As an important light metal material, magnesium has an irreplaceable role in aerospace, automobile
manufacturing, 3C electronics and other fields. With the acceleration of global industrialization, the
traditional magnesium smelting mode is experiencing profound changes, and the non-ferrous industry
has realized the leapfrog development of the extraction process through intelligent upgrading.
This paper focuses on the application of automation technology in the whole process of magnesium
extraction, analyzing how technological innovation reshapes the industrial pattern.
Automation technology to promote magnesium
extraction process innovation
In the industrialized production of magnesium, electrolysis and thermal reduction method occupies a
dominant position. The traditional production mode relies on manual operation, there are high energy
consumption, quality control difficulties, safety hazards and other pain points. In recent years, automation
technology has realized breakthroughs in three dimensions: intelligent sensor systems monitor reaction
parameters in real time, industrial robots complete high-risk operations, and distributed control systems
(DCS) realize integrated management of the whole process.
In the electrolysis workshop, the application of intelligent sensor network is most representative. By deploying
online monitoring devices for temperature, current density, electrolyte composition, etc., the system can
automatically adjust the electrolyzer voltage and control the fluctuation of electrolyte mole ratio within
±0.02. After the transformation of a large smelter, the current efficiency of a single tank was increased to
92%, and the DC power consumption of tons of magnesium decreased by 600kW-h.
Construction of whole-process intelligent production system
From ore pretreatment to metal refining, automation technology runs through the whole industry chain of
magnesium extraction. The raw material crushing link introduces machine vision sorting system, which
recognizes the ore grade through hyperspectral imaging, and the sorting efficiency is more than 5 times
higher than that of manual. In the reduction furnace control link, the fuzzy PID algorithm dynamically
adjusts the furnace temperature, increasing the stability of magnesium vapor output by 40%.
The automatic slag picking robot equipped in the refining workshop is a typical example of intelligent
upgrading. Equipped with a multi-axis robotic arm and thermal imaging system, the equipment accurately
locates the slag on the melt surface, increasing the operational efficiency by 3 times compared with that
of manual labor, while reducing the metal loss rate from 2.1% to 0.8%. In the ingot casting process, the
automated pouring line stabilizes the ingot yield at over 99.5% through laser positioning and flow
control system.
Digital transformation of quality control system
Intelligent quality control system consists of three parts: online monitoring platform collects 200+ process
parameters in real time, big data analysis engine builds production model, and digital twin system carries
out virtual verification. In the silicon thermal reduction process of the Pijiang method, the system
automatically optimizes the ratio of ferrosilicon by analyzing the temperature field distribution of the
reduction tank, and increases the magnesium crystallization rate of a single tank to 83%.
The automatic X-ray fluorescence spectroscopy (XRF) inspection line deployed by an enterprise can analyze
the composition of magnesium ingots within 30 seconds, with an inspection accuracy of 0.001%. The
quality data is linked with production equipment through the MES system to achieve closed-loop
optimization of process parameters, and the product qualification rate has increased from 94.6% to 98.9%.
Green Manufacturing and Energy Efficiency Optimization Practice
Automation technology brings significant energy saving and emission reduction benefits. The smart grid
system stabilizes the power factor of the electrolysis workshop above 0.93 through load prediction and
dynamic scheduling. The waste heat recovery device is linked with DCS system to increase the utilization
rate of flue gas waste heat of the reduction furnace to 65%, saving 12,000 tons of standard coal annually.
In terms of environmental protection management, the intelligent desulfurization system controls the
concentration of SO₂ in the tail gas below 35mg/m³ through feed-forward-feedback composite control.
The wastewater treatment station applies PLC automatic dosing system, the precision of pharmaceutical
dosing reaches ±1.5%, and the reuse rate of wastewater is increased to 85%.
Outlook of future technology development trend
With the in-depth application of Industry 4.0 technology, magnesium extraction process is developing
in three directions: virtual factory based on digital twin to achieve process simulation optimization, 5G +
edge computing technology to enhance the efficiency of equipment synergy, and AI algorithms play a
central role in process decision-making. A pilot project has successfully shortened the process optimization
cycle from 30 days to 72 hours by establishing a magnesium reduction kinetic model through machine learning.
In the field of equipment operation and maintenance, the predictive maintenance system identifies
equipment anomalies 14 days in advance through vibration analysis, thermal imaging and other technologies,
and the maintenance response speed is increased by 60%. The application of blockchain technology
establishes a product traceability system from the mine to the terminal, meeting the automotive
industry's stringent requirements for material traceability.
Conclusion
The in-depth application of automation technology is reshaping the technological landscape of the magnesium
industry. By building an intelligent production system, the non-ferrous industry has not only achieved efficiency
improvement and cost optimization, but also made breakthroughs in green manufacturing and product quality.
With the continuous empowerment of 5G, artificial intelligence and other new technologies, magnesium
extraction process will accelerate to the direction of high efficiency, cleanliness and intelligence, providing
solid support for the development of new materials industry.