In the metallurgical industry, the accuracy of raw material
proportioning directly determines the stability of metal
composition, energy consumption and product quality.
Traditional manual dosing relies on empirical operation,
and the weighing error often reaches ±3%-5%, leading to
frequent problems such as large fluctuations in furnace
conditions and impurities exceeding the standard. The in-depth
application of intelligent dosage system realizes the dosage
error to be reduced to within ±0.3% through data driving,
which promotes the smelting process to step into the era of
“gram-level precision”.
I. Technology core: Paradigm upgrade from
“experience-driven” to “algorithm optimization
Intelligent Batching System reconstructs the whole process of smelting
raw material management through three core technology modules:
1. Multi-source data fusion sensing
High-precision sensing network: Laser ranging, microwave moisture
detection, X-fluorescence composition analysis and other sensors
are deployed at key nodes such as raw material silos, conveyor belts,
weighing hoppers, and real-time collection of 15 parameters such
as material particle size, humidity, elemental content, and so on;
Dynamic Compensation Algorithm: For the interference factors
such as belt deflection and uneven material flow, Kalman filter
algorithm is utilized to make millisecond corrections to the
instantaneous flow rate to ensure that the weighing error stabilizes
at less than 0.2%;
Digital twin modeling: build a 3D dynamic model of raw material
inventory-conveying-mixing, preview the material flow state under
different proportioning schemes, and avoid the risk of material
blockage and stratification in advance.
2. Intelligent Decision Engine
Formulation Optimization AI: Based on historical production data
and real-time furnace condition feedback, it automatically calculates
the combination of raw materials that meets the target composition
and has the lowest cost, which is 50 times more efficient than manual
calculation;
Self-adaptive learning: through the neural network to continuously
learn the physical properties of raw materials change law, dynamic
adjustment of dosing weight coefficients, so that the system in the
ore grade fluctuations of ± 10% still maintain a stable ratio.
3. Closed-loop control system
Multi-actuator synergy: Integrate the frequency converter feeder,
pneumatic gate, screw conveyor and other equipment to realize
±50g accurate feeding, and improve batch consistency by 90%;
Quality traceability chain: utilizing blockchain technology to record
the proportioning data and process parameters of each batch of
raw materials, supporting the location of problematic links within
15 minutes in case of compositional anomalies.
The measured data of a copper smelting enterprise shows that after
deploying the intelligent dosing system, the standard deviation of
copper content in anode plate is reduced from 0.8% to 0.07%, and
the recovery rate of precious metals is increased by 2.3 percentage points.
Application Value: Cracking the four core
pain points of metallurgical industry
1. Raw material cost optimization
The system can automatically match the optimal mixing ratio
of low-priced ore and high-grade ore, reducing the raw material
cost of crude copper by 80-120 yuan per ton under the premise of
ensuring that the composition is up to standard;
By accurately controlling the additive amount of auxiliary materials
(limestone, coke, etc.), the waste of auxiliary materials in a single
furnace is reduced by 65%, and the annual cost saving is more
than 5 million RMB.
2. Process stability improvement
Real-time monitoring of the moisture content of raw materials
and automatic compensation of heat balance calculations have
narrowed the temperature fluctuation of the smelting furnace
from ±25℃ to ±5℃, and the furnace lining life has been extended by 40%;
In lead and zinc smelting, the error in the proportioning of
arsenic, antimony and other harmful elements was reduced
by 95%, and the cost of anode sludge treatment dropped by 30%.
3. Enhanced environmental compliance
Precise control of the molar ratio of sulfide and oxidizer makes
SO₂ emission concentration stable below 50mg/m³, and the
dosage of desulfurizer saves 22%;
By optimizing the slag phase composition, the generation of
hazardous waste slag is reduced by 18%, and the utilization
rate of resource utilization is increased to 92%.
