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Title:
REAL-TIME MONITORING AND PERFORMANCE ADVISORY SYSTEM FOR MULTI-CELL FROTH FLOTATION SYSTEM
Document Type and Number:
WIPO Patent Application WO/2018/225003
Kind Code:
A1
Abstract:
The present invention provides systems and methods for monitoring a froth flotation system (100) that includes a number of flotation cells (102). Any one or more of a plurality of cells forming part of a froth flotation system may be individually monitored with appropriate sensors (110, 111) to determine various properties associated with the flotation process. Plant-specific data may be provided by an operator or may be determined by appropriate measuring components. By analysing the plant- specific data and measured properties, performance indicators of the complete system as well as for individually monitored cells may be determined. The performance indicators may be used to classify system performance. The system may allow operating inefficiencies to be determined, particularly per cell, and provide an operator with an advisory action to address or even cure the operating inefficiency, or the system may facilitate such addressing or curing automatically.

Inventors:
HAASBROEK, Adriaan Lodewicus (8 Vriende Street, Gardens, 8001 Cape Town, 8001, ZA)
BROWN, Robert Pieter (655 De Velde, De Beers AveSomerset West, 7130 Cape Town, 7130, ZA)
STREICHER, Simon Jacobus (801 Brookdale, Tenerife AvenueSomerset Lake, Somerset West 7130 Cape Town, 7130, ZA)
VAN DER BIJL, Leendert (9 Eagle Crescent, Somerset West, 7130 Cape Town, 7130, ZA)
Application Number:
IB2018/054106
Publication Date:
December 13, 2018
Filing Date:
June 07, 2018
Export Citation:
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Assignee:
STONE THREE MINING SOLUTIONS (PTY) LTD (24 Gardner Williams Ave, Paardevlei Somerset West, 7130 Cape Town, 7130, ZA)
International Classes:
B03D1/02; B03D1/14
Attorney, Agent or Firm:
VON SEIDELS INTELLECTUAL PROPERTY ATTORNEYS (P O Box 440, Century City, 7446 Cape Town, 7446, ZA)
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Claims:
CLAIMS:

A computer-implemented method for monitoring a froth flotation process including multiple flotation cells, the method including the steps of:

receiving plant variables relating to operation of the flotation process; receiving properties measured in real-time at at least one flotation cell in the flotation process, the properties being measured by one or both of a sensor analysing a froth phase and a sensor analysing a pulp phase of the at least one flotations cell;

processing data defining the plant variables and measured properties to identify performance indicators; and

classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

The method as claimed in claim 1 , including the step of determining estimated future performance of the process based on the performance indicators, the estimated future performance including an expected grade of concentrate, an expected recovery of target material, and mass pull.

The method as claimed in Claim 2 wherein the classification defining the froth flotation process includes indicating whether the grade of concentrate is high, medium or low, and whether recovery of target material is high, medium or low.

The method as claimed in any one of the preceding claims including the steps of monitoring the data for an operating inefficiency manageable by operator input, and, responsive to detecting such an operating inefficiency, providing a notification of an advisory action required to address the inefficiency.

The method as claimed in Claim 4 including the step of automatically feeding back instructions to key components of individual cells or the process as a whole to automatically adjust operating parameters to address operating inefficiencies.

The method as claimed in Claim 4 including the step of transmitting one or more of the performance indicators, the estimated future performance, the operating inefficiencies, the advisory actions, or an alarm to a display. The method as claimed in any one of the preceding claims wherein the properties measured at the at least one flotation cell include any one or more of bubble size, froth velocity, froth stability, froth height above a lip of the cell, froth colour, froth volume, mass pull, pulp gas holdup, pulp gas velocity, and pulp bubble size distribution.

The method as claimed in any one of the preceding claims wherein the plant variables include any one or more of aeration rate, reactant addition, stirring motor power draw, mill power, mill load, ore hardness, ore grade, pulp density, pulp viscosity, pulp level, flotation feed rate, flow rate, and mill product particle size distribution.

The method as claimed in any one of the preceding claims wherein the step of processing data includes performing data selection and/or data cleaning by any one or more of ignoring values below a predetermined minimum value, ignoring values above a predetermined maximum value, ignoring values falling outside selected standard deviations of the mean of measured values, ignoring values where rate-of-change values are above a certain threshold, and considering variable relationships between data.

The method as claimed in any one of the preceding claims wherein the step of processing data includes performing dimension reduction techniques in the form of any one or more of principle component analysis, projection to latent structures, and linear discriminant analyses.

The method as claimed in any one of the preceding claims wherein the step of processing data includes applying machine learning and fundamental models, the machine learning including any one or more of a long short-term memory recurrent neural network, a feedforward neural network, deep learning, and probabilistic graphical models.

