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Avoiding surprises in coal testing

Published by
World Coal,

Sang Ho, Ventyx – and ABB Co., US, launches a search for the eureka moment in coal testing and inspection.

Despite the advances in technology, specifically in the areas of weighing and measurement devices, some things have remained unchanged over the centuries. One such unchangeable is the principle employed to determine the cargo weight of an ocean-going vessel. It is based on the Archimedes Principle, which states that “any floating object displaces its own weight in fluid”. Legend has it that at the moment inspiration hit, the ancient scientist is said to have run stark naked through the streets shouting: “eureka!” (I have found it!).

This article examines the challenges faced by mining companies today and shares some insights into how to overcome some of these based on an overarching guiding principle. In doing so, there is the hope that the mining community will discover its own moment of eureka.

Nowadays, large penalties can be incurred at the delivery of coal (or any minerals) shipments, due to the deviation between what is delivered and what is stipulated in the sales contract. It can be argued that, in many cases, some of the penalties paid are intentionally engineered by the mining companies for various reasons. But, by and large, a good proportion of penalties are caused by what can only be termed as surprises in terms of shipment assay results. This leads to the following guiding principle, which will be used as the basis of the discussions that follow.

The principle of no surprises

The principle of no surprises begins with the element of assaying, or testing. There are essentially three parts to the mining value chain: determining what is under the ground, getting the material out of the ground and getting it ready for sale. Hypothetically, assuming the mining company does a good job in the exploration and resource model estimation and that it furthermore has a good handle on the mining process, it can be expected that what comes out of the ground should closely match the model (give or take an acceptable percentage of errors). Similarly, having materials arrive at the ROM pads in a predictable and controlled manner and assuming that the processing plant is performing at its designed operating capacity, what comes out of the plant should also be predictable. Furthermore, assuming the logistics of transporting the final product to the port is void of human errors, the question is, where do the surprises come from?

In reality, mining involves a complex chain of processes, which are often influenced by a number of uncertainties, including dilution factors, stockpile space restrictions, sampling errors, human errors and contamination (intentional or otherwise), etc. Therefore, based on the guiding principle, it can be useful to observe some of the areas where the surprises may come from, to see what can be learned from them.

Rule 1: to inspect is better than to expect

The first potential surprise offered during the natural sequence of the mining value chain is the unexpected differences between the model estimation and blast sample results, in terms of volume and assay qualities. The model may have given incorrect estimations, or there may be an issue with the blasting or with the sampling of the blast sample(s). Alternatively, the problem might lie in the assaying process by either an onsite or an outsourced laboratory, which in itself is subject to a number of systemic, as well as human, errors.

As an illustration, one coal mine operated an onsite laboratory with minimum staff. The mine recently replaced the old Excel-based system with a laboratory information management system (LIMS). Through the audit trail functionality provided by the LIMS, it was discovered that certain assay results during night shift were entered into the system without going through the proper analytical procedure. No generalisation is made here that this practice is widely used in the industry, but one can only imagine the sequence of events leading to this anomaly by putting oneself in the shoes of the lone laboratory technician working the night shift. A plant sample comes in every few hours, it looks black, and it looks no different to any other ones so far during the shift, so it must be roughly the same values. The incident in this story was only detected by a system that offers the capability to inspect the audit trail. The moral of this story, therefore, is that to inspect is better than to expect.

Continue reading here for rule #2: use a whole-of-supply-chain enterprise solution.

Written by Sang Ho. Edited by

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