Measuring process parameters to improve performance
Published by Jane Bentham,
Editorial Assistant
Global Mining Review,
Henry Kurth, Scantech, Australia, presents the benefits of representative, real-time conveyed flow measurement in improving material quality and process performance.
To improve quality or performance, there must be some means to measure the parameters requiring improvement, so that effectiveness can be evaluated and adjustments made to enhance outcomes. In the resources sector, and particularly in large processing operations, throughput rates can be many thousands of tonnes per hour. Very small improvements in process performance can have a major effect on overall economics and profitability – for example, a 1% improvement in recovery of a base metal can add tens of millions of dollars per annum to the bottom line. Demand is increasing for precise, timely, and representative measurement systems to ensure benefits can be quantified and further improvements implemented.
Approach
Some considerations in selecting a measurement solution include:
- Which parameters need to be quantified?
- At which point(s) in the process should measurements be taken?
- Which precisions need to be achieved for measurements to be useful?
- How frequently do the measurements need to be determined?
- What constitutes timely measurement to enable improvements?
- How long does it take for a change in control to take effect when responding to a measurement, and what is the cost of delaying a corrective action?
- Does sampling or online analysis provide the most suitable data?
- Which technologies should be considered?
- How will implementation and maintenance affect production?
- How is success determined?
- What payback period is appropriate to justify the chosen solution?
The example used here relates to that of a base metal mining and processing operation that mines ore and produces a base metal concentrate. The aim is to assess potential measurement solutions for mined material to optimise process performance and maximise metal recovered and economic returns. Another objective is to minimise any detrimental environmental, social, and governance (ESG) effects and save unnecessary expenditure.
Parameters that affect process performance may include ore quality, deleterious components, mineralogy of the ore and waste components, and other compositional characteristics. Some parameters unable to be measured may be determined using proxies for a parameter of interest that affects process performance. High compositional variability and large particle size usually limit the practicalities of sampling conveyed flows to determine quality in a timely manner to benefit process control. Online systems have therefore become the preference on such material flows.
Representative measurement
For the measurement technique to be representative, it should be able to comply with the theory of sampling, and thus provide an equal chance of any component to be included in the measurement. This precludes technologies that measure only the surface of material flows or bias measurement to a limited portion of the material because coarse process feed streams usually contain high compositional variability. The measurement location should allow for enough reaction time to respond to the quality in some way; diverting short increments based on composition and decision parameters based on process impact, blending with other quality materials, or feeding information backwards or forwards. Feed forward control can include flow rate control, reagent control, and other operational process variables that affect recoveries or product quality. Measurement prior to particle size reduction provides opportunities to influence the average quality proceeding to the next processing stage. Measurement of conveyed flows after primary crushing has become a common solution. Any material that is undesirable to process may be rejected, for example, parcels of waste material that generate no economic benefit in processing could be diverted before further crushing, grinding, or exposure to reagents. This also reduces energy consumption (a large contributor to greenhouse gas [GHG] emissions), water and reagent consumption, crushing and grinding consumables and equipment wear, and fine tailings generation. Other material diverted could be high in deleterious content or lower quality material that could be processed when higher quality feed is unavailable.
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