The method as claimed in any one of claims 4 to 1 1 that includes the step of tracking a number of advisory actions provided, the step of comparing the number of advisory actions to a pre-determined limit, wherein the step of providing an advisory action occurs only if the advisory action limit is not exceeded, and the step of resetting the advisory action tracking after a predetermined time period.

13. The method as claimed in any one of the preceding claims wherein the performance indicators are any one or more of a grade of concentrate, a recovery of target material; and mass pull.

The method as claimed in any one of the preceding claims wherein the step of receiving properties includes receiving properties measured in real-time at a plurality of the flotation cells in the flotation process.

A system for monitoring a froth flotation process including multiple flotation cells, the system including:

at least one sensor associated with at least one of the flotation cells and configured to measure properties of a flotation process of the cell;

a receiving component configured to receive plant variables; and

a processor in data communication with the at least one sensor and receiving component and configured to:

process data defining the plant variables and measured properties to identify performance indicators; and

predict future performance of the system based on the performance indicators, the future performance including an expected grade of target material and an expected recovery of target material.

A system for monitoring a froth flotation process, the system including a memory for storing computer-readable program code and a processor for executing the computer- readable program code, and comprising:

a plant variable receiving component for receiving plant variables relating to operation of the flotation process;

a cell property receiving component for receiving cell properties measured at at least one of a plurality of flotation cells in the process, the properties being measured by at least one sensor analysing a froth phase and one sensor measuring a pulp phase of the applicable flotation cell;

a data processing component for processing data defining the plant variables and measured properties to identify performance indicators; and

a performance classification component for classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

17. A computer program product for monitoring a froth flotation process, the computer program product comprising a computer-readable medium having stored computer- readable program code for performing the steps of:

receiving plant variables relating to operation of the flotation process; receiving properties measured at at least one of a plurality of flotation cells in the flotation process, the properties being measured by at least one sensor analysing a froth phase and one sensor analysing a pulp phase of the applicable flotation cell;

processing data defining the plant variables and measured properties to identify performance indicators; and

classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

Description:
REAL-TIME MONITORING AND PERFORMANCE ADVISORY SYSTEM FOR MULTI-CELL

FROTH FLOTATION SYSTEM

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority from South African provisional patent application number 2017/03892 filed on 7 June 2018, which is incorporated by reference herein.

FIELD OF THE INVENTION

This invention relates to a monitoring system for a froth flotation system, particularly for a froth flotation system comprising multiple cells. Furthermore, the invention extends to a system for measuring real-time performance of the froth flotation system and configured to provide advisory actions if the performance is not satisfactory.

BACKGROUND TO THE INVENTION

Froth flotation is a process for separating minerals from gangue by taking advantage of differences in their hydrophobicity. Hydrophobicity differences between valuable minerals and waste gangue are managed and increased through the use of surfactants and wetting agents.

The flotation process typically takes place in an open tank and consists of a pulp phase, typically known as the "reactor", and a froth phase, typically termed the "separator". A slurry of hydrophobic and/or hydrophilic particles are introduced to tanks known as flotation cells, and are aerated to produce bubbles. The hydrophobic particles attach to the bubbles, which in turn rise to the surface in the form of a froth. The froth may then be removed to produce a concentrated target material.

Froth generated by the flotation process may be analysed to determine properties and characteristics of the concentrate. A combination of information gathered by analysing the froth and input variables describing elements of the flotation system may provide performance indicators for the flotation system. Analysis of the froth may be performed in a laboratory. A sample is taken from a cell for analysis, and analysed in a laboratory where the results are generally only available after 8 to 24 hours, or more. This is clearly undesirable as this long period of time to receive feedback may allow a cell to run ineffectively for an extended period of time. Multiple samples may be taken over time and combined so that a single laboratory analysis may be performed thereon. This, however, will not provide immediate feedback, and will only provide information averages over the sampling period. Furthermore, multiple cells often form part of a flotation plant. A standard practise to analyse such a flotation process is to take a sample from more than one cell and potentially from more than one location in a cell, possibly numerous times over an extended operating period, and combine the samples so that only a single general sample needs to be analysed to provide an estimation of properties of the flotation process normalised over all of the cells. It will be apparent that this may lead to ineffective results, potentially hiding a problematic cell. In some cases, automatic analysers are provided, but such devices typically only measure a complete stream, which is a combination of multiple cells. Such systems therefore still do not provide adequate information. Mass pull, a property of a flotation process, is often determined by analysing product sump levels. Where a flotation system includes multiple cells, a sump may be fed by multiple cells. This may provide the same problems whereby an undesired performance is not evident due to measurements not considering individual cell performances. The applicant has developed sensors which may be used to provide properties and characteristics of both froth and pulp phases of individual flotation cells in situ, without the need to do offline analysis. There is a need for these sensors to be employed to alleviate the abovementioned problems, at least to some extent. In the remainder of the specification, the term "grade of concentrate" should be construed to mean a percentage of concentrate mass that is a target material. For example, a grade of 80% means that 80% of the concentrate mass produced is of a desired target material, for example copper. The term "recovery of target material" should be construed to mean a percentage of target material in a feed that is recovered in the concentrate. For example, a recovery of 80% means that 80% of target material in the feed is recovered in the concentrate. The term "mass pull" should be construed to mean a rate at which concentrate is produced by the flotation process. For example, a mass pull of 100kg/h mean that a particular cell, group of cells or the system as a whole is producing 100kg/h of concentrate. The preceding discussion of the background to the invention is intended only to facilitate an understanding of the present invention. It should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was part of the common general knowledge in the art as at the priority date of the application.

