Following on to the conclusion of another successful MEI conference, Flotation ’13, some interesting comments and feedback have emerged that highlight the continuing interest in and need for mineralogical data in understanding flotation response – and some of the challenges that emerge from trying to obtain that.
Barry Wills’ blog of 18th November 2013 refers back to the prediction made by Professor Dee Bradshaw at Flotation ’11 that chemistry would dominate discussions; and how she has seen that shift to a point where mineralogy dominates at Flotation ’13. This point is further underlined by Dr Chris Greet (30th November 2013), who also makes the essential connection between the realisation of the value of mineralogy, and the hurdles encountered in generating and utilising valid mineralogical data correctly. Chris sights three commonly encountered hurdles:
1) Turn-around time
Mineralogical studies have long been considered time intensive: to a point where there is a widely held (mis)belief in industry that they take too long to produce any relevant data. In the same way however as the recognition of the value of mineralogy in understanding flotation response is changing, so too is the technology and accessibility of the tools.
Sample preparation, instruments and data processing are continually getting faster, and laboratories are being deployed closer and closer to the plant – at some sites they can now be found in the plant. For those sites without on-site mineralogical services (tools and/or skills), the number of service providers around the world is growing with many offering straight analytical services and others (such as MinAssist) offering comprehensive solutions to establish, manage, report and help interpret testwork programs and results. Postal services are highly efficient (in most places!), and a well-run routine testwork program can provide rapid results and real benefits.
As ever, the more focused the study and the clearer the objectives, the more optimised the turn-around time can become.
The cost, or perhaps more specifically the understanding of the perceived cost of undertaking process mineralogical testwork is an area that is lagging further behind. There are ways of speeding up turn-around time, and we can generate valid data through understanding the principles of the techniques and the objectives of the project. Quantifying the value and ROI however is much harder and is a topic that has been discussed here a number of times (When to Invest in Process Mineralogy – 13th September 2013 and What is the Return on Investment of Process Mineralogy – 13th August 2013). This accounts for why mineralogy is still seen by most as an additional optional expense; however it need not always be costly and in many cases it will save money on other testwork.
Those who routinely use mineralogical data in their operations come to rely on the understanding that brings to their decision making, and the ‘expense’ question moves from being one of cost to being one of value and the risk of not having that information means that it is part of routine operations.
Equally, in the same way as turn-around time can be optimised so too can the expense. An optimised testwork program will minimise expense (particularly in the case of routine work), and will most likely also directly save money by reducing the amount of other testwork by helping to keep that focused. It may not therefore even require ‘extra’ budget.
In order to save time and expense, process mineralogy studies can be streamlined; but this needs to be done carefully, and the resultant data needs to be interpreted and utilised within the framework of validity.
Chris uses the excellent example of some operators reducing costs and time by using ‘virtual sizing’ based on QEMSCAN data derived from un-sized samples to generate liberation data more quickly. Certainly these analysis will produce liberation ‘results’ much more quickly and cheaply as there is no need to split the sample in to a series of sized fractions, prepare multiple sample blocks and then undertake separate analysis of each fraction. However the underlying principle of stereology dictates that calculations of factors such as size and liberation will be inherently error prone and skewed if based on un-sized samples: rendering the data invalid.
It is the ‘tip of the iceberg’ effect. Given that particle sections are being analysed, how does one know on a population basis whether the sectional area of grains represent slices through the middle or through the tip of the grains of interest? Any size or liberation data should be based on sized fractions to reduce the error and generate better statistics. One can derive some information on the mineralogy from un-sized samples, but this is largely limited to the types of minerals present, elemental deportment and so on; not textural data. This is a classic example of a ‘false economy’.
That said however, it is important to understand that valid data to solve a particular challenge or answer a specific question does not necessarily mean spending more time and money. With experience this can often mean a reduction in these things where a focused study can become an optimised study. The key is to access the experience in how to do this.
Focus and Understanding
One of the most significant ways of improving the time, expense and accuracy of mineralogical testwork is project focus. The more defined, specific and understood the required outcomes are, the more streamlined the testwork can become. This can often have the knock-on effect of reducing the range of data required, and therefore the time it takes to collect, validate and interpret. If for example a program is aimed at understanding the liberation of copper sulphides in the flotation feed (or by way of another example, Mg deportment), then this can be relatively quick (and therefore cheap) to quantify by reducing the collection and handling of irrelevant data. A program to ‘look at the mineralogy of the flotation feed’ by comparison is all-encompassing; requiring significantly more data, analysis, validation and interpretation. At times that is necessary, but knowing when it is not can make a significant difference.
Equally, be careful! As with Chris’ case study of ‘virtual sizing’ based on the QEMSCAN analysis of un-sized samples, knowing where and how to use a data set is critical. By way of example, data collected for a focused study on the liberation of copper sulphides in the flotation feed is not likely to be valid for examining the gangue mineralogy.
Take the time to understand what is and is not possible, or utilise the services of those with specialist process mineralogy experience, in order to find the right path to valid data in an optimal time frame and budget.
– Mineralogy is vital in the understanding flotation response of an ore type
– Mineralogical studies need, first and foremost, to be based on valid data otherwise they will at best be a waste of time and money, and at worst lead to erroneous decisions
– There is often a balance to be struck between the time spent, the validity of the data collected and the expense – but don’t assume the right data means greater expense or time!
– Mineralogical studies can be undertaken quickly, efficiently and correctly if well organised and well managed
– Those who routinely use mineralogy in their operations reply on such data, and consider it necessary in reducing operational risk and improving results
As an example of a focused study, the MinAssist Flotation Health Check provides a method of undertaking a snap-shot audit of the performance of a flotation circuit quickly and efficiently. If undertaken on a routine basis, this model can be further tailored and streamlined to a particular operation, whilst still maintaining a valid framework.
How far away do you think the industry is from making the step from mineralogy being ‘extra’ to ‘necessary’? Is that happening now, or is it still largely lip-service? We would love to hear your thoughts…