The “efficiency dilemma” caused by a scraper
In 2019, a copper mine invested a large amount of money to introduce two 4m³ bucket capacity diesel scrapers. It was originally expected to solve the ore bottleneck at once, but it was unexpected that the problem was discovered after the equipment went down the mine: the turning radius of the tunnel was insufficient, and the scrapers were in a dilemma; the stope width was only 3.5m, and the large-volume equipment could not even complete the steering; after the transportation distance exceeded 200m, the efficiency of the diesel scrapers dropped off a cliff, and the ore output in a single shift was not even as good as the original 2m³ old equipment.
This kind of situation is not an isolated case. In the field of metal mining, it is common for “good equipment to fail to meet the expected production capacity” scenarios: the efficiency of rock drilling rigs is less than half of the nameplate parameters, the scraper cannot pass in narrow tunnels, and the ore production capacity is much higher than the rock drilling capacity, resulting in equipment being idle for a long time.
The core of the problem is not in the equipment itself, but in the selection and matching link.
Equipment selection is not about “just buying the most expensive one”, nor is supporting optimization “just putting together the equipment and running”. It is a systematic project that is “adapted to the conditions of the mine”: the conditions of the ore body determine the direction of selection, the equipment parameters match the needs of the scene, and the entire process capacity can be adapted to each other to maximize benefits.
1. The underlying logic of selection: ore body conditions → equipment parameters → production capacity
When many companies choose equipment, they first look at the parameter table and then compare prices before making a final decision. This is actually putting the cart before the horse.
The correct selection logic chain should be: Ore body conditions (thickness, inclination, surrounding rock stability) → Determine stope structural parameters (section, transportation distance, mining height) → Determine equipment type and specifications → Check whether production capacity meets mining needs.
For example, for a steeply inclined thin vein with a thickness of 2m and an inclination angle of 65°, the stope width is only about 2m. It is impossible to enter the stope with a 3m³ scraper. In this case, a small remote-controlled scraper with a bucket capacity of 0.9m³ and a body width of 1.4m is the best choice.
According to relevant industry statistics, Zijin Mining has invested a total of more than 24 million yuan since 2022 to develop 6 types of small and lightweight equipment suitable for four typical scenarios of rock drilling, transportation, support, and disaster relief. A total of 92 sets have been promoted and applied. Among them, a small remote-controlled scraper has a shoveling capacity of up to 80 tons in a single shift of 6 hours under the condition of 50m transportation distance, and the mining efficiency is three times that of an electric rake winch of the same power.
The first principle of model selection: the equipment must be able to “go in, work, and come out.”
2. Scraper selection: the “golden partner” of bucket capacity and transport distance
The scraper is the core equipment for ore extraction in underground mines. The core selection refers to three dimensions: Bucket capacity, transport distance, and ore body thickness.
2.1 Calculation of hourly production capacity of scraper
The hourly production capacity of the scraper directly determines the upper limit of the production capacity of the mining system. The calculation formula is: Q = 3600×q×k₁×ρ/
(k₂×T), where Q is the scraper hourly production capacity (t/h); k₁ is the bucket filling coefficient, generally 0.8; T is the single cycle time (s), including loading, unloading, U-turn time and round-trip travel time; q is the scraper bucket capacity (m³); ρ is the ore density (t/m³); k₂ is the loose coefficient.
Take a 3m³ scraper in a copper mine as an example: the ore density is 2.88t/m³, the looseness coefficient is 1.6, the transportation distance is 80m, the running speed is 8km/h, the loading and unloading U-turn time is 2min, and the filling coefficient is 0.8.
The calculated hourly production capacity is 126t/h; if the transport distance is increased to 200m, the hourly production capacity directly drops to 81t/h. When the transport distance increases from 80m to 200m, the efficiency directly drops by 36%. This is also the core reason why large-capacity diesel scrapers are not suitable for long transport distance scenarios, and electric cable-powered scrapers are more economical in long transport distance scenarios.
2.2 Practical rules for selecting fighting capacity
| Ore body thickness/stope width | Recommended bucket capacity | Typical hauling distance |
|---|---|---|
| <2.5m | 0.6~1.0m³ | <80m |
| 2.5~5m | 1.5~3m³ | 80~200m |
| 5~8m | 3~5m³ | 100~300m |
| >8m | 5~8m³ | 150~500m |
According to industry public information, the country’s first 8m³ underground scraper adopts a reversing six-link mechanism. The overall height of the machine is 3% lower than that of similar products, and the shoveling force is increased by 5%. It has been promoted and applied in large-scale mines in Russia. It can be seen that large-capacity equipment is not the same as “silly and thick”, and structural innovation can further expand equipment adaptation scenarios.