SUMMARY OF THE INVENTION

In accordance with the invention there is provided a computer-implemented method for monitoring a froth flotation process including multiple flotation cells, the method including the steps of:

receiving plant variables relating to operation of the flotation process;

receiving properties measured in real-time at at least one flotation cell in the flotation process, the properties being measured by one or both of a sensor analysing a froth phase and a sensor analysing a pulp phase of the at least one flotations cell;

processing data defining the plant variables and measured properties to identify performance indicators; and

classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

Further features provide for the method to include the step of determining estimated future performance of the process based on the performance indicators, the estimated future performance including an expected grade of concentrate, an expected recovery of target material, and mass pull.

Still further features provide for the classification defining the froth flotation process to include indicating whether the grade of concentrate is high, medium or low; and whether recovery of target material is high, medium or low.

Further features provide for the method to include the steps of: monitoring the data for an operating inefficiency manageable by operator input; and, responsive to detecting such an operating inefficiency, providing a notification of an advisory action required to address the inefficiency. The operating inefficiency may be directed at a single cell of the process, and the advisory action may be aimed at addressing the inefficiency for only that cell. In a situation wherein the inefficiency is particularly dangerous or serious, the advisory action may be provided in the form of or as part of an alarm. Logic rules may be employed to determine when an operating inefficiency may be managed by operator input. The method may also include automatically feeding back instructions to key components of individual cells or the process as a whole to automatically adjust operating parameters to address operating inefficiencies. Instructions may be displayed to an operator, and may also be automatically provided over an Object Linking and Embedding for Process Control (OPC) communication system to an applicable control system.

Still further features provide for the method to include the step of: transmitting one or more of the performance indicators, estimated future performance, operating inefficiencies, advisory actions, or alarm to a display. Yet further features provide for the properties measured at the at least one flotation cell to include any one or more of: bubble size, froth velocity, froth stability, froth height above a lip of the cell, froth colour, forth volume, mass pull, pulp gas holdup, pulp gas velocity, and pulp bubble size distribution. Further features provide for the plant variables to include any one or more of: aeration rate, reactant addition, stirring motor power draw, mill power, mill load, ore hardness, ore grade, pulp density, pulp viscosity, pulp level, flotation feed rate, flow rate, and mill product particle size distribution. Still further features provide for the step of processing data to include performing data selection and/or data cleaning by any one or more of: ignoring values below a predetermined minimum value; ignoring values above a predetermined maximum value, ignoring values falling outside selected standard deviations of the mean of measured values; ignoring values where rate-of- change values are above a certain threshold; considering variable relationships between data; and the like.

Yet further features provide for the step of processing data to include performing dimension reduction techniques in the form of any one or more of: principle component analysis; projection to latent structures; linear discriminant analyses; and the like.

Further features provide for the step of processing data to include applying machine learning and fundamental models; and for the machine learning to include any one or more of: a long short-term memory recurrent neural network; a feedforward neural network; deep learning; probabilistic graphical models; and the like. Still further features provide for the method to include the steps of: tracking a number of advisory actions provided; comparing the number of advisory actions to a pre-determined limit; for the step of providing an advisory action to occur only if the advisory action limit is not exceeded; and for the advisory action tracking to be reset after a predetermined time period.

Yet further features provide for the performance indicators to be any one or more of: a grade of concentrate; recovery of target material; and mass pull. The performance indicators may be for a specific cell, for a bank of or selection of cells, or overall and for all of the cells. The step of receiving properties may include receiving properties measured in real-time at a plurality of the flotation cells in the flotation process. The plurality of flotation cells may be a selection from all of the cells, for example a bank of cells, or may include all of the cells.

