1. Material Specifications

  • Primary Material: Limestone.
  • Material Characteristics:
    • Medium Hardness: Mohs hardness of 3–4, easy to crush.
    • Low Abrasiveness: Effectively reduces wear on impact crusher (sand-making machine) components.
  • Feed & Output Specifications:
    • Feed Size: Blasted raw ore with a maximum size of ≤650 mm.
    • Final Products: High-quality multi-specification outputs:
      • Premium Aggregates (Stone): 5–10 mm, 10–20 mm, 16–31.5 mm, etc.
      • Premium Machine-Made Sand: 0–5 mm, rounded particle shape with reasonable gradation.

2. Core Equipment & Process Design

The success of this project largely stems from meticulously selected equipment and innovative layout design.

  • Terrain Utilization for Energy Savings: Leveraging the natural elevation difference on-site, the jaw crusher discharges material directly into two parallel impact crushers below via gravity. This eliminates the need for intermediate conveying equipment, reducing both investment and operational costs while optimizing space utilization

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  • Flexible “Pre-Screening Before Crushing” Process: A screening stage after the impact crusher separates out particles that already meet product specifications, preventing re-crushing. This minimizes equipment wear and over-crushing, significantly improving overall efficiency

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3. Key Advantages of the Equipment Plan

  • Terrain-Driven Efficiency: The gravity-fed design between crushers cuts energy consumption and simplifies maintenance. The compact layout maximizes output within limited space, allowing room for future expansion or upgrades. Additionally, the configuration reduces noise and dust emissions, aligning with green production standards
  • Superior Product Quality: The impact crusher ensures cubical particle shapes for aggregates, with low flakiness content.

4. Client Feedback

  • Stable Operation & Rapid ROI: Clients report that the line’s high efficiency and stability enabled cost recovery in approximately one year, outperforming the initial two-year projection