Mining
Ai-feature
sorting
Ai-feature
sorting
Higher Yield, Lower Cost
Mining operations aim to increase recovery, reduce cost, and maintain consistent product quality under demanding conditions. InSystem mineral sorting solutions improve yield by separating valuable material earlier in the process, reducing energy use and downstream load. With reliable machine performance, your plant can achieve higher throughput and a lower cost per ton.
Applications by material
Base metal ores
Copper, lead, zinc, nickel
Early material separation improves recovery and concentrate quality before milling.
industrial minerals
Limestone, sandstone, graphite
Precise classification ensures consistent purity and stable product specifications.
ferrous metals
Steel, carbon, iron ores
Contaminant removal enhances feed quality and efficiency in downstream processing.
Every stone counts
Efficient mineral sorting systems reduce transportation, energy, and resource use, improving profitability.
Sorting options
for your operation
Setting sorting criteria
Objects are analyzed against defined accept or reject parameters to separate valuable ore from waste and remove impurities or foreign material.
Detecting with precision cameras
High-speed sensors analyze each particle in real time, capturing detailed visual and material data to ensure accurate identification and classification. Optical sorters can recognize characteristics such as:
color
size
shape
strucaral properties
chemical composition
Sorting into 2+ segments
Once identified, each particle is automatically directed into the correct output stream. The process ensures consistent material separation, higher recovery rates, and lower operational costs compared to manual sorting.
MicroSort
SCU: 0802
Loading material to the belt
Feed material arrives at the conveyor after primary crushing, with particles up to 500 mm in size. This consistent feed entry helps protect downstream equipment and supports smooth, controlled processing.
Separation with grids
The feed passes through a series of mesh screens that classify material by size, improving efficiency and protecting downstream equipment. Typical classifications include:
60 mm
xxxx
xxxx
all < 60 mm
40 mm
stones
xxxx
all < 40 mm
20 mm
sand
dust
all < 20 mm
Sorting into 2 or 6 segments
Pre-screened material is separated into up to six output streams according to density, particle motion, and composition. This step removes residual impurities, improves concentrate quality, and maintains consistent feed for downstream processing.
Defining sorting parameters
Operators set product specifications such as acceptable mineral grade, color range, and reflectance threshold. The system uses these values as reference criteria for classification and removal of unwanted material.
Analyzing material with UV cameras
UV-sensitive cameras scan the material to detect differences in reflectivity and fluorescence. These optical signals reveal variations in mineral composition, helping distinguish valuable ore from gangue with high accuracy.
Sorting material into output fractions
Material is separated into two or more output streams based on the detected optical characteristics. This ensures cleaner concentrate, higher recovery rates, and improved feed consistency for downstream processes.
Ai-feature sorting
Rising demand for high-quality minerals such as lithium, copper, and precious metals for use in electronics, batteries, and green technologies (e.g., solar panels) is pushing the development of advanced sorting solutions.
Ai-feature
sorting
Ai-feature
sorting
Ai-feature sorting
Rising demand for high-quality minerals such as lithium, copper, and precious metals for use in electronics, batteries, and green technologies (e.g., solar panels) is pushing the development of advanced sorting solutions.
3 type
uv sorting
3 type
uv sorting
Optical separator
V-light
2 type
ballistic separation
2 type
ballistic separation
Ballistic separation
MicroSort
1 type
optical sorting
Setting category criteria
The sorter compares objects to user-defined accept/reject criteria to identify and remove defective products and foreign material (FM) from the production line, or to separate product of different grades or types of materials.
Recognizing pieces with the camera
Depending on the types of sensors used and the software-driven intelligence of the image processing system, optical sorters can recognize an object's characteristics:
color
size
shape
strucaral properties
chemical composition
Sorting into 2+ segments
Compared to manual sorting, which is subjective and incon-sistent, optical sorting helps improve product quality, maximize throughput and increase yields while reducing labor costs.
Optical separator
v-heavy
V-light
V-light
SCU: 0701
Ballistic separator
MicroSort
2 type
ballistic separation
Ballistic separation
MicroSort
1
Uploading material to tape
Loading material onto the belt. The material requires the simplest preparation - initial crushing, so as not to damage the machine.
2
Separation with grids
Materials are categorized according to their size. The overall flow flies through several stages, each characterized by the size of the hole in the mesh into which the material can fall.
60 mm
xxxx
xxxx
all < 60 mm
40 mm
xxxx
xxxx
all < 40 mm
20 mm
sand
dust
all < 20 mm
3
Sorting into 2 or 6 segments
Compared to manual sorting, which is subjective and inconsistent, optical sorting helps improve product quality, maximize throughput and increase yields while reducing labor costs.
Uploading material to tape
Loading material onto the belt. The material requires the simplest preparation - initial crushing, so as not to damage the machine.
Separation with grids
Materials are categorized accor-ding to their size. The overall flow flies through several stages, each characterized by the size of the hole in the mesh into which the material can fall.
60 mm
xxxx
xxxx
all < 60 mm
40 mm
xxxx
xxxx
all < 40 mm
20 mm
sand
dust
all < 20 mm
Sorting into 2 or 6 segments
Compared to manual sorting, which is subjective and incon-sistent, optical sorting helps improve product quality, maximize throughput and increase yields while reducing labor costs.
microsort
SCU: 0802
3 type
uv sorting
Optical separator
V-light
Setting category criteria
The sorter compares objects to user-defined accept/reject criteria to identify and remove defective products and foreign material (FM) from the production line, or to separate product of different grades or types of materials.
Analyzing objects with the camera
The sorter compares objects to user-defined accept/reject criteria to identify and remove defective products and foreign material (FM) from the production line, or to separate product of different grades or types of materials.
Sorting into 2+ segments
Compared to manual sorting, which is subjective and incon-sistent, optical sorting helps improve product quality, maximize throughput and increase yields while reducing labor costs.