4. Production flexibility expansion
Supporting one-click switching of formula libraries for more
than 20 metals, such as copper, aluminum, nickel, etc., the
preparation time for transferring production is compressed
from 8 hours to 30 minutes;
For the recycling of scrap and miscellaneous metals, it automatically
identifies the composition of the fragments and generates a
customized proportioning scheme, and the proportion of
scrap blending can be up to 45%.
Scenarios: innovation of the whole chain
from ore powder to alloy
Scenario 1: Ore powder pre-batching
At the front-end of sintering/smelting, the system dynamically adjusts
the ratio of iron ore, solvent and fuel according to the fluctuation
of ore grade, reducing the fluctuation of sintered ore alkalinity
from ±0.15 to ±0.03, and lowering the fuel ratio of blast furnace
by 8kg/t.
Scene 2: Alloying production
In copper alloy manufacturing, ±0.01% level control of trace elements
such as tin, nickel and chromium is realized to meet the stringent
composition requirements of aerospace copper;
In aluminum alloy melting and casting, online detection and real-time
replenishment of nanoscale silicon particles reduce the dispersion of
mechanical properties by 60%.
Scene 3: Scrap regeneration smelting
Automatically identify the plastic and rubber impurity content in waste
copper cables and electronic scrap, accurately calculate the amount
of deoxidizer and slagging agent to be added, and increase the direct
metal recovery rate to 98.5%;
For complex materials such as zinc-containing fumes, the metal
recovery rate and energy consumption are balanced by a
multi-objective optimization algorithm, and the comprehensive cost of
each ton of regenerated zinc is reduced by 400 yuan.
Fourth, industry change: driving green
metallurgy and digital transformation
According to the estimation of international authoritative organizations,
the popularization of intelligent dosage system will reconstruct the
competitiveness pattern of the global metallurgical industry:
Quality leap: make the qualification rate of high-end copper foil,
aviation aluminum and other products break through 99.95%,
and help metallurgical enterprises enter the top supply chain of
Tesla, Boeing and so on;
Cost reduction and efficiency: a copper smelter with an annual
capacity of 500,000 tons can increase its annual profit by 120
million yuan through precise dosing, and shorten the payback
period to 14 months;
Low-carbon transformation: reduce carbon emissions by 8%-12%
per ton of steel smelting, promoting the industry to achieve the
goal of carbon neutrality ahead of schedule;
Mode of innovation: the new mode of “cloud dosing” service, small
and medium-sized smelters can subscribe to the expert-level dosing
program on demand, and the technical barriers in the industry
have been broken.
The practice of a special steel enterprise shows that the intelligent
dosage system reduces the fluctuation range of sulfur and phosphorus
content of its ship plate steel by 80%, successfully passes the
certification of nine classification societies, and raises the product
premium by 15%.
Fifth, the future picture: the industrial
meta-universe of intelligent dosage ecology
With the deep integration of 5G, AI and digital twin technology,
the intelligent batching system is evolving in three major directions:
Territorial synergy: opening up the raw material data chain of
mine-port-factory, realizing second-level recipe linkage between
global procurement and local production;
Autonomous decision-making: introducing reinforcement learning
algorithms, the system can autonomously respond to sudden raw
material supply cut-offs, quality anomalies and other black swan events;
Virtual and real mutual control: simulating the smelting process of
new minerals in the meta-universe space, verifying the feasibility
of the dosing scheme in advance, and reducing the cost of trial
production by 90%.
Industry forecasts show that by 2030 the global metallurgical
intelligent batching market size will exceed $24 billion, becoming
the most explosive growth pole in the Industry 4.0 system.
Conclusion
From “fuzzy experience” to “gram-level precision”, the intelligent
batching system reconstructs the underlying logic of metallurgical
production with data. This technology not only solves the dosing
precision problem that has plagued the industry for a hundred years,
but also opens up a new channel for high-quality and sustainable
development of the metallurgical industry through the digitization
of the whole chain of raw materials, processes and products. Driven
by the “dual-carbon” strategy and intelligent manufacturing,
this precision revolution triggered by algorithms is reshaping
the future map of the global metallurgical industry.