1001

Automation a57. Automation and Robotics in Miningand Mineral Processing

Sirkka-Liisa Jämsä-Jounela, Greg Baiden

Mines and mineral processing plants need in-tegrated process control systems capable ofimproving plant-wide efficiency and produc-tivity. Mining automation systems today typicallycontrol fixed plant equipment such as pumps,fans, and phone systems. Much work is under-way around the world in attempting to create themoveable equivalent of the manufacturing as-sembly line for mining. This technology has thegoals of speeding production, improving safety,and reducing costs. Process automation systemsin mineral processing plants provide importantplant operational information such as metal-lurgical accounting, mass balances, productionmanagement, process control, and optimization.This chapter discusses robotics and automation formining and process control in mineral processing.Teleoperation of mining equipment and control

57.1 Background ......................................... 1001

57.2 Mining Methodsand Application Examples ..................... 1004

57.3 Processing Methodsand Application Examples ..................... 100557.3.1 Grinding Control ........................ 100557.3.2 Flotation ................................... 1007

57.4 Emerging Trends .................................. 100957.4.1 Teleremote Equipment................ 100957.4.2 Evaluation of Teleoperated Mining101157.4.3 Future Trends in Grinding

and Flotation Control.................. 1011

References .................................................. 1012

strategies for grinding and flotation serve asexamples of current development of field.

57.1 Background

Mining is the act of extracting mineral determined tobe ore from the earth to be processed in a mineral pro-cessing operation. All mining operations have a leastsome limited mineral processing available on site. Usu-ally the sophistication of the complex is determined byunit process operations needed to make the product,or distribution and transportation costs (Fig. 57.1). Themineral extraction process can occur using many po-tential mining methods. Some of the methods includeopen pit, caving, bulk stoping, and/or selective miningtechniques such as cut and fill, as well as room andpillar [57.1]. Each method and suite of mining equip-ment has the aim of extracting the mineral at a profit forprocessing.

The aim of a mineral processing operation is to con-centrate a raw ore for the subsequent metal extractionstage. Usually, the valuable minerals are first liberated

from the ore matrix by comminution and size separationprocesses (crushing, grinding, and size classification),and then separated from the gangue using processescapable of selecting the particles according to theirphysical or chemical properties, such as surface hy-drophobicity, specific gravity, magnetic susceptibility,and color (flotation, magnetic or gravimetric separation,sorting, etc.) [57.2].

Process automation has always played a key rolein the mineral process industries and is gaining mo-mentum in mining extraction operations as mobilerobotics techniques are being applied. The use of ad-vanced technologies, including modeling, simulation,advanced control strategies, smart equipment, field-buses, wireless networks, remote maintenance, etc., iswidespread in many sectors (Fig. 57.2). Information-based technologies are responsible for making mineral

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1002 Part F Industrial Automation

Gyratorycrusher Sag mill

Electrowinning

Concentratethickener

Anode

Anode casting wheel

CyclonesRougherflotation cells

Extraction

Flotation and thickeners

Smelter

Extraction and leaching

Stock pile

Ball mill

Oxide ore

Strip tankPregnantsolution tank

Filter press

Thickener

Solvent extraction and leach tanks

Scavenger/cleanerflotation cells

Refining

Smelting

Crushing and grinding

Modular control (A-B SLC, PLC-5¤, ControlLogix“)

Device network (DeviceNet“)

Process and SCADA software

Push buttons and signalling (A-B RediSTATION“, RediPANEL“)

Graphic terminals/industrial computer products (A-B PanelView“, PanelBuilder“, RAC 6000 Series)

Low-voltage motor management (A-B MCS“, SMM, SMC, SMP, contactors, overload protection)

Power quality and automation (A-B Powermonitor II, Line synchronization module“)

AC and DC industrial motors (A-B 1329R, 1329L; Reliance E-master¤, RPM“, RPM“III, IQ Intelligent“, XE“)

Gearings (DODGE TORQUE-ARM“, MAXUM“, CST“)

Bearings (DODGE EZLINK¤, UNIFIED“, SAF-XT, STAR“, HFH, IMPERIAL“, S-2000)

Variable speed AC and DC drives (A-B 1336 PLUS, 1336 PLUS II, 1336 IMPACT“, SP500; Reliance electric GV3000/SE“, FlexPak¤ 3000)