In accordance with a further aspect of the invention there is provided a system for monitoring a froth flotation process including multiple flotation cells, the system including:

at least one sensor associated with one of the flotation cells and configured to measure properties of a flotation process of the cell;

a receiving component configured to receive plant variables; and

a processor in data communication with the at least one sensor and receiving component and configured to:

process data defining the plant variables and measured properties to identify performance indicators; and

predict future performance of the system based on the performance indicators, the future performance including an expected grade of target material and an expected recovery of target material .

Further features provide for the receiving component to include an input device for receiving input from an operator; and a display to display information regarding the process as well as advisory actions to an operator.

Still further features provide for the at least one sensor to include both a froth phase and a pulp phase sensor; and for each measured flotation cell to have a froth phase and pulp phase sensor associated therewith. A yet further feature of this aspect of the invention provides for the system to include a feedback path whereby instructions may be issued to key components of individual flotation cells or the process as a whole to automatically adjust operating parameters to address measured or calculated operating inefficiencies.

In accordance with a further aspect of the invention there is provided a system for monitoring a froth flotation process, the system including a memory for storing computer-readable program code and a processor for executing the computer-readable program code, and comprising: a plant variable receiving component for receiving plant variables relating to operation of the flotation process;

a cell property receiving component for receiving cell properties measured at at least one of a plurality of flotation cells in the process, the properties being measured by at least one sensor analysing a froth phase and one sensor measuring a pulp phase of the applicable flotation cell;

a data processing component for processing data defining the plant variables and measured properties to identify performance indicators; and

a performance classification component for classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process. Still further features provide for the system to include a future performance determining component for determining estimated future performance of the system based on the performance indicators, the future performance including an expected grade of target material and an expected recovery of target material being recovered. Further features provide for the system to include an operating inefficiency component including a monitoring component for monitoring the data for an operating inefficiency manageable by operator input, a detecting component for detecting such an operating inefficiency, and a notification component for, responsive to detecting an operating inefficiency, providing an advisory action required to address the inefficiency to a display.

Still further features provide for the system to include a display component for displaying information regarding monitoring of the process to an operator, the information including any one or more of performance indicators, estimated future performance, operating inefficiencies, and advisory actions. Yet further features provide for the system to include an advisory action tracking component for tracking a number of advisory actions provided and including a comparing component for comparing the number of advisory actions to a pre-determined limit; and a prevention component to prevent the number of provided advisory actions from exceeding a predetermined number.

In accordance with a further aspect of the invention there is provided a computer program product for monitoring a froth flotation process, the computer program product comprising a computer-readable medium having stored computer-readable program code for performing the steps of:

receiving plant variables relating to operation of the flotation process;

receiving properties measured at at least one of a plurality of flotation cells in the flotation process, the properties being measured by at least one sensor analysing a froth phase and one sensor analysing a pulp phase of the applicable flotation cell;

processing data defining the plant variables and measured properties to identify performance indicators; and

classifying the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

Further features provide for the computer-readable medium to be a non-transitory computer- readable medium and for the computer-readable program code to be executable by a processing circuit. An embodiment of the invention will now be described, by way of example only, with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS In the drawings:

Figure 1 is a schematic diagram of an exemplary system for monitoring a froth flotation process; Figure 2 is a flow diagram of a method for monitoring a froth flotation process according to the system of Figure 1 ; Figure 3 is a block diagram which illustrates an exemplary system for monitoring a froth flotation process; Figures 4A and 4B are graphs showing experimental results indicating a correlation between predicted and actual values obtained using the method and systems of Figures 1 to 3; and

Figure 5 shows a block diagram of an electronic computing device that may be used in embodiments of the disclosure.

DETAILED DESCRIPTION WITH REFERENCE TO THE DRAWINGS

The present invention provides systems and methods for monitoring a froth flotation system that includes a number of flotation cells. A plurality of cells forming part of a froth flotation system may be individually monitored with appropriate sensors to determine various properties associated with the flotation process. Plant-specific data may be provided by an operator or may be determined by appropriate measuring components, typically known as plant instrumentation, such as ore measuring sensors, flow meters, weightometers, level meters, density meters, power meters, pressure meters, valve position meters, and the like. Alternatively, plant-specific data may be read by or retrieved from an applicable process historian. By analysing the plant-specific data and measured properties, performance indicators of the complete system as well as for individual cells may be determined. The performance indicators may be used to classify system performance by defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process. This may be as simple as indicating whether the grade of concentrate and recovery of target material is low, medium or high. The system may allow operating inefficiencies to be determined, particularly per cell, and provide an operator with an advisory action to address or even cure the operating inefficiency. Additionally, the performance indicators may be used to predict future yield of target material, particularly an expected grade of concentrate and recovery of target material for the entire system, but also allows for a per-cell prediction.

