Integration of Non-ferrous Metals and Automation Technology: A Practical Path to Drive the Efficient Upgrading of Modern Industry

2025-04-02

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Non-ferrous metals, i.e. all metals other than iron, chromium and manganese,

have become core materials in electronic information, new energy and high-end

equipment due to their unique physical and chemical properties. From the

circuit boards of cell phones in daily life to the high-temperature-resistant

parts of spacecraft, from the copper wires of power transmission to the

aluminum battery shells of new energy vehicles, non-ferrous metals are

ubiquitous. This paper will combine specific examples, analysis of the

core value of non-ferrous metals, and in-depth discussion of automation

technology how to empower the non-ferrous industry to achieve

production efficiency and quality leapfrog improvement.

Typical categories of non-ferrous metals and

application scenarios

1. Light metals: aluminum, magnesium, titanium “lightweight revolution”.

Aluminum: density is only 1/3 of steel, but has excellent conductivity and corrosion

resistance. In automation equipment, aluminum robotic arm parts can reduce the

weight of the equipment by 30%, improve the speed of movement and energy

efficiency. For example, an intelligent warehousing system of handling robots using

aluminum alloy frame, single day handling volume increased to 1.5 times the

traditional steel structure.

Magnesium alloy: 33% lighter than aluminum, with outstanding shock-absorbing

performance, it is commonly used in shock-absorbing brackets for precision

instruments. The vibration suppression module of a high-precision CNC machine

tool adopts magnesium alloy base, and the processing error is controlled

within ±2 microns.

Titanium: both high strength and biocompatibility, medical automation

equipment in the joint parts of surgical robots are mostly titanium alloy,

to ensure long-term use without the risk of metal ion precipitation.

2. Heavy metals: copper, zinc, lead “functionalization of the role”

Copper: second only to silver in terms of conductivity, but at a cost of only

1/50th of a percent, copper is widely used in industrial automation scenarios

for key components such as servo motor windings and sensor contacts. 

An automotive welding robot production line consumes over 200 kilograms

of copper wire to ensure the stability of current transmission.

Zinc: The galvanization process gives steel the ability to resist corrosion. 

Automated galvanization production lines precisely control the temperature

of the zinc solution and the dipping time, so that the uniformity of the

coating reaches more than 95%, which extends the life of the shell of the

construction machinery arm to more than 10 years.

Lead: Despite the increase in environmental restrictions, lead-acid batteries

are still used as a backup power source in AGVs (Automated Guided Vehicles),

 and their high energy density supports unmanned handling vehicles to

work continuously for 8 hours.

3. Rare metals: tungsten, rare earths, molybdenum “high-end breakthrough”

Tungsten: with a melting point of 3,422°C, tungsten is used for cutting robotic

tungsten carbide tools. A laser cutting machine tungsten nozzle can work

continuously at a high temperature of 1600 ℃ for 500 hours, the kerf

accuracy of 0.1mm.

Rare earth: neodymium-iron-boron permanent magnet material is the

core component of the servo motor, equipped with rare earth magnets

motor efficiency of 20% higher than traditional products, drive industrial

robot joints to achieve 0.01 ° level positioning accuracy.

Molybdenum: high-temperature characteristics of the semiconductor automation

packaging furnace lining materials, to protect the chip welding process furnace

temperature fluctuations of not more than ± 5 ℃.


Automation technology to reshape the production paradigm of the non-ferrous industry


1. Data-driven intelligent smelting

Traditional non-ferrous metal smelting relies on manual experience to adjust furnace temperature, pressure and other parameters, while the automation system through the deployment of thousands of sensors to achieve real-time collection of data for the entire process. Example:


Intelligent control of copper smelting: In the flash smelting furnace, the infrared thermal camera is linked with the gas composition analyzer to dynamically adjust the oxygen enrichment concentration and material delivery speed, which increases the copper recovery rate from 92% to 96% and reduces energy consumption by 15%.

Aluminum electrolyzer optimization: Based on the current density distribution model, the anode lifting and lowering mechanism is automatically adjusted, the voltage fluctuation range of the electrolyzer is compressed to ±10mV, and the electricity consumption of a single ton of aluminum is reduced by 800 kWh.

2. Machine vision empowers precision processing

Detection of surface defects of copper foil: A copper foil plant introduced AI vision system, which scans the foil surface with 0.1mm resolution and automatically identifies defects such as pinholes and wrinkles, and the inspection speed reaches 60m/min, which improves the efficiency by 20 times compared with the manual sampling inspection.

Titanium pipe weld quality monitoring: Laser vision sensors capture the weld molten pool morphology in real time and predict defects such as porosity and unfused through deep learning algorithms, enabling the titanium alloy pipe qualification rate to jump from 88% to 99.6%.

3. Unmanned logistics and warehousing

Intelligent storage of zinc ingots: AGVs and stacker cranes work together to identify zinc ingot batch information through RFID, realizing automatic storage and retrieval of 500 tons of zinc ingots per day, and shortening the time taken for inventory counting from 8 hours to 15 minutes.

Sorting of rare earth materials: robotic arms equipped with near-infrared spectrometers automatically sort materials according to the characteristic absorption peaks of rare earth oxides, with a purity grading accuracy rate of over 99%, replacing 30 manual sorters.

4. Green production and recycling

Resourceful treatment of aluminum ash: the automated production line extracts metallic aluminum and refractory materials from aluminum ash through magnetic separation, screening and other processes, with a resource recovery rate of 85%, reducing the amount of hazardous waste to landfill by 70%.

Copper slag waste heat power generation: high-temperature copper slag enters into the closed drum, generates steam through the heat exchanger to drive the turbine unit, and the annual power generation of a single production line can be up to 12 million kWh, which meets 20% of the plant's electricity demand.


Future outlook: deep synergy between automation and non-ferrous metals


With the popularity of 5G, digital twins, and autonomous decision-making algorithms, automation in the non-ferrous industry will move to a higher level:


Autonomous optimization of process: smelting equipment is trained with process knowledge graph through historical data to automatically generate the optimal ore distribution scheme and temperature profile. For example, copper smelting furnace can be based on fluctuations in ore grade, real-time adjustment of the proportion of flux added, the impurity removal rate will be stabilized at more than 98%.

Flexible manufacturing upgrade: support for multi-species, small batch production mode, a production line can quickly switch between different products such as aluminum plates and copper tubes. Through modularized design, an extruder completes die replacement within 30 minutes to meet customized order demands.

Industry chain synergistic network: mines, smelters and downstream application side share data through the industrial Internet platform to realize dynamic deployment of production capacity. When the demand for new energy vehicle batteries surges, the system can automatically trigger the lithium electrolyzer to increase production instructions and synchronize the production rhythm of the copper foil mill.


Conclusion



From the mine to the end product, the value chain of non-ferrous metals is being deeply reconstructed by automation technology. Machine vision to replace the human eye to identify defects, algorithmic models to optimize the smelting process inherited for thousands of years, unmanned logistics to break the bottleneck of warehousing efficiency - these changes not only enhance the performance of the material and production efficiency, but also to promote the transformation of the non-ferrous industry to the direction of green, low-carbon, high value-added. In the future, with the continuous penetration of intelligent technology, non-ferrous metal “industrial vitamins” will be deeply integrated with the automation engine, releasing a more powerful kinetic energy of industrial upgrading.