Conveyor components (DODGE PARA-FLEX“, GRID-LIGN“, FLEXIDYNE“, Mine Duty Xtra“, engineered pulleys)

Drive systems (Rockwell automation)

Motor control centers (A-B CENTERLINE¤)

Medium voltage control (A-B PowerMAX AC drives, starters, SMC)

Process systems (A-B ProcessLogix“, Rockwell software ProcessPak“ : RSView32“, RSLogix Frameworks“, RSTune“)

Fig. 57.1 Mineral processing automation (courtesy of Rockwell Automation, Inc)

processing more efficient and reliable, and help the in-dustry to adapt to new competitive environments ina safe and environmentally sound manner. One criticalstep in achieving these objectives is to develop and ap-ply improved control systems across the full range ofapplications from mining to processing and utilization.

While mineral processing has had extensive use ofmany advanced technologies, standard mining applica-tions such as pumping, dewatering, hoist control, andpower distribution remain the norm with some individ-ual exceptions in ventilation systems and other minewide systems. Overall, the complication and scale ofmining operations has delayed the wide adoption ofadvanced technology. Several stand alone technologieshave seen successful implementation in mining and pi-lot projects; full scale mine implementation have beenattempted with extremely encouraging results. The In-telligent Mine Program in Scandinavia and the MiningAutomation Program [57.3] in Canada were two mainprojects attempted in the 1990s and early 2000s. Themain technology drivers were seen to be: telecommuni-cations, positioning and navigation, integrated softwaresystems, and mobile robotic equipment. The Intelli-gent Mine Program explored the issues from a rockand process characteristic point of view and the Min-ing Automation Program from an equipment point ofview.

The optimization of the economics of the pro-cess operations is the key driver for the applicationof advanced control. Many successful control strat-egy implementations in mineral processing have been

reported. The power of model-based control for indus-trial semi-autogenous grinding circuits was discussedby Herbst and Pate [57.4]. In the application, they usedan expert system and online process models to find theoptimum feed rate. A Kalman filter was used to esti-mate unmeasured variables such as mill filling and orehardness that were required by the expert system. An8% improvement in feed rate over manual control wasachieved with the control system. In the multivariablecontrol application on a two-stage milling circuit at theEast Driefontein Gold Mine in South Africa, the aver-age throughput t/h was increased from 73.1 to 79.2,and the average grain size % < 75 μm from 76.5 to78.5. The standard deviation of the grain size valueswas reported to decrease from 3 to the 0.9 [57.5]. Suc-cessful economic results and benefits from 13 years ofcomputer control in flotation have been reported by Mi-ettunen [57.6].

The economics of the application of intelligentrobotics for mining was seen as having substantial ben-efits. These were discussed in Baiden [57.7]. This reportshowed that the fundamental definition of ore would bealtered by the projected results of cost reduction andmining rate improvements. Further, robotic operationwould improve the safety of miners as it would dropexposure levels. Subsequently, the Intelligent Mine Pro-gram and Mining Automation Program showed throughfield feasibility experimentation that these projectionswere realistic. Several projects around the world noware investigating the opportunity for robotic and teleop-erated equipment in particular applications.

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Automation and Robotics in Mining and Mineral Processing 57.1 Background 1003

Operator workstation

Reliance electric IQ intelligent“ motorwith PreAlert“technology

A-B DeviceLink“ adapter with limit switch

A-B RediStationpushbutton

A-B ControlLogix“ system

DODGE EZLINK¤

bearing A-B DTAM“ message display

A-B Photoelectricsensor 9000

A-B PLC-5/80“controller

Reliance electric E-master¤

AC motor

A-B 1329 AC motorA-B 1329

AC motor

Reliance electric medium voltage AC motor

A-B CENTERLINE¤

motor control center

A-B Bulletin 1557/1557MSCI medium voltage drive

A-B Powermonitor II

A-B Datalinermessage display

A-B 1336 IMPACT“ drive

A-B SMC DialogPlus“controller

A-B ControlNet“, Ethernet, TCP/IP, A-B DH+“ networks

A-B 1336 Plus IIdrive

A-B PanelView“ 550operator terminal

DeviceNet

Planthistorian

Supervisory process control(Rockwell software RSView32 and RSLogix Frameworks“ software)

