The MiniBond test: A robust and cost-effective alternative for ore hardness characterisation and geometallurgical profiling

Efficient ore hardness characterisation is pivotal for effective geometallurgical modelling and mine planning. However, conventional Bond Work Index (BWi) tests, despite their established accuracy, are resource-intensive in terms of cost, time, and sample requirements. This article introduces the MiniBond test, a novel reduced-scale grindability assay designed to provide reliable BWi estimates using significantly lower sample volumes (approximately 600 grams). Extensive calibration across diverse mineralogical domains (over 80 ore samples) validated a high correlation (R 2 = 0 . 98 ) with the traditional Bond test and internal calibration errors consistently below 3%. Double-blind homologation and validation studies conducted collaboratively between Aminpro and Anglo American confirmed the test’s operational reproducibility across laboratories, achieving less than 5% variation. By significantly reducing the cost per test (approximately 80%) and enabling high-throughput testing, the MiniBond test enhances the density of geometallurgical datasets, improving geostatistical interpolation reliability. This paper presents a detailed description of the MiniBond test procedure, the extensive calibration and homologation campaigns, and discusses the practical implications and advantages of implementing this method for large-scale resource evaluation. • The MiniBond test replicates Bond mill grinding conditions using only 600 g of sample. • Calibration models achieve <3% error versus the standard Bond Work Index. • AATS homologation and blind validation confirmed reproducibility across labs. • Bootstrap learning curves establish minimum calibration dataset size for stable predictions.

Authors

Institutions

Publication Details

Journal
Minerals Engineering
Published
2025-08-29
DOI
https://doi.org/10.1016/j.mineng.2025.109740
Primary Topic
Mineral Processing and Grinding
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The MiniBond test: A robust and cost-effective alternative for ore hardness characterisation and geometallurgical profiling

Esteban Ruisanchez Rodriguez, Peter Amelunxen, Roger Amelunxen, Diego Mesa et al.
Minerals Engineering
Mineral Processing and Grinding
article

The MiniBond test: A robust and cost-effective alternative for ore hardness characterisation and geometallurgical profiling

Esteban Ruisanchez Rodriguez, Peter Amelunxen, Roger Amelunxen, Diego Mesa, Patricio Berríos, Caillan Govender, Portia Mudau, Sergio Spichiger
article en

Abstract

Efficient ore hardness characterisation is pivotal for effective geometallurgical modelling and mine planning. However, conventional Bond Work Index (BWi) tests, despite their established accuracy, are resource-intensive in terms of cost, time, and sample requirements. This article introduces the MiniBond test, a novel reduced-scale grindability assay designed to provide reliable BWi estimates using significantly lower sample volumes (approximately 600 grams). Extensive calibration across diverse mineralogical domains (over 80 ore samples) validated a high correlation (R 2 = 0 . 98 ) with the traditional Bond test and internal calibration errors consistently below 3%. Double-blind homologation and validation studies conducted collaboratively between Aminpro and Anglo American confirmed the test’s operational reproducibility across laboratories, achieving less than 5% variation. By significantly reducing the cost per test (approximately 80%) and enabling high-throughput testing, the MiniBond test enhances the density of geometallurgical datasets, improving geostatistical interpolation reliability. This paper presents a detailed description of the MiniBond test procedure, the extensive calibration and homologation campaigns, and discusses the practical implications and advantages of implementing this method for large-scale resource evaluation. • The MiniBond test replicates Bond mill grinding conditions using only 600 g of sample. • Calibration models achieve <3% error versus the standard Bond Work Index. • AATS homologation and blind validation confirmed reproducibility across labs. • Bootstrap learning curves establish minimum calibration dataset size for stable predictions.

Minerals EngineeringVol. 234
Clínica Las Condes (CL), The Medical Oncology Centre of Rosebank (ZA), Hospital Metropolitano (EC), Imperial College London (GB), Anglo American (South Africa) (ZA)
Openalex Percentile: Top 77%
Mineral Processing and Grinding
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.