Figure 1 is a schematic diagram which illustrates an exemplary system (100) for monitoring a froth flotation system. The system includes four flotation cells (102) in which froth flotation processes are taking place. As is known in the art, each flotation cell includes an aerator (104) that introduces bubbles into a pulp phase (106) containing the target material in the cells (102). Hydrophobic particles including the target material attach to the bubbles, which rises to the surface of the pulp phase (106) and form a froth phase (108) on top of the pulp phase (106). The froth (108) may then be removed as is known in the art for further processing and recovery of the target material.

In the present embodiment, each cell (102) includes a froth phase sensor (1 10) capable of analysing the froth phase (108) of the applicable cell, as well as a pulp phase sensor (1 1 1 ) capable of analysing the pulp phase (106) of the applicable cell. In combination the sensors (1 10, 1 1 1 ) measure properties of the flotation cell in which they are configured. Each sensor (1 10, 1 1 1 ) is in data communication with a processor (1 12) associated with an electronic computing device, presently a computer (1 14). The computer (1 14) acts as a receiving component, receiving data from the sensors (1 10, 1 1 1 ). The computer (1 14) includes an input device (1 16), in the present embodiment a keyboard, with which an operator may input information required for operation of the system. The input device (1 16) is also in data communication with the processor and may be used by an operator to provide plant variables defining operating aspects of the system to the processor (1 12). A display (1 18) is also in data communication with the processor and may display information concerning the system and its operation. It should be noted that although the present embodiment includes both a froth phase sensor and a pulp phase sensor, it may only include one such sensor, for example only a froth phase sensor. Sufficient information may be determined from a single sensor and which may allow suitable operation of the system. It is, however, envisaged that some plant variables may be measured by appropriate sensors or may be determined by a controller device managing operation of the system. The computer (1 14) may be the controller managing operation of the system, with the plant variables then being easily accessible thereon. The system (100) above may implement a method for monitoring a froth flotation process. An exemplary method for monitoring a froth flotation process is illustrated in the flow diagram (200) of Figure 2. The method is performed on the processor (1 12) of Figure 1 .

The processor (1 14) receives (202) plant variables from either one or both of the input device (1 16) and appropriates sensors (1 10, 1 1 1 ) measuring such variables. The variables may include any one or more of, but are not limited to, aeration rate, reactant addition, stirring motor power draw, mill power, mill load, ore hardness, ore grade, pulp density, pulp viscosity, pulp level, flotation feed rate, flow rate, and mill product particle size distribution. It will be apparent to a person skilled in the relevant art that some of these properties will typically be known to an operator of the system beforehand, and some properties may be determined by sensors monitoring operation of the various components.

The processor (1 14) further receives (204) properties relating to the flotation process in each, or in some cases at least a plurality, of the cells that make op the flotation system/process, and measured by the sensors (1 10, 1 1 1 ) analysing the pulp (106) and froth (108) phases of the applicable flotation cells (102). It should be noted that in certain embodiments, not all cells may need to be monitored. If one cell, or a selection of cells such as a bank of cells, have a significant or the largest influence on the overall performance of the flotation system, only such one cell or selection of cells may need to be monitored. This may be due to the fact that a specific cell is larger than other cells, with the result that its performance may have a greater influence on the performance of the entire process than that of other, smaller cells. The properties may include any one or more of, but are not limited to, bubble size, froth velocity, froth stability, froth height above a lip of the cell, froth colour, froth volume, mass pull, pulp gas holdup, pulp gas velocity, and pulp bubble size distribution. The processor (1 14) may then process (206) data defining the plant variables and measured properties to identify performance indicators. Specific algorithms and/or rules will typically define the impact of the data to the performance indicators.

Processing data may include performing data selection and/or data cleaning on a dataset containing the plant variables and flotation process properties. This may be performed according to any method known in the art, including, but not limited to: ignoring values above a predetermined maximum value, ignoring values falling outside selected standard deviations of the mean of measured values (for example the "Six Sigma method"), ignoring values where rate-of-change values are above a certain threshold, considering variable relationships between data, and the like.

Then, data may further be processed by performing dimension reduction techniques thereon. This may be in the form of, but is not limited to: principle component analysis, projection to latent structures, linear discriminant analyses, and the like. Further data analyses may be done by applying machine learning and/or fundamental models thereto. The machine learning may include any one or more of: a long short-term memory recurrent neural network, a feedforward neural network, deep learning, probabilistic graphical models, and the like.

