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Industrial Communication Protocols 56.7 Emerging Trends 995

access. The requirements made for this line have to

be fulﬁlled by the service level agreements from the

chosen provider. Within the public network it is not

possible to inﬂuence the quality of service. The data

package leaves the public network when the VAN

switching endpoint access from the faced communi-

cation partner is achieved. The connection from the

public network to the faced VAN -AP is also pro-

vided by the same or an alternative provider and

guarantees deﬁned requirements.The data exchange

between two communication partners is indepen-

dent of each other.

•

Use case 2: For a connection-oriented data trans-

mission (or data packages with high-level priority)

the use of manageable data transport technology is

needed. The VA N switching line represents a man-

ageable connection. A direct known connection

between two VAN-APs has to be established and

a VAN switching endpoint access is not needed.

The chosen provider guarantees the deﬁned require-

ments for the complete line. When the current line

loses the promised requirements it is possible to de-

ﬁne the VA N -APs to build up an alternative line and

hold on/disconnect the current line automatically.

56.6 Conclusions

As discussed in the above sections, the area of indus-

trial communication protocols has been experiencing

a tremendous evolution over the last ten years, being

strongly inﬂuenced by advances in the area of informa-

tion technology and hardware/software developments.

Existing industrial communication protocols have im-

pacted very positively both in the operation of industrial

plants, due to enhanced diagnostic capabilities, which

has improved maintenance operations, as well as in the

development of complex automation systems.

The chapter has reviewed the main concepts of

industrial communication networks and presented the

most prominent wired and wireless protocols that are

already incorporated in a large number of industrial de-

vices (from thousands to millions).

Within this scope of a multitude of existing proto-

cols and also motivated by the growth of the Internet

and increasing possibilities of the World Wide Web

network, and the increased demand for geographically

distributedautomation functionsvirtual automation net-

works (VA N), a very interesting approach would appear

to be to allow integration via heterogeneous networks.

The section presented the concepts of VAN domains

and interfaces and the challenges on ensuring timely

communication behavior, safety, and security across

multiple VA N domains.

56.7 Emerging Trends

The number of commercially available industrial com-

munication protocols has continued to increase, despite

some trials to converge to a single and uniﬁed pro-

tocol, in particular during the deﬁnition of the IEC

61178 standard; the automation community has started

to accept that no single protocol will be able to meet

all different communication requirements from differ-

ent application areas. This trend will be continued by

the emerging wireless sensor networks as well as the

integration of wireless communication technologies in

all mentioned automation-related communication con-

cepts. Therefore, increasing attention has been given

to concepts and techniques to allow integration among

heterogeneous networks, and within this context vir-

tual automation networks are playing an increasing

role.

With the proliferation of networked devices with

increasing computing capabilities, the trend of de-

centralization in industrial automation systems will

increase in the future (Figs. 56.10 and 56.11). This sit-

uation will lead to an increased interest in autonomic

systems with self-X capabilities, where X stands for

alternatives as conﬁguration, organizing, optimizing,

healing, etc. The idea is to develop automation sys-

tems and devices that are able to manage themselves

given high level objectives. Those systems should have

sufﬁcient degrees of freedom to allow a self-organized

behavior, which will adapt to dynamically changing re-

quirements. Theability todeal with widely varying time

and resources demands while still delivering depend-

able and adaptable services with guaranteed temporal

qualities is a key aspect for future automation systems.

Part F 56.7

996 Part F Industrial Automation

SCADA

Just one

power cable....

UWB

Location

sensing

Ethernet

HSDPA

UMTS

Sensors

Actuators

LBS

Control

parameterization

set-up

Fig. 56.10 The wireless factory (from [56.52])

• Ubisense UWB-realtime

positioning system

• RFID grid for mobile

workshop navigation

• Cricket ultrasonic indoor

location system

Fig. 56.11 Indoor positioning systems in the SmartFactory (from [56.52])

Part F 56.7

Industrial Communication Protocols 56.8 Further Reading 997

56.8 Further Reading

56.8.1 Books

•

J.W.S. Liu: Real-Time Systems (Prentice Hall, Up-

per Saddle River 2000)

•

P.S. Marshall: Industrial Ethernet (ISA, 2004)

•

P. Pedreiras, L. Almeida: Approaches to enforce

real-time behavior in Ethernet. In: The Indus-

trial Communication Technology Handbook, ed. by

R. Zurawski (CRC, Boca Raton 2005)

•

B. Schneider: Secrets and Lies – Digital Security in

a Networked World (Wiley, New York 2000)

