In the wave of digitization in the non-ferrous metal industry, the tin and antimony extraction
process is experiencing unprecedented technological changes. With the deep integration of
intelligent equipment and industrial Internet of Things, the sweaty workers in the traditional
metallurgical workshop are gradually being replaced by precision-controlled robotic arms,
and the empirical parameters in the production control room are being replaced by real-time
algorithmic models. This quiet intelligent revolution is reshaping the production landscape
of the non-ferrous industry.
Intelligent transformation opportunities for traditional
processes
Tin and antimony extraction, as a typical process industry, has long faced pain points such as
complex process parameters, high energy consumption, and large fluctuations in metal recovery
rates. Traditional pyrometallurgical process, the furnace temperature control relies on artificial
experience, raw material composition differences directly affect the metal recovery rate. The lag
in the regulation of acid and alkali concentration in the wet purification process leads to the
consumption of auxiliary materials exceeding the design value by 15%-20%. These technical
bottlenecks in the tightening of environmental standards, energy price fluctuations in the
market environment, forcing enterprises to seek technological breakthroughs.
Intelligent sensing technology breakthroughs provide a new path for process optimization.
Distributed temperature sensor network can capture the heat field distribution in the 2,000℃
high temperature zone in the metallurgical furnace in real time, and the spectrum analyzer can
complete the composition detection of molten metal within 0.5 seconds. After the application
of intelligent control system in a smelter, the direct recovery rate of refined tin has been increased
by 4.2 percentage points, and also the consumption of raw coal has been reduced by 12 tons/day,
and the number of equipment startups and shutdowns has been reduced by 60%.
The intervention of automation equipment is reconstructing the production process. The
unmanned traveling car accurately grab 5-ton material package, positioning error control in
± 3mm; intelligent charging system according to the composition of the ore dynamically adjust
the ratio, the raw material fluctuations on the process to reduce the impact of 70%; mechanical
arm in the hazardous work area to achieve all-weather continuous operation, so that high-risk
jobs to reduce the number of personnel by 80%.
Innovative Application of Intelligent Technology in Tin and
Antimony Smelting
In the field of tin smelting, intelligent transformation focuses on process control optimization. The
slag feature recognition system based on machine vision can warn of abnormal furnace conditions
30 minutes in advance by analyzing the melt surface texture and color changes. After applying digital
twin technology in a project, the refining cycle was shortened by 1.2 hours and the anode sludge
generation was reduced by 18%. The linkage between online X-ray fluorescence analyzer and DCS
system narrows the fluctuation range of crude tin purity from ±0.5% to ±0.15%.
The intelligence of antimony extraction process is reflected in the synergistic control of the whole
process. The intelligent oxygen control system of boiling roaster controls the fluctuation of oxygen
concentration at ±0.3% through fuzzy PID algorithm, and the loss of metal volatilization is reduced
by 25%. Intelligent pH value adjustment device in leaching process dynamically adjusts acid
consumption according to the change of solution potential and reduces the dosage of neutralizer
by 15 tons/month. The intelligent inspection robot in the electrolysis workshop, equipped with
thermal imaging and gas detection modules, realizes early warning of hidden equipment problems.
The digital twin platform is becoming the core carrier of process optimization. The three-dimensional
virtual model constructed by an antimony smelting project compresses the material balance calculation
time from 4 hours to 20 minutes, and shortens the process parameter optimization cycle by 75%.
By simulating 3,000 trials of different raw material ratios, the metal recovery rate increased by 1.8%,
and the equipment failure rate decreased by 40%.
The Future Evolution of Smart Factory
The all-factor connectivity built by Industrial Internet of Things is breaking down information silos.
5G private network realizes millisecond data transmission for 2,000 monitoring points, and edge
computing nodes process 80% of real-time data locally. The intelligent operation and maintenance
platform built by an enterprise integrates 12 types of data, such as equipment vibration, temperature,
energy consumption, etc., to increase the accuracy of fault diagnosis to 92% and the turnover rate
of spare parts inventory by three times.
Intelligent algorithms for process optimization continue to evolve iteratively. The prediction model of
material characteristics based on deep learning has an accuracy rate exceeding 85%; the reinforcement
learning algorithm independently explores a new temperature control curve, which reduces the energy
consumption of tons of products by another 5.8%. The real-time interaction between the digital twin
and the physical system promotes the process parameters to approach the theoretical optimal value
continuously.
The integration of green production and intelligent technology has opened up new paths. The intelligent
exhaust gas treatment system automatically adjusts the operating parameters according to the concentration
of pollutants, stabilizing the desulfurization efficiency at over 99.5%. The intelligent scheduling module of
the waste heat recovery device increases the steam utilization rate to 92%. The AI dosing system for
wastewater treatment reduces the consumption of pharmaceuticals by 18%, and the heavy metal index
of the effluent water is 30% better than the national standard.
Standing on the turning point of industrial change, the intelligent upgrading of non-ferrous enterprises is
no longer a multiple choice question but a must-answer question. When the metallurgical process meets
digital technology, resulting not only in quantitative changes in efficiency, but also qualitative changes in
production methods. Those who take the lead in building up intelligent perception, real-time analysis,
autonomous decision-making capabilities of enterprises, is the digital transformation of the non-ferrous
metals industry to win the first opportunity. This technological revolution started in the production
workshop will eventually reshape the competitive pattern of the entire industry.