As an important industrial raw material, magnesite is the core resource for the production of fused magnesia. With its high melting point, corrosion resistance, insulation and other characteristics, fused magnesia is widely used in metallurgy, building materials, chemical industry and new energy fields. However, the traditional mineral processing technology has problems such as low efficiency, large waste of resources and unstable product quality, which seriously restricts the improvement of industrial value. In this context, the artificial intelligence sorting machine developed by MINGDER Optoelectronics has achieved accurate sorting of raw ore through technological innovation, promoted the efficient transformation of magnesite resources into the fused magnesium industry chain, and helped enterprises achieve a double breakthrough in economic benefits and sustainable development.

1. Dilemma of traditional mineral processing: waste of resources and loss of value

Traditional magnesite beneficiation relies more on manual sorting or simple physical screening, facing three core problems:

Ore grade fluctuates greatly: Natural magnesite is often accompanied by impurities such as talc and dolomite, and the ore composition is complex. It is difficult to accurately remove low-grade ore by manual sorting.

Low utilization rate of secondary ore: Traditional processes can only separate some high-grade ores, and a large number of medium and low-grade ores are discarded, resulting in waste of resources.

Cost and environmental pressure: Inefficient sorting leads to increased energy consumption for subsequent calcination and rising costs for waste slag treatment, which is not in line with the trend of green production.

These problems directly lead to high production costs of fused magnesia and limited product added value, making it difficult for companies to gain an advantage in market competition.

2. Artificial intelligence sorting technology: solving the dual problems of ore dressing efficiency and accuracy

The AI intelligent sorting machine independently developed by MINGDER Optoelectronics has built a closed-loop sorting system of "human-like eye recognition (machine vision)-AI analysis (big data processing)-pneumatic system execution (spray valve blowing)" by integrating deep learning, hyperspectral imaging and intelligent control technology, realizing full process optimization from raw ore to finished product.

Core technology breakthrough

High-precision ore identification:

Using hyperspectral cameras and high-sensitivity sensors to collect multi-dimensional features of the ore surface in real time, accurately identifying magnesia and associated secondary ores.

The deep learning algorithm can dynamically optimize the sorting model through massive ore sample training to adapt to the ore characteristics of different mining areas.

Intelligent grading decision:

Based on parameters such as ore grade, impurity distribution, and target product demand, the system automatically divides the raw ore into fused magnesium concentrate, secondary ore, and waste to achieve cascade utilization of resources.

Efficient execution system:

Feeding, identification, and sorting work in multiple steps, which can sort 5-150mm particle raw ore, with a sorting output of 10 to 100 tons/hour, and an identification accuracy of more than 98%, far exceeding the efficiency of manual sorting.

Application value:

Improve the utilization rate of raw ore: the output rate of concentrate is increased by 20%-30%, secondary ore can be used as raw material for light-burned magnesium powder, and the waste rate is reduced to less than 5%.

Optimize production costs:

The energy consumption of the calcination link is reduced by 15%, and the quality stability of fused magnesia products is improved, which can greatly increase the proportion of high-end orders.

Green and low-carbon transformation: Reduce tailings accumulation and carbon emissions, in line with environmental protection requirements.

3. Reconstruction of industrial value: from "extensive processing" to "precision manufacturing"

The application of MINGDER Optoelectronics AI sorting machine is reshaping the value distribution logic of the fused magnesium industry chain.

Upstream resource value-added:

Mining companies sell raw ores in grades through sorting technology, and low-grade ores change from "burden" to "profit growth point".

Midstream production efficiency improvement:

Fused magnesia companies use high-purity concentrates as raw materials, reduce the frequency of calcination process adjustments, and increase the capacity of a single furnace by 10%-15%.

Downstream market expansion:

High-purity fused magnesia can meet the needs of high-end fields such as aerospace and new energy vehicle battery insulation materials, and the product premium space has been significantly expanded.

Take a large magnesium mining company as an example. If an AI sorting machine is introduced, the superior grade rate of its fused magnesia can be increased from 78% to 94%, and the inferior ore can be converted into light magnesium carbonate products through deep processing, with an annual additional profit of more than 4 million US dollars.

From mines to terminal products, artificial intelligence sorting technology is injecting new momentum into traditional resource-based industries.MINGDER Optoelectronics uses technological innovation as a fulcrum to maximize the value of mineral resources, which not only creates considerable economic benefits for the company, but also promotes the industry's transformation towards green, high-end and intelligent development, providing vivid practice for the high-quality development of China's manufacturing.