Operator workstations with Rockwell softwareRSView32“active display

Operator workstations with Rockwell softwareRSView32active display

Bridge ormodem

Reliance electric FlexPak¤

3000 drive

Reliance electric RPM“ IIIDC motor

Reliance electricRPM“ AC motor

A-B RediPANEL“terminal

DODGE EZLINKbearing

DODGE TORQUE-ARM“ reducer

A-B FLEX I/O“ module

Field device I/O

Remote site 1

A-B SLC controllerRemote I/O

A-B PanelView“operator workstation

A-B SMM“ protection relay

A-B MV dialogPlus“ controllerthrough 8 000 HP

A-B Medium voltagedrive through10 000 HP

DeviceNet

A-B Contactor with SMP-3“ solid-state overload relay

A-B FLEX Ex“ module

Ethernet¤, TCP/IP networks

Reliance electric GV3000/SE“ drive

Reliance electric E-master AC motor

Reliance electric E-master AC motor

Fig. 57.2 Mining automation architecture (courtesy of Rockwell automation)

However, the control of mineral processes is facedwith many challenges. At the present time it is not pos-sible to measure, on a real-time basis, the importantphysical or chemical properties of the material pro-cesses. This is particularly true for the fresh ore feedcharacteristics (mineral grain size distribution, mineralcomposition, mineral association, grindability) and theground material properties (liberation degree, particlecomposition distribution, particle hydrophobicity). Anessential feature of control and optimization strategies isthe availability of mathematical models that accurately

describe the characteristics of the process. Satisfactorymathematical models are not, however, available formineral processing unit processes due to the fact that thephysics and chemistry of the sub-processes involved arepoorly understood. Models for process analysis and op-timization for comminution circuits are usually basedon population balance models and the use of break-age and selection functions. Numerous empirical andphenomenological models based on various assump-tions for flotation have been proposed in the literature.Among the many flotation models, the classical first-

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1004 Part F Industrial Automation

order kinetic model is widely used and can be utilizedto optimize the design of the flotation circuit and itscontrol strategy. Recently progress has been made in

grinding circuit modeling using the discrete elementmethod (DEM) [57.8–12], and efforts have been madein the CFD modeling of flotation [57.13].

57.2 Mining Methods and Application Examples

Mining in general has had little process control ca-pability as mechanization of equipment was the onlyreal opportunity that existed. For example, the absenceof communication systems limited the types of pro-cess control that could be applied. In the last twodecades work has been underway to change this. Theportable size of computers and the availability of net-works to connect them to spawned growth in theapplication of process control to mining. The basicsof main distribution systems such as water and powerare now the norm. Networks have further enabled theinstallation of rock mechanics systems such as micro-seismic systems. While these systems are importantthey do not get to the actual main production technolo-gies because the machine systems for production aremobile.

Both the Intelligent Mine Program and the Min-ing Automation Program worked to change this and theconcepts behind telemining started to gain momentumin the mid to late 1990s. Telemining (mobile processcontrol for mining) is the application of remote sensing,remote control, and the limited automation of miningequipment and systems to mine mineral ores at a profit.The main technical elements are (Fig. 57.3):

• Advanced underground mobile computer networks• Positioning and navigation systems• Mining process monitoring and control softwaresystems• Mining methods designed specifically for telemi-ning• Advanced mining equipment.

Telemining has the capability to reduce cycle times, im-prove quality and increase the efficiency of equipmentand personnel, resulting in increased revenue and lowercosts.

Advanced high capacity mobile computer networksform the foundation of teleremote mining (Fig. 57.4).The mine may be connected via the telecommunica-tion system so mines can be run from operation centersunderground or on the surface. Several opportunities ex-ist for communication, depending on the environment.

Surface mines have trended towards network systemssuch as the 802.11 standard [57.14]. Whereas under-ground mines have focused on much higher bandwidthsystems consisting of a high capacity backbone linkedto 2.4 GHz capacity radio cells for communication. Thehigh capacity allows the operation of not only datasystems but mobile telephones, handheld computers,mobile computers on board machines, and multiplevideo channels to run multiple pieces of mining equip-ment from surface operation centers [57.15, 16].