•

L.R. Franco, C.E. Pereira: Real-time characteristics

of the foundation Fieldbus protocol. In: Field-

bus Technology: Industrial Network Standards for

Real-Time Distributed Control, ed. by N.P. Ma-

halik (Springer, Berlin Heidelberg 2003), pp. 57–

56.8.2 Various Communication Standards

•

IEC: IEC 61508: Functional safety of elec-

trical/electronic/programmable electronic safety-

related systems (2000)

•

IEC: IEC 61158 Ser., Edition 3: Digital data com-

munication for measurement and control – Fieldbus

for use in industrial control systems (2003)

•

IEC: IEC 61784-1: Digital data communications for

measurement and control – Part 1: Proﬁle sets for

continuous and discrete manufacturing relative to

Fieldbus use in industrial control systems (2003)

•

PROFIBUS Guideline: PROFInet Architecture De-

scription and Speciﬁcation, Version V 2.0 (PNO,

Karlsruhe 2003)

56.8.3 Various web Sites of Fieldbus

Organizations and Wireless Alliances

•

IEEE 802: http://www.ieee802.org (last accessed

April 6, 2009)

•

HART Communication Foundation:

http://hartcomm.org (last accessed April 6, 2009)

•

ODVA: http://www.odva.org (last accessed April 6,

2009)

•

PROFIBUS Nutzer Organisation/PROFIBUS In-

ternational: http://www.proﬁbus.com (last accessed

April 6, 2009)

•

Interbus Club: http://www.interbusclub.com (last

accessed April 6, 2009)

•

Fieldbus Foundation: http://www.ﬁeldbus.org (last

accessed April 6, 2009)

•

MODBUS: http://www.modbus.org/ (last accessed

April 6, 2009)

•

Actor-Sensor-Interface ASi:

http://www.as-interface.net (last accessed April 6,

2009)

•

Ethernet POWERLINK Standardization Group

(EPSG): http://www.ethernet-powerlink.org (last

accessed April 6, 2009)

•

EtherCAT Technology Group:

http://www.ethercat.org (last accessed April 6,

2009)

•

Interessengemeinschaft SERCOS interface e.V.:

http://www.ig.sercos.de (last accessed April 6,

2009)

•

IEEE 802.11TM Wireless Local Area Networks:

http://ieee802.org/11/ (last accessed April 6, 2009)

•

ZigBee Alliance: http://www.zigbee.org (last ac-

cessed April 6, 2009)

•

Bluetooth Special Interest Group:

http://www.bluetooth.org (last accessed April 6,

2009)

•

WISA: Wireless Interface for Sensors and Actua-

tors: http://library.abb.com/global/scot/scot209.nsf/

veritydisplay/4e478bd7490a3f8bc12571f100

427dcb/$File/2CDC171017K0201.PDF (last acces-

sed April 6, 2009)

•

Virtual Automation Networks (VA N):

http://www.van-eu.eu/ (last accessed April 6, 2009)

Part F 56.8

998 Part F Industrial Automation

References

56.1 P. Neumann: Communication in industrial au-

tomation – what is going on?, INCOM 2004, 11th

IFAC Symp. Inf. Control Probl. Manuf., Salvador da

Bahia (2004)

56.2 IEC 61508: Functional safety of electrical/electronic/

programmable electronnic safety-related systems

(2000)

56.3 P. Neumann, A. Pöschmann, E. Flaschka: Virtual

automation networks, heterogeneous networks for

industrial automation, atp Int. Autom. Technol.

Pract. 2, 36–46 (2007)

56.4 Virtual Automation Networks: European Integrated

Project FP6/2004/IST/NMP/2 016696 VAN. Deliverable

D02.2-1: Topology Architecture for the VAN Virtual

Automation Domain (2006)

56.5 HART: http://www.hartcomm2.org/ (last accessed

April 6, 2009)

56.6 R. Becker, B. Müller, A. Schiff, T. Schinke,

H. Walker: A Compilation of Technology, Function-

ality and Application (AS International Association,

Gelnhausen 2002)

56.7 CAN: IEC 11898 Controller Area Networks: http://de.

wikipedia.org/wiki/Controller_Area_Network (last

accessed April 6, 2009), see also http://www.can-

cia.org/canopen

56.8 IO-Link Communication Speciﬁcation, V 1.0;

PROFIBUS International 2.802 (2008)

56.9 IO-Link Integration, Part 1, V. 1.00; PROFIBUS Inter-

national 2.812 (2008)

56.10 PROFIBUS: Technical description,

http://www.proﬁbus.com/pb/ (last accessed April

6, 2009)

