies in the depth of diagnostics. We are comparing four diagnostic levels:

Level 1: Fault Code Display (Basic Function)
A fault code is displayed, necessitating manual inspection. This is twenty-year-old technology.

Level 2: Troubleshooting and Advice (Current Standard)
For example, "Fault in the three-cylinder engine injector circuit; inspection of spark plug X12 is recommended" describes the cause of the fault and the recommended repair in Chinese.

Level III: Health Assessment (Advanced System)
The integrity scores of key subsystems, such as the hydraulic system integrity (87%) and the need for attention to main pump wear. A certain national brand system can predict hydraulic pump failures 200 hours in advance, with an accuracy of 92%.

Level IV: Maintenance Programme Development (Top-tier Technology)
The system not only diagnoses faults but also generates a complete repair programme, including a parts list, repair procedures, and labour estimates. Utilising augmented reality technology, it can also display disassembly sequences directly onto the technician's glasses.

Cost-performance analysis: The additional cost of the Horizontal Three System is approximately $80,000 to $120,000, but it can reduce unplanned downtime by 301 to 401 TP3T. For a drilling rig with an hourly production value of $5,000, avoiding five days of unplanned downtime per year would recoup the investment.

IV. Data Management and Analysis Platform: Upgrading from 'Data Accumulation' to 'Decision Support'
Data generated by devices only holds value when transformed into the basis for decision-making. An excellent data platform must possess three functions:

Capability 1: Multi-device collaborative analysis
The management platform for large-scale mining groups can simultaneously analyse the synergistic efficiency of excavators, haul trucks, and drilling rigs. An intriguing phenomenon was discovered: when excavator operational efficiency increased by 15%, haul truck idle time rose, causing overall operational efficiency to decrease by 3%. This platform automatically proposed fleet ratio adjustments, ultimately leading to system optimisation.

Capability 2: Energy Efficiency Benchmark Analysis
This platform incorporates industry energy efficiency benchmark data, displaying real-time energy efficiency rankings for equipment. Utilising this functionality, a coal mine in Shanxi Province improved the energy efficiency of all its drilling rigs from the industry's lowest-ranked 30% to the top-ranked 20% within six months through operational training and parameter optimisation.

Capability III: Lifespan Prediction and Replacement Recommendations
Based on actual operational data, the system predicts the remaining service life of key components and issues early warnings three months in advance. At one iron ore mine implementing this capability, the maintenance mode was shifted from reactive maintenance to predictive maintenance, resulting in a reduction of maintenance costs by 281 million yuan.

Key considerations when selecting a platform: Insist that vendors provide open data interfaces to ensure raw data can be reliably exported. Some vendors lock data into their proprietary cloud platforms, which will constrain future data analysis capabilities.

V. Human-Computer Interface: The Transformation from "Complex and Cumbersome" to "Simple and Intelligent"
Even the most sophisticated system is a design failure if operators are unwilling to use it. An excellent HMI possesses four characteristics:

Feature 1: Context-sensitive display
During excavation, the display automatically switches to show excavation depth and inclination; during travel, it shows track tension status; and during maintenance, it displays key maintenance points.

Feature 2: Personalisation
The operator can save three personal parameter sets (Beginner Mode, Standard Mode, Efficiency Mode) and switch between them with a single button press.

Feature 3: Voice Dialogue
In noisy environments, voice commands are safer than touch operations. At the current technological level, recognition rates of 95% or higher can be achieved for standard Mandarin with local accents.

Feature 4: AR Assist
AR glasses display animations of component disassembly and reassembly during maintenance, reducing the time required for complex repairs by 40%.

A comparative test was conducted at a mine. Two operators with identical experience were assigned to use the conventional interface and the intelligent interface respectively. After one month, the operator using the intelligent interface achieved a 121% increase in work efficiency and remarked that "operations had become easier".

VI. Intelligent Configuration Selection Decision Matrix
Faced with rapidly changing smart configurations, we propose the following decision matrix:

Intelligent Systems Additional Investment Annual Profit Applicable Conditions Priority
Basic Remote Monitoring $80,000–$150,000 Downtime Reduction 5–8% Required for all mines
Intelligent Hydraulic System 25-40 million yuan Energy Saving 15-22% Annual Operating Hours >3500 hours High
High-Precision Diagnostic System $100,000 – $200,000 Maintenance Cost Reduction 20-30% Number of Units >10 Medium-Sized
Remote Control 500,000–800,000 RMB Operations to address special working conditions Elevated positions, hazardous zones Specific
Autonomous operation exceeding one million dollars Capable of sustained operation Simple fixed-route pilot
Finally, a 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 reducing fuel consumption, enhancing safety, minimising downtime, or optimising management? Choose a configuration that addresses the problem to avoid the waste of “intelligence for intelligence's sake'. The finest intelligent systems are often inseparable from the hardware they utilise; it is not the system's technical specifications that determine its effectiveness, but rather its most sophisticated technical parameters.