The estimated performance data will typically be transmitted to the display (1 18) for display to an operator. The processor then classifies (207) the performance of the system based on the performance indicators. Classification defines the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process.

Classification of the froth flotation process need only include indicating whether the grade of concentrate is relatively high, medium or low, and whether the recovery of target material produced by the process is relatively high, medium or low. These classification options may be sufficient to indicate to an operator whether the system is operating adequately. The classification may also be provided to the display for operator information.

While processing (206) the data, the processor may monitor (208) the data for an operating inefficiency which is manageable or even curable by operator input. Should such an inefficiency be detected (210), a notification to that effect will be provided (212) to the display. The notification will typically include an advisory action which may address the inefficiency. The advisory actions may attempt to modify a process driver, which may be known to lead to the detected inefficiency.

As an example, an inefficiency may lead to poor performance as a result of an incorrect aeration rate. By providing an advisory action that will address the inefficiency, for example to lower a pulp level of the cell at which the inefficiency is detected or to reduce an aeration rate at the cell, the inefficiency may be addressed and the expected future performance may be improved for the cell, and therefore also for the overall process. As a further example, in the event that the system recognises that the flotation process has moved from a normal operation cluster to a low density feed cluster. This information may be interpreted, and the operator may be informed that the process may now be run on higher aeration rates, and with less activators added to the slurry. As another example, should the system detect that recovery prediction has dropped significantly, and it is noted that the air flow rate on a specific cell has also changed, the operator may be notified to raise or lower the air flow rate, as applicable, in order to attempt to rectify the reduced recovery prediction.

It is envisaged that these advisory actions may be displayed to the operator on the display, or in any other suitable manner, or may be written back to a Supervisory Control and Data Acquisition (SCADA) system in use for viewing. The SCADA system may be the only physical interface for an operator to use and interact with. It is further envisaged that the system may detect operating clusters where an operator may be allowed to act aggressively, and instruct an Object Linking and Embedding for Process Control (OPC) in use to automatically respond to operating inefficiencies, without the need for further operator input.

The method may include monitoring (214) advisory actions provided and/or recommended to an operator. This may include tracking a number of advisory actions provided, and comparing the number to a predetermined maximum number being a pre-determined advisory action limit. A further advisory action, or a further identical advisory action, may only be provided if this limit has not been reached. Tracking of the advisory actions may be reset after a predetermined time period. This may allow only a certain number of actions to be provided in a given time period, or may prevent the continuous providing of the same advisory action. It is envisaged that some advisory actions may be prioritised over others, so that an operator is notified of a higher-priority advisory action before a lower-priority action.

Based on the performance indicators, expected future performance of the system, and possibly also for each individual cell, may be determined (216). At least an expected grade of concentrate and expected recovery of target material that may be recovered may be provided to define the future performance of the system. The expected future performance may be provided (218) for display on an appropriate display device. Performance indicators may be directed at, but are not limited to, a grade of concentrate, recovery of target material, and mass pull. The performance indicators may be for a specific cell, for a bank of or selection of cells, or overall and for all of the cells. It is envisaged that the expected future performance may also be indicated as a high, medium or low grade of concentrate and recovery of target material produced by the process.

It is envisaged that a particular operating inefficiency may be identified as being particularly dangerous or serious. In such a case, an alarm notification, preferably visual and audible, may be provided to an operator as part of the advisory action notification. It will be apparent that specific logic rules may be employed to determine when an operating inefficiency may be solved by operator input.

The advisory action may be in the form of an action that will impact the entire system, but may also be an action to be performed on a single cell only. As the flotation process properties may be measured for each cell individually, and plant variables individual to a cell may also be independently monitored, the processor is able to determine the performance of each individual monitored cell. The operator may then be provided with feedback as to each monitored cell's performance in near real-time (e.g. in the order of seconds or possibly even milliseconds). It is envisaged that the display will show performance indicators for not only the overall process, but also for each monitored cell forming part of the process.

Instead of performing a laboratory analysis on a combined sample which may hide individual cells' inefficiencies, the present invention allows an operator to identify and address inefficiencies in individual cells in near real-time. As lengthy, and potentially costly, laboratory or otherwise offline analysis is no longer required to determine an inefficiency, the present invention allows speedy management and resolution of inefficiencies on a per-cell basis.

It is envisaged that feedback as to system operation, system performance, as well as advisory actions and expected future performance will be provided to an operator in a visualized manner to facilitate interactive investigation of displayed data. The feedback may be provided via a feedback path of the system. The feedback path may allow instructions to be issued to key components of individual flotation cells, or the process as a whole, to automatically adjust operating parameters to address measured or calculated operating inefficiencies. The key components may be components that enable alterations to the froth flotation process so that it may to operate more efficiently.

