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Sampling Columns

11 Oct 2021

Stéphane Brochot

CASPEO, Orléans, France. www.caspeo.net

Editor’s summary

11 Oct 2021

Quentin Dehaine

Senior Researcher at the Geological Survey of Finland (GTK), Circular Raw Material Hub (Vuorimiehentie 2) 02151, Espoo, Finland

11 Oct 2021

Li Huachang and Zhu Mingwei

BGRIMM MTC Technology Co. Ltd, China

11 Oct 2021

Martin Lischka

HERZOG Maschinenfabrik GmbH & Co. KG, Germany

11 Oct 2021

Ralph Holmes

Honorary Fellow, CSIRO Mineral Resources, Australia

Case 1. Even a small sampling bias can have a BIG negative economic consequence

Poor sampling procedures for iron ore can lead to preferential exclusion of coarser high grade particles from shipment samples for analysis due to cutter apertures that are too small or cutter speeds that are too high. This leads to a negative bias on Fe content—the result is that shipments are also carrying away substantial lost revenues!

11 Oct 2021

Pedro Carrasco, Pablo Carrasco and Eduardo Jara

Incorrect sampling operations cause huge economic losses to the mining industry, here illustrated by three industrial cases, which also show that when the Theory of Sampling (TOS) is applied correctly (ensuring unbiased sam-pling and analysis), considerable amounts of money can be saved.

Case 1

Sampling density influences the estimated value of mining plan alternatives

11 Oct 2021

Kim H. Esbensen

Independent researcher, consultant, owner, KHE Consulting, Copenhagen

11 Oct 2021

Geoff Lyman

Materials Sampling & Consulting. [email protected]

11 Oct 2021

Elke Thisted

PhD, Manager Process Control & Development On-Line Analysis, Glencore Nikkelverk AS; Head of organisational committee for WCSB10

11 Oct 2021

Pentti Minkkinen

Professor emeritus, Lappeenranta Lahti University of technology (LUT), Finland and President, Senior Consultant, Sirpeka Oy, Finland

11 Oct 2021

Richard C.A. Minnitt

Visiting Emeritus Professor, University of the Witwatersrand, Johannesburg, South Africa

11 Oct 2021

Kim H. Esbensen

KHE Consult

Money out the window—either way

9 Sep 2021

When previously industrialised or urbanised sites are redeveloped, the contamination of the soil is a vital consideration. It is essential that it is classified correctly as being fit for reuse or only for landfill, or even needing decontamination. When dealing with truck loads of soil, correct, representative sampling is essential to assure safety and to minimise unnecessary costs.

19 Jul 2021

Kim Esbensen has enlisted the support of another doyen of representative sampling, Pentti Minkkinen. In the commercial world, the reason for analysis comes down to money: whether ensuring you are getting what you paid for, but not providing more than necessary, or in regulatory compliance and the avoidance of fines. Kim’s Column has been pushing the importance of not overlooking the sampling step since its beginnings, and this edition provides clear examples where the consequences are costly; very costly.

24 May 2021

Many of you will be working in the cancer field, whether in diagnosis or research, in which case you will be very interested in this Sampling Column. Even if this is not your field of work, you will be interested from a personal point of view! It presents a fascinating idea and solution to improving the identification of different parts of a tumour and, thus, to provide better personalised treatment. “…in solid tumour oncology, representative sampling is truly a matter of life or death…”

12 Apr 2021

This cannot be true—surely sampling and weighing are different activities. Well yes—and no! Sampling and weighing of traded metal, mineral and agro commodities are different activities—but at one or several stages in the supply chain they will come together in a single focus point, which is value ($, EUR).

16 Mar 2021

The Sampling Column provides some easy-to-understand examples of what sampling errors are, what are the consequences of them and what can be done about them. Particular examples from pharma, PAT and NIR spectroscopy are provided.

3 Feb 2021

Oscar Dominquez here presents the critical role of QM in the mining sector, where everything is BIG: tonnages, challenges, environmental impact, profits, risks—illustrating how proper sampling is a major critical success factor also here. But the mining sector view is not unique; the QM prerogatives can be carried over to very many other sectors as well.

2 Dec 2020

There is hardly any other application field where correct sampling is as critically important than for Gold mineral resource estimation, because of the very low grades and the extremely irregular mineralisation heterogeneities encountered.

Latest Issue

Editor: Kim H. Esbensen

What is the meaning of analysing any sample if it cannot be documented to be representative? The answer is “none”, and that is the reason for this column. Starting with the Theory of Sampling, it builds into a valuable resource covering the theory and practice of representative sampling.
Read more about the Column Editor.