Case Study | Blast Optimisation

Blasting Optimisation

Bhadokara Stone Mines, Nawada District, Bihar
M/s Eklavya Stone & Mines Pvt Ltd Nawada, Bihar, India Fragmentation · Cost · Productivity FY 2022–23

AMW Mining & Allied Services was engaged by M/s Eklavya Stone & Mines Pvt Ltd to optimise the blasting operation at the Bhadokara Stone Mines in Nawada District, Bihar. Using Kuz-Ram fragmentation modelling, pattern re-engineering, explosive selection and timing optimization, AMW delivered a measurable step-change in fragmentation quality and unit cost — without any increase in explosive consumption per tonne of stone produced.

The Challenge

Inconsistent fragmentation was driving up cost at every downstream stage

The Challenge

  • Inconsistent fragmentation with oversize boulders exceeding 25% of blasted muck
  • Frequent secondary blasting and breaker deployment slowing the loading cycle
  • High powder factor with energy wasted in over-crushing and fines generation
  • No scientific basis for pattern geometry — burden, spacing and stemming set by habit
  • Rising cost per tonne and crusher downtime from irregular feed size

The Approach

  • Blast audit and rock mass assessment of the granite gneiss benches
  • Kuz-Ram fragmentation modelling to predict and control mean fragment size
  • Pattern redesign: burden, spacing, subdrill and stemming from first principles
  • Explosive selection matched to hole conditions (ANFO / emulsion)
  • Initiation timing optimization with image-analysis fragmentation feedback

Methodology

A closed-loop fragmentation engineering workflow

1

Blast Audit & Rock Mass Assessment

Every blast was audited over a full production cycle — hole geometry, charging, stemming, initiation and muckpile outcome. Rock mass assessment of the granite gneiss benches established UCS 100–160 MPa (ISRM "strong to very strong"), RQD 65–80 ("good"), in-situ density 2.60–2.75 t/m³, and a Kuz-Ram rock factor A ≈ 12. Joint orientation analysis identified strike-parallel open joints that were venting explosive energy and causing backbreak.

2

Kuz-Ram Fragmentation Modelling

The Kuz-Ram model was used to predict mean fragment size (X₅₀) and the Rosin-Rammler distribution for candidate patterns before any hole was drilled. The model was calibrated against measured muckpile fragmentation, giving a reliable design tool for burden, spacing and charge per hole.

X₅₀ = A · K⁻⁰·⁸ · Q^(1/6) · (RWS/115)^(19/20)
3

Pattern Re-Engineering

For 100 mm diameter holes on 9 m benches, the pattern was redesigned to burden B = 2.9 m (≈29 × d), spacing S = 3.2 m (S/B ≈ 1.10), subdrill 0.9 m (≈0.3 B) and stemming 2.6 m (≈26 × d) with drill cuttings. Staggered geometry and a stiffness ratio H/B ≈ 3.1 delivered uniform energy distribution across the bench.

B ≈ 25–40 d · S = 1.0–1.4 B · Subdrill ≈ 0.3 B · Stemming ≈ 20–30 d
4

Explosive Selection & Charging

ANFO (RWS 100) was retained for dry holes with site-mixed emulsion (RWS 110–120) specified for wet or water-bearing holes. Charge per hole was optimized against the Kuz-Ram prediction, and stemming quality was upgraded to eliminate fines-only stemming that was causing cratering and energy loss.

5

Timing Optimization & Feedback Loop

NONEL dual-delay initiation (25 ms inter-hole / 42 ms inter-row) was tuned iteratively. Muckpile fragmentation was measured after every blast using image-analysis techniques, feeding a closed-loop that refined the pattern until the target fragment size distribution was consistently achieved.

Results

Measured outcomes after pattern stabilization

−32%Powder factor (0.38 → 0.26 kg/m³)
400 → 250 mmMean fragment size X₅₀
25% → 6%Oversize boulders
−15%Cost per tonne blasted

Secondary blasting dropped by 80% and breaker deployment was largely eliminated. Loading productivity improved by 20% with a consistent, crusher-friendly feed, and the mine achieved the same production with significantly lower explosive and drilling cost per tonne. Ground vibration at the nearest structures remained within DGMS Circular 7 of 1997 limits throughout.

Statutory Compliance

Standards and regulations applied

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