While the above examples only includes 4 cells as part of a froth flotation process, it will be apparent to a person skilled in the art that any number of cells may form part of the system and that the systems and methods forming part of the present disclosure will be equally suited to operate with any number of cells. Additionally, while only a single froth phase and single pulp phase sensor is shown for each cell in Figure 1 , multiple sensors may be provided to measure the required process properties. The sensors may also be placed or located at various locations of the cells, as required. It is also foreseen that only selected cells in the process may be actively monitored. Various components may be provided for implementing the method described above with reference to Figure 2. Figure 3 is a block diagram which illustrates exemplary components which may be provided by an electronic device (300) defining a system for monitoring a froth flotation system.

The electronic device (300) may include a processor (302) for executing the functions of components described below, which may be provided by hardware or by software units executing on the electronic device (300). The software units may be stored in a memory component (304) and instructions may be provided to the processor (302) to carry out the functionality of the described components. Some or all of the components may be provided by a software application downloadable onto and executable on the electronic device (300).

The electronic device (300) further includes a plant variable receiving component (306) adapted to receive plant variables relating to operation of the froth flotation system, a cell property receiving component (308) adapted to receive cell properties measured at each cell and relating to its flotation process, a data processing component (310) adapted to process data defining the plant variables and measured properties to identify performance indicators, a performance classification component (31 1 ) adapted to classify the performance of the system based on the performance indicators, the classification defining the froth flotation process in terms of at least a grade of concentrate and recovery of target material produced by the process, and a future performance determining component (312) adapted to determine estimated future performance of the system as described above.

The electronic device (300) further includes an operating inefficiency component (314), which includes a monitoring component (316) adapted to monitor the data for an operating inefficiency manageable by operator input, a detecting component (318) adapted to detect such an operating inefficiency, and a notification component (320) adapted to, in response to detecting an operating inefficiency, provide an advisory action required to address the inefficiency to a display. An advisory action tracking component (321 ) may be provided to track a number of advisory actions provided. The advisory action tracking component (321 ) may include a comparing component for comparing the number of advisory actions to a pre-determined limit. A prevention component may also form part of the advisory action tracking component, and may be configured to prevent the number of advisory actions from exceeding the pre-determined limit. The electronic device (300) also includes a display component (322) adapted to display information regarding monitoring of the process to an operator. As described above, the information may include any one or more of performance indicators, estimated future performance, operating inefficiencies, and advisory actions.

Experimental results by the applicant has rendered a 94.8% classification accuracy of predicted recovery of target material, with an R-squared value of +- 0.7. A 97.4% accurate classification of concentrate grade in categories of good, normal and bad was also achieved. . Figure 4A is a graph (400) illustrating a correlation between predicted recovery of target material and actual recovery measured during production froth flotation performance using the present system and methods. An x-axis (402) represents time, while a y-axis (404) represents a recovery value. Predicted recovery is indicated by a dotted line (406), and actual recovery by a solid line (408). Rectangles (409) are drawn around bad quality sections determined by the algorithms responsible for performing data cleaning as described above.

Figure 4B is a graph (410) illustrating a correlation between predicted grade of concentrate and actual grade measured during production froth flotation performance using the present system and methods. An x-axis (412) represents time, while a y-axis (414) represents a grade value. Predicted grade is indicated by a dotted line (416), and actual grade by a solid line (418). Rectangles (419) are again drawn around bad quality sections determined by the algorithms responsible for performing data cleaning as described above.

As mentioned above, the systems and methods described may be configured to automatically provide instructions to key components of individual cells or the process as a whole to automatically adjust operating parameters in order to address any detected operating inefficiencies. The detecting component may then be further adapted to detect an operating inefficiency which could automatically be addressed without the need for operator input, and an operating inefficiency addressing component may be provided to automatically address the inefficiency. In such a case, an operator may only be notified of the inefficiency and be informed that the system has automatically addressed it. The operator may be informed how the system has attempted to address the inefficiency.

Figure 5 illustrates an example of an electronic computing device (500) in which various aspects of the disclosure may be implemented. The computing device (500) may be embodied as any form of data processing device including a personal computing device (e.g. laptop or desktop computer), a server computer (which may be self-contained, physically distributed over a number of locations), a client computer, or a communication device, such as a mobile phone (e.g. cellular telephone), satellite phone, tablet computer, personal digital assistant or the like. Different embodiments of the computing device may dictate the inclusion or exclusion of various components or subsystems described below.

