Avoiding surprises in coal testing: Rule #2

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

Rule 2: use a whole-of-supply-chain enterprise solution

It can be stated that the main objective of inspection is to validate what is predicted in the context of quantity and qualities in the mining value chain. When inspection produces results that invalidate the expected measurements, questions need to be raised as to what went wrong, including – but not limited to – sampling errors, assaying errors and human errors.

It is a well-established challenge in mining that obtaining a representative sample is in itself difficult. Ore bodies are generally large and heterogeneous, while the samples are in comparison very small. Consequently, a lot of effort is put into sampling techniques to ensure that samples are representative throughout the whole mining value chain.

A good sampling regime is only the beginning. In order to reduce surprises, which have often resulted in heavy penalties, mining companies now invest heavily in an integrated enterprise quality system. These systems are capable not only of offering visibility of the whole supply chain in terms of quantity and qualities, but are also able to provide the closed analytic loop that is often missing when isolated and disparate systems are employed.

A direct consequence of the use of disparate systems is the inability to reconcile between the mine and the final product delivered, which leads to the inability to improve the process – from refining the modelling used to detecting surprises before they become real.

Once there is a closed analytic loop between the initial samplings during exploration and the final product delivered to customers months or sometimes years later, the whole operation becomes self-correcting.

An example of the power of a closed loop system can be found in the metallurgical balancing process. It is relatively easy to monitor, because it is essentially a closed system (in coal, this process is often referred to as plant reconciliation). Ore arrives at one end and the finished product comes out at the other. Taking into account the processing factors, the assay data before and after the plant can be compared and used to improve the process over time, which should reduce surprises in measurement. It can be observed that the closer the feedback loop is, the easier it is to achieve the desired reconciliation.

The above example illustrates the power of a self-adjusting system based on a closed loop system, with the caveat that it relates to only a small segment of the supply chain. It is of no surprise, therefore, that more and more mining companies are making great effort to employ the whole-of-supply-chain approach when it comes to inventory and production solutions that offer an end-to-end closed loop system.

An essential component of a closed loop system is a central assay repository for the whole enterprise, which stores in one database all the assay results, from exploration, grade control, plant data and transportation and shipment samples. This central repository ensures high-quality information can be built up as time progresses and, in turn, makes the analysis of new samples much more accurate and predictable, leading to an improved mining process over time.

Continue reading here for rule #3: watch out for intentional malpractices. Rule #1: to inspect is better than to expect can be read here.

Written by Sang Ho. Edited by Jonathan Rowland.

Read the article online at: https://www.worldcoal.com/handling/03092014/world-coal-avoiding-surprises-in-coal-testing-coal1280/