To apply mobile robotics to mining, accurate posi-tioning systems are an absolute necessity. Positioningsystems that have sufficient accuracy to locate the mo-bile equipment in real-time at the tolerances necessaryfor mining have been developed [57.17, 18]. Practicaluses of such systems include machine set-up, hole loca-tion, and remote topographic mapping. Surface systemsuse GPS for location and several of these systems havebeen developed. In underground mines, some of themost advanced positioning equipment consists of laserreference positioning, ring-laser-gyro (RLG), and ac-celerometers. Units are mounted on all types of drillingmachines so that operators can position the equipment.These types of systems are just beginning to make theirpresence known over conventional surveying; severalmanufacturers offer this new product [57.19]. RLG sys-tems track the location of mobile machinery in the

Miningmethods

Process engineering,monitoring and control

Positioning andnavigation systems

Undergroundtelecommunication system

Min

ing

equi

pmen

t

Mining process system

s

Fig. 57.3 Conceptual representation of the key technolog-ical components (after [57.1])

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Automation and Robotics in Mining and Mineral Processing 57.3 Processing Methods and Application Examples 1005

DAT

DAT

DAT

PLC

Headend

Fig. 57.4 Example of a high capacity cellular network (af-ter [57.1])

mine. Accurate positioning systems mounted on mo-bile equipment will enable the application of advanced

manufacturing robotics to mining. Usually in advancedmanufacturing, robotic equipment is fixed to the floor,allowing very accurate surveying and positioning ofthe equipment. The positioning systems being used formining equipment allow accurate positioning of sur-face equipment using GPS, and inference techniquesallow high accuracy positioning of mobile undergroundequipment.

Mine planning, simulation, and process control sys-tems are growing using the foundations of telecommu-nications, positioning, and navigation. Linking geologyand engineering directly to operations is important forthe successful application of these systems. Several sys-tems such as Datamine, Gemcom, Mine 24D, to namea few, are in use around the world today. Further, pro-cess control systems for the day-to-day operation ofpumping, dewatering, and power distribution are thenorm. New systems for ventilation control are startingto emerge as the cost of the overall system infrastructureis reduced.

57.3 Processing Methods and Application Examples

The overall objective of a grinding and flotation unit isto prepare a concentrate, which may be as simple asthe net revenue of the plant. In practice, however, thelinks between the grinding and flotation circuits tun-ing and the economic objective are not obvious, andthe objectives are always broken down into particlesize reduction, mineral liberation, and mineral separa-tion objectives. In the following, grinding and flotationareas are briefly discussed as application areas whereautomation has played an important role in mineral pro-cessing. These application areas serve as examples ofcurrent developments in the field of automation in min-eral processing.

57.3.1 Grinding Control

Grinding ore to the optimum size for mineral extrac-tion by flotation or leaching is an essential but highenergy intensive part of most mineral processing opera-tions. The benefits from improved grinding control aresubstantial, primarily in the areas of improved millingefficiency, more stable operation, higher throughput,and improved downstream processing. Grinding an orefiner than is necessary leads to increased energy costs,reduced throughput, increased mill liner consumption,and increased consumption of grinding media and

reagents. Insufficient ore grinding, on the other hand,reduces the recovery rate of the valuable mineral.

InstrumentationFor grinding instrumentation both basic measurementand advanced indirect instruments are available. Themost common measurements are: mass flow rate ona conveyor belt, volume flow rate, pipeline pressure,pulp density, sump level, mill motor power consump-tion, and mill rotation speed. Online particle sizemeasurement is also a part of the well-instrumentedgrinding circuit. Indirect instruments are mostly usedin mill or hydrocyclone operation monitoring. Thesemeasurements are based, for example, on acoustic mea-surements, vision-based monitoring, mill liner sensors,and mill power frequency analysis.

Mass flow rate measurement on a conveyor belt ismainly performed by nuclear weight gauges. In pipelineflow measurements magnetic instruments are the mosttypical. Pulp densities can be measured by a nucleardensity meter, soft sensors, or alternatively by certainparticle size analyzers.