The computing device (500) may be suitable for storing and executing computer program code. The various participants and elements in the previously described system diagrams may use any suitable number of subsystems or components of the computing device (500) to facilitate the functions described herein. The computing device (500) may include subsystems or components interconnected via a communication infrastructure (505) (for example, a communications bus, a network, etc.). The computing device (500) may include one or more processors (510) and at least one memory component in the form of computer-readable media. The one or more processors (510) may include one or more of: CPUs, graphical processing units (GPUs), microprocessors, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs) and the like. In some configurations, a number of processors may be provided and may be arranged to carry out calculations simultaneously. In some implementations various subsystems or components of the computing device (500) may be distributed over a number of physical locations (e.g. in a distributed, cluster or cloud-based computing configuration) and appropriate software units may be arranged to manage and/or process data on behalf of remote devices.

The memory components may include system memory (515), which may include read only memory (ROM) and random access memory (RAM). A basic input/output system (BIOS) may be stored in ROM. System software may be stored in the system memory (515) including operating system software. The memory components may also include secondary memory (520). The secondary memory (520) may include a fixed disk (521 ), such as a hard disk drive, and, optionally, one or more storage interfaces (522) for interfacing with storage components (523), such as removable storage components (e.g. magnetic tape, optical disk, flash memory drive, external hard drive, removable memory chip, etc.), network attached storage components (e.g. NAS drives), remote storage components (e.g. cloud-based storage) or the like.

The computing device (500) may include an external communications interface (530) for operation of the computing device (500) in a networked environment enabling transfer of data between multiple computing devices (500) and/or the Internet. Data transferred via the external communications interface (530) may be in the form of signals, which may be electronic, electromagnetic, optical, radio, or other types of signal. The external communications interface (530) may enable communication of data between the computing device (500) and other computing devices including servers and external storage facilities. Web services may be accessible by and/or from the computing device (500) via the communications interface (530). The external communications interface (530) may be configured for connection to wireless communication channels (e.g., a cellular telephone network, wireless local area network (e.g. using Wi-Fi™), satellite-phone network, Satellite Internet Network, etc.) and may include an associated wireless transfer element, such as an antenna and associated circuity.

The computer-readable media in the form of the various memory components may provide storage of computer-executable instructions, data structures, program modules, software units and other data. A computer program product may be provided by a computer-readable medium having stored computer-readable program code executable by the central processor (510). A computer program product may be provided by a non-transient computer-readable medium, or may be provided via a signal or other transient means via the communications interface (530).

Interconnection via the communication infrastructure (505) allows the one or more processors (510) to communicate with each subsystem or component and to control the execution of instructions from the memory components, as well as the exchange of information between subsystems or components. Peripherals (such as printers, scanners, cameras, or the like) and input/output (I/O) devices (such as a mouse, touchpad, keyboard, microphone, touch-sensitive display, input buttons, speakers and the like) may couple to or be integrally formed with the computing device (500) either directly or via an I/O controller (535). One or more displays (545) (which may be touch-sensitive displays) may be coupled to or integrally formed with the computing device (500) via a display (545) or video adapter (540).

The foregoing description has been presented for the purpose of illustration; it is not intended to be exhaustive or to limit the invention to the precise forms disclosed. Persons skilled in the relevant art can appreciate that many modifications and variations are possible in light of the above disclosure.

Any of the steps, operations, components or processes described herein may be performed or implemented with one or more hardware or software units, alone or in combination with other devices. In one embodiment, a software unit is implemented with a computer program product comprising a non-transient computer-readable medium containing computer program code, which can be executed by a processor for performing any or all of the steps, operations, or processes described. Software units or functions described in this application may be implemented as computer program code using any suitable computer language such as, for example, Java™, C++, Perl™, or Python™ using, for example, conventional or object-oriented techniques. The computer program code may be stored as a series of instructions, or commands on a non-transitory computer-readable medium, such as a random access memory (RAM), a read-only memory (ROM), a magnetic medium such as a hard-drive, or an optical medium such as a CD-ROM. Any such computer-readable medium may also reside on or within a single computational apparatus, and may be present on or within different computational apparatuses within a system or network.

Flowchart illustrations and block diagrams of methods, systems, and computer program products according to embodiments are used herein. Each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, may provide functions which may be implemented by computer readable program instructions. In some alternative implementations, the functions identified by the blocks may take place in a different order to that shown in the flowchart illustrations.

Some portions of this description describe the embodiments of the invention in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent electrical circuits, microcode, or the like. The described operations may be embodied in software, firmware, hardware, or any combinations thereof.

The language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based hereon. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

Finally, throughout the specification and claims unless the contents requires otherwise the word 'comprise' or variations such as 'comprises' or 'comprising' will be understood to imply the inclusion of a stated integer or group of integers but not the exclusion of any other integer or group of integers.