3. Rock drilling equipment selection: Perforation efficiency determines the mining rhythm
Rock drilling is the front-end link of mining. If the perforation efficiency is not up to standard, all subsequent links will fall into the dilemma of “waiting for rice to be ready.”
The formula for calculating the shift production capacity of rock drilling rigs is: V = v×h×k×n, where V is the shift production capacity (m/shift); v is the pure drilling speed of the rock drill (m/h); h is the number of working hours in a shift; k is the working hour utilization coefficient, generally 0.4~0.6; n is the number of rock drills mounted on the rig.
Taking a double-arm rock drilling rig in a mine as an example, the pure drilling speed in hard rock is 0.8m/h, a single shift works for 8 hours, and the working hour utilization coefficient is 0.5. The calculated shift production capacity is 6.4m/shift.
If a small intelligent excavation trolley is used instead, the rock drilling advancement speed under hard rock conditions can be increased from 0.4m/min to 1m/min, the drilling operation time of the same cross-section tunnel is reduced from 8 hours to less than 4 hours, the rock drilling advancement speed is doubled, and the comprehensive drilling capacity is increased by more than 1 times.
4. Optimization of supporting facilities: cracking the “barrel effect” of the whole process
Equipment selection is a single-point optimization, and supporting optimization is a full-system upgrade.
The complete mining and transportation production line includes rock drilling → blasting → mining → transportation and other links. If any link becomes a shortcoming, the overall efficiency will be reduced.
The core of supporting optimization is that the production capacity of each link matches each other, and the overall capacity adapts to the mine’s design capacity.
4.1 Typical supporting pitfalls and solutions
| Trap Types | Performance | Hazards | Solutions |
|---|---|---|---|
| Large horse-drawn trolley | Large-capacity scraper equipped with small-section tunnel | The equipment is impassable and extremely inefficient | Select according to the size of the stope |
| Bottleneck link | The rock drilling capacity is far lower than the ore production capacity | The mines and equipment such as scrapers are idle | Rock drilling first, capacity matching |
| Transportation stuck | Electric locomotive transportation cannot keep up with the pace of mining | The slide shaft is full and the mining is interrupted | Improve the capacity of the transportation system |
5. Economic analysis: Calculate cost per ton of ore
The final criterion for equipment selection is economic benefit. As long as the cost per ton of ore can be reduced, a large investment is worthwhile.
The calculation formula for the cost of equipment per ton of mineral resources is: C = (P
Take a mine’s 3m³ scraper as an example: the equipment investment is 2.8 million yuan, the annual interest rate is 5%, the service life is 8 years, the annual maintenance cost is 350,000 yuan, and the annual production capacity is 180,000 tons. It is estimated that the cost per ton of mining equipment is about 4.2 yuan/t, and the investment payback period is less than 4 months.
However, if improper selection results in half the efficiency, the annual production capacity drops to 90,000 tons, the cost of mining equipment per ton will rise to 9.64 yuan/t, and the investment recovery period will be extended to more than 7 months. The gap in selection will be directly reflected in economic benefits.
6. Practical case reference
Case 1: Guangxi Panlong Lead-Zinc Mine: The mine had generally narrow tunnels and could only use a 1m³ scraper, severely limiting its production capacity.
When promoting the 6000t/d production expansion project, the company adjusted the tunnel parameters in a targeted manner and introduced a 3m³ scraper through decomposition transportation and underground assembly. It only took 4 days to complete the assembly and put into production, which greatly improved the modern production level of the mine.
Case 2: Hunan Shizhuyuan Non-ferrous Metal Mine: The company adopts a step-by-step upgrade strategy to promote equipment updates in the entire underground production process: replacing handheld drill rigs with intelligent rock drilling rigs, increasing rock drilling efficiency by three times; using 5m³ large scrapers to eliminate 4m³ or more
By removing old equipment, the per capita mining efficiency increased by 20%; it is equipped with 5G+ driverless scrapers to realize remote mining. In the first half of 2024 alone, it recovered 48,000 tons of stope ore through remote control shoveling technology, creating an economic value of 32 million yuan, and was successfully selected as a provincial “5G+ Industrial Internet” demonstration factory.
To sum up, the essence of mining equipment selection and supporting optimization is the “art of matching”: only by matching the ore body and equipment, matching links and links, and matching inputs and outputs can maximum benefits be achieved.
The core principles can be summarized in three sentences: The ore body conditions determine the direction, the calculation formula is verified, and the matching optimization produces benefits.