56.11 IEC 61158 Ser., Edition 3: Digital data communica-

tion for measurement and control – Fieldbus for

use in industrial control systems (2003)

56.12 IEC 61784-1: Digital data communications for mea-

surement and control – Part 1: Proﬁle sets for

continuous and discrete manufacturing relative to

ﬁeldbus use in industrial control systems (2003)

56.13 ANSI/TIA/EIA-485-A: Electrical characteristics of

generators and receivers for use in balanced digital

multipoint systems (1998)

56.14 ODVA: http://www.odva.org/portals/ (last accessed

April 6, 2009)

56.15 MODBUS TCP/IP: IEC 65C/341/NP: Real-Time Ethernet:

MODBUS-RTPS (2004)

56.16 Ethernet IP: Ethernet/IP speciﬁcation, Release 1.0.,

(ControlNet International and Open DeviceNet Ven-

dor Association, 2001)

56.17 High Speed Ethernet: HSE Speciﬁcation documents

FF-801, 803, 586, 588, 589, 593, 941 (Fieldbus

Foundation, Austin 2001)

56.18 P. Neumann: Communication in industrial au-

tomation. What is going on?, Control Eng. Pract.

15, 1332–1347 (2007)

56.19 PROFIBUS Nutzerorganisation: PROFInet Architec-

ture Description and Speciﬁcation, Version V 2.0.,

PROFIBUS Guideline (2003)

56.20 P-Net on IP: IEC 65C/360/NP: Real-Time Ethernet:

P-NET on IP (2007)

56.21 PROFINET IO: IEC 65C/359/NP: Real-Time Ethernet:

PROFINET IO, Application Layer Service Deﬁni-

tion and Application Layer Protocol Speciﬁcation

(2004)

56.22 P. Neumann, A. Pöschmann: Ethernet-based real-

time communication with PROFINET IO, WSEAS

Trans. Commun.

4(5), 235–245 (2005)

56.23 Time-critical Control Network: IEC 65C/353/NP:

Real-Time Ethernet: Tcnet (2007)

56.24 Vnet/IP: IEC 65C/352/NP: Real-Time Ethernet:

Vnet/IP (2007)

56.25 POWERLINK: IEC 65C/356/NP: Real-Time Ethernet:

POWERLINK (2007)

56.26 ETHERCAT: IEC 65C/355/NP: Real-Time Ethernet:

ETHERCAT (2007)

56.27 W. Manges, P. Fuhr (Eds.): PROFINET IO/Isochronous

Technology, IFAC Summer School Control, Comput-

ing, Communications, Prague (2005)

56.28 J. Jasperneite, K. Shehab, K. Weber: Enhancements

to the time synchronization standard IEEE-1588 for

a system of cascaded bridges, 5th IEEE Int. Work-

shop Fact. Commun. Syst., WFCS2004, Vienna (2004)

pp. 239–244

56.29 EtherNet/IP with time synchronization: IEC 65C/361/

NP: Real-Time Ethernet: EtherNet/IP with time syn-

chronization (2007)

56.30 IEC 61588: Precision clock synchronization protocol

for networked measurement and control systems

(2002)

56.31 SERCOS III: IEC 65C/358/NP: Real-Time Ethernet: SER-

COS III (2007)

56.32 Wireless LAN: IEEE 802.11: IEEE 802.11 Wireless Local

Area Networks Working Group for WLAN Stan-

dards, http://ieee802.org/11/ (last accessed April 6,

2009)

56.33 Personal Area Networks: IEEE 802.15: IEEE 802.15

Working Group for Wireless Personal Area Net-

works, Task Group 1 (TG1), http://www.ieee802.org/

15/pub/TG1.html (last accessed April 6, 2009), and:

Task Group 4 (TG4), http://www.ieee802.org/15/pub/

TG4.html (last accessed April 6, 2009)

56.34 Bluetooth: The Ofﬁcial Bluetooth Membership Site,

https://www.bluetooth.org (last accessed April 6,

2009)

56.35 ZigBee: http://www.zigbee.org/ (last accessed April

6, 2009)

56.36 WISA: http://library.abb.com/GLOBAL/SCOT/SCOT209.

nsf/VerityDisplay/4E478BD7490A3F8BC

12571F100427DCB/$File/2CDC171017K0201.PDF (last ac-

cessed April 6, 2009)

Part F 56

Industrial Communication Protocols References 999

56.37 ABI Research Forecast and Information on Emerg-

ing Wireless Technologies:

http://www.abiresearch.com (last accessed April 6,

2009