Online particle size analysis can be performed us-ing several techniques. The three most typical onlineparticle size analysis methods in mineral processes aremechanical, ultrasonic, and laser diffraction-based de-

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1006 Part F Industrial Automation

vices. Outokumpu Technology’s PSI-200 has been oneof the most popular mechanical devices since the 1970s.The measurement is based on a reciprocating caliperwith high precision position measurement. The mea-surement technique limits accurate size measurement tothe coarser end of the distribution. The ultrasonic-basedmeasurements were also developed in the 1970s, for ex-ample the Svedala Multipoint PSM-400. However, themethod requires frequent calibration and is susceptibleto air bubbles. The laser diffraction method representsthe latest technology in online particle size analysis.The PSI-500 particle size analyzer, manufactured byOutokumpu, uses laser diffraction-based measurement,with automatic sample preparation. The system enablesthe development of new advanced control employingthe full scale of the particle size distribution [57.20].

Some vision-based measurements have recentlybeen developed. Mintek has a product CYCAM forhydrocyclone underflow monitoring. The equipmentmeasures the angle of the discharge and thereforethe conditions; for example, roping can be detected.For particle size on-belt monitoring of the grind-ing and crushing circuit Metso has a product calledVisioRock.

Various methods are used for mill charge measure-ment. These include acoustic measurements [57.9], mill

A

Hydro-cyclon

Cone

BallRod

D

D

FF

P

PI

LI

PT

FIFI

F

F

FFI

F

JT

F

FI

J

F

AT Analysis (particle size)DT DensityFT FlowJT PowerLT LevelPT Pressure T

Fig. 57.5 Typical flowsheet of a grinding circuit (after [57.21])

liner sensors and mill power frequency analysis [57.22–24]. The methods are mostly applied to specific pro-cesses, and there have been no significant commercialproduct breakthroughs.

To summarize, an example of a grinding circuit withtypical instrumentation is given in Fig. 57.5.

Control StrategiesControl of the wet mineral grinding circuits might havedifferent objectives depending on the application. Themost common control objectives are:

• The particle size distribution of the circuit productis to be maintained constant at constant feed rate.• The particle size distribution of the circuit productis to be maintained constant at maximum feed rate.• Both the particle size distribution and solid contentscircuit product are to remain constant.

The control strategy for the grinding circuit is basedon a hierarchical structure. Basic controls mainly con-sist of traditional PI controllers and ratio controllers.The mill water feed typically has a ratio control withthe ore feed. In many cases, sump levels are controlledby changing the pump speed. Furthermore, the pumpspeed is used to control the hydrocyclone feed pressure.

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Automation and Robotics in Mining and Mineral Processing 57.3 Processing Methods and Application Examples 1007

The cyclone feed density is stabilized by manipulat-ing an additional water feed rate to the sump. Particlesize measurement is also currently applied in grindingcircuit control. The product particle size measurementcan, for example, be used to manipulate the ore feedrate to the primary mill. In addition, higher level opti-mization methods are typically applied to maximize thethroughput with desired constraints.

57.3.2 Flotation

In flotation the aim of the control strategy is adjust-ment of the operating conditions as a function of theraw ore properties and feed rate, metal market prices,energy, and reagent costs [57.25]. Usually these objec-tives require a certain amount of trade-off between theconcentrate and tonnage, the impurity contents and theoperating costs.

InstrumentationIn flotation, instrumentation is available for measuringflow rates, density, cell levels, airflow rate, reagent feedrates, pH, and conductivity. Slurry flow measurement ismainly performed by a magnetic flow meter, and densityby a nuclear density meter. The most typical instrumentsused for measuring the slurry level in a cell are a floatwith a target plate and ultrasonic level transmitter,a float with angle arms and capacitive angle trans-mitter, and reflex radar. The instrument for measuringflotation airflow rate contains a thermal gas mass flowsensor or a differential pressure transmitter with a ven-ture tube, pitot tube, or Annubar element. A wide rangeof different instrumentation solutions for reagent dos-ing exist. The best choice is to use inductive flow metersand control valves. Electrochemical measurements giveimportant information about the surface chemistry ofvaluable and gangue minerals in the process. pH isthe most commonly measured electrochemical poten-tial, and sometimes pH measurement can be replaced byconductivity measurement, which gives approximatelythe same information as pH measurement. Recently,other electrochemical potential measurements have alsobeen under study. The use of minerals as working elec-trodes makes it possible to detect the oxidation state ofdifferent minerals and to control their floatability. Sta-bility of the electrodes, however, has been a problem inonline use, but some good results have been reported.

X-ray fluorescence is the universal method foronline solid composition measurement in flotation.Equipment vendors now offer, however, more efficient,

compact, flexible and reliable devices than were avail-able in the 1970s.

To summarize, an example of a flotation circuitwith typical basic instrumentation is given in Fig. 57.6.Conductivity and pH are measured in the conditioner.On-stream analyses are taken from the feed, tailings andconcentrate, and also from several flows between theflotation sections. Flow rates, levels, and airflow ratesare measured at several points. Most of the reagents areadded in the grinding circuit, except for frother, which isadded in the conditioner and additional sodium cyanidein the cleaner.

Recent developments in instrumentation have pro-vided new instruments, such as image analysis-baseddevices for froth characteristics measurement. Threedifferent image analysis products have been reportedto be available commercially: FrothMaster from Out-okumpu, JKFrothCam from JKTech, and VisioFrothfrom Metso Minerals. Research has been carried out ondeveloping image processing algorithms and on analyz-ing the correlations between image analysis and processvariables, more recently also on flotation control basedon image analysis.

A comprehensive description of the flotationplant instrumentation has been reported by Laurilaet al. [57.26].

Flotation ControlFlotation control designed according to the classicalcontrol hierarchy of base level controls, stabilizing con-trol, and optimizing control has been widely acceptedas a mature technology since 1970. Basic controlsconsist of traditional PI controllers for cell levelsand airflow rates. A feedforward ratio controller isused for reagent flow rates. For cell levels in seriesa combination of feedforward and multivariable con-trol strategy has been also widely applied in industrialuse [57.27].

Developing flotation control strategies is still an ac-tive research topic since the benefits to be gained interms of improved metallurgical performance are sub-stantial. However, flotation control is becoming moreand more difficult due to the emergence of low gradeand complex ores. Machine vision technology providesa novel solution to several of the problems encounteredin conventional flotation control systems, like the effectsof various disturbances appearing in the froth phase.Structural characteristics such as bubble diameter andfroth mobility give valuable information for followingthe trend in metal grade and recovery.

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1008 Part F Industrial Automation

Frother

Water

Ore

NAX

NaCN

NaCN

Ca(OH)2

Grinding

Conditioning

Roughing

Rougher concentrate Rougher tailings

Cleanertailings

Concentrate

Cleaning

Air

A

L

LF

L

F

A

L

A

FpH

C

Air

Scavenging

Scavenger concentrate Cu-tailing

L

A F

F

F

A

FA

Air

F FlowL Pulp levelA Online analysis (Cu, Zn, Fe)C Conductivity

ZnSO4

Fig. 57.6 Typical flowsheet of a flotation process (Cu circuit of Pyhäsalmi concentrator) (after [57.28])

In the FrothMaster-based control in the rougherflotation at Cadia Hills Gold Mine in New South Wales,Australia, three FrothMaster units measure froth speed,bubble size, and froth stability. The control strategycontains stabilizing and optimizing options. Stabiliz-ing control strategy is logic based and manipulates thelevel, frother addition rate, and aeration rate to con-trol the froth speed. Optimizing the control of the gradechanges the setpoint values of the froth speed [57.29].Many industrial implementations of the JKFrothCamsystem have been reported as well. The control sys-tem consists of PID controllers and/or an expert system.Measurements of bubble size, froth structure, and frothvelocity are taken and reagent dosages, cell level, andaeration rates are used as manipulated variables [57.30].VisioFroth is one module in the Metso Minerals CISAoptimizing control system, by which froth velocity, bub-ble size distribution, and froth color can be measured.The largest VisioFroth installations are at Freeport, In-donesia, with 172 cameras and Minera escondida PhaseIV, Chile, with 102 cameras. A combination of on-

stream analysis and image analysis technology seems tobe the most efficient way to control flotation today. Bet-ter concentrate grade consistency, and thus improvedplant recovery, have been reported using this combina-tion [57.31].

Flotation, being a time variant and nonlinear processthat usually also undergoes large unknown disturbancesis, however, difficult to manage optimally by classi-cal linear control theory applications. Operator supportsystems are needed to overcome these problematic sit-uations. The latest applications of the operator supportsystems are concentrating on solving the issue of feedtype classification. At many mines, changes in the min-eralogy of the concentrator feed cause problems inprocess control. After a change in the feed type a newprocess control method has to be found. This is usuallydone by experimentation because the new type is oftenunknown. These experiments take time and the resultingtreatment method might not be optimal. The monitoringsystem developed by Jämsä-Jounela et al. [57.28] usesSOM for online identification of the feed ore type and

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Automation and Robotics in Mining and Mineral Processing 57.4 Emerging Trends 1009

a knowledge database that contains information abouthow to handle a specific ore type. A self-learning al-gorithm scans historical data in order to suggest the

best control strategy. The key for successful implemen-tations is the right selection of variables for the ore typedetermination.

57.4 Emerging Trends

Modern automation systems in plants that have to pro-cess ever more complex ore are faced with the challengeof incorporating the increasing capabilities of moderntechnology in order to be able to succeed in a verycompetitive and global market, in which product vari-ety and complexity, as well as quality requirements, areincreasing, and environmental issues are playing evermore important key roles.

Mines and processing plants need integrated processcontrol systems that can improve plant-wide efficiencyand productivity. Advances in information technologyhave provided the capabilities for sharing informationacross the globe and, as such, process automation andcontrol have become more directly responsible for as-sisting in the financial decision making of companies.The future aim of the system approach is to cover the

Fig. 57.7 RLG and test-bed (after [57.32])

complete value-added chain from the mine to the endproduct, and to utilize the latest hardware and softwaretechnology advances in their systems (Fig. 57.12).

Emerging trends in mining will likely take the formof moving towards advanced manufacturing techniques.Telecommunications systems on the surface and un-derground have opened the door to a completely newthinking in mining. The three biggest trends will beadvances in positioning systems, telerobotic control ofmachinery, and the techniques that these systems willenable.

57.4.1 Teleremote Equipment

Work continues in the research field in building theequivalent to global positioning systems for under-ground. This technology development was recentlyreported at Massmin 2008 in Lulea, Sweden [57.33].This new development combined with gyro technologywill alter current practices in ways not yet compre-hended. If this technology is combined with a RLG anda laser scanners mounted on a mobile machine such asshown in Fig. 57.7; the machines can have knowledgeof positioning in real time on board the machine. Tasks

Fig. 57.8 Software generated drift from test-bed machine data (af-ter [57.32])

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1010 Part F Industrial Automation

Fig. 57.9 Teleremote operation chair (after [57.32])

such as mapping, drill setup, and machine guidancesystems will become simple to implement. Figure 57.7shows a RLG and a concept of a machine for surveying.Figure 57.8 shows the actual mapping data collected bythis surveying machine. At present, this unit is capableof surveying a 1 km drift (tunnel) in a few hours as op-posed to several days using current work practices. Theaddition of an equivalent to GPS for underground willimprove this technology and many more.

Another important trend is enabled by advances be-ing made in communications capacity. The operation ofteleremote equipment is possible for all processes andequipment. An operator station as shown in Fig. 57.9is connected to the machine via the telecommunica-tions system. This allows the operator to run severalmachines simultaneously, and together with position-ing and navigation systems will allow the operator toinstantaneously move from machine to machine acrossmultiple mine environments. Several mines around theworld are attempting this technology in operation. Thelist includes Inco, LKAB, Rio Tinto, and Codelco.

Creighton

Stobie

175 Test mine

Fig. 57.10 Mines operation center

As the technology becomes more widespread, itwill allow mining companies to consider the installa-tion of mine operation centers such as the one shown inFig. 57.10. Prototypes have been designed and installedaround the world. The figure shows a mine operationcenter (MOC) that connects Stobie Mine, CreightonMine, and the Research Mine at Inco. As seen in thispicture, all are connected to the MOC. Three TamrockDatasolo drills and five LHDs of various types are work-ing or have worked from the MOC since its inception.

BenefitsSignificant benefits of this teleremote style of opera-tion lie in safety, productivity, and value-added time.Operators spend less time underground thus reducingexposure to underground hazards, and productivity isimproved from the current one person per machine toone person per three machines. Initial tests indicate that23 continuous LHD hours of operation in a 24 h periodis possible, which is significantly better than the current15 h. Clearly capital requirements in the latter situationare reduced.

0 365 730 1095 1460

a) Conventional blasthole miningTons/day

Drifts accessibleOre TPD (×100)Rock TPD (×100)

0 365 730 1095 1460

b) Teleoperated blasthole miningTons/day

Drifts accessibleOre TPD (×100)Rock TPD (×100)

Fig. 57.11a,b Conventional (a) and teleremote mine (b) lifecomparisons (after [57.1])

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Automation and Robotics in Mining and Mineral Processing 57.4 Emerging Trends 1011

Hammermill crusher

Limestoneor clay

Rawmaterialstorage

Raw mill

Blendingsilo

Gypsum

Central control room

Clinker

High efficiencyclassifier

Dust collectorand fan

Calcinercoal pump

Kiln burnercoal pump

CoalCoal mill

Pulverizedcoal bin

Cementpump

Cement mill(Typ. of 12)

Bulk cementdispatch

Bagged cement dispatch

Cement silos(Typ. 13)

Clinkercooler

Rotary kiln

To rawmill

Cooler dust collector

Vent fan

Alkali bypassprecipitator

Precipitator4-stagepreheater

Separatateline calciner

Packing house

PLC, SLC, MicroLogixand ControlLogix Controllers

RSView32, RSTools, RSComponentsSoftware

PanelView Terminals (PV900, PV550)

Motor protection (SMC, SMP, SMM)

Motion control

Allen-Bradley drives, reliance electric drives and rockwellautomation drive systems

Sensors (Photoswitch)

Reliance electric motors

Industrial control (push buttons,pilot lights, contactors, starters,terminal blocks, switches, relays)

Medium voltage control (starters,SMC controllers, medium voltage drives)

Networks (Ethernet, ControlNet,DeviceNet, Remote I/O, DataHighway Plus)

SCADA

Power transmission

DODGE Belts, sheaves, couplings,gear boxes, mounted bearings

BurnerMaster and CombustionMastersystems

CENTERLINE Motor control centers

Fig. 57.12 Automation of cement processing by coordinating needed software and hardware (courtesy of Rockwell Automation,Inc)

The effectiveness of teleremote mining may beanalyzed in the short term using computer-based sim-ulation systems, which are powerful quantification andvisualization tools of technology and operations. Thefollowing example shows the impact of the teleoper-ated mining technology on throughput, mine life, betterresource utilization, and increased value generation forthe organization.

57.4.2 Evaluation of Teleoperated Mining

A simulation model was used to evaluate the impactof teleremote operations on mine life and provide out-puts required to make planning decisions. Teleremoteoperations have been shown in an operating mine tobe capable of 7 to 7.5 h of operation per 8 h shift ascompared to 5 h in a conventional mine. Other signif-icant differences between conventional and teleroboticmining are increased flexibility and safety.

The comparative graphs shown in Fig. 57.11 showsignificant potential results from the application ofrobotics and automation. Mine life is reduced by 38%using teleremote mining versus conventional miningbecause of the higher mining rate from improvedthroughput and face utilization. Moreover, utilization of

LHD equipment is increased by 80% in teleremote min-ing compared to conventional settings. With a total oftwo LHDs, high rates of production were achieved.

57.4.3 Future Trends in Grindingand Flotation Control

The optimization methods for grinding control are ex-pected to be developed due to better particle distributionmeasurement systems, advanced mill condition mea-surements (e.g. frequency analysis), and the use ofefficient grinding simulations based, for instance, onthe discrete element method. Flotation is facing a newera in terms of process control and automation. Flota-tion cells have increased in size dramatically over thepast years; flotation circuit design of multiple recyclestreams will be replaced by simpler circuits, subse-quently leading to a decreasing number of instrumentswith higher demands on reliability and accuracy. Thiswill set new challenges for the control system designand implementation of these new plants. Process datadriven monitoring methods, model predictive control(MPC), and fault tolerant control (FTC) will be amongthe most favorable methods to be applied together withthe recently developed new measurement instruments.

PartF

57.4

1012 Part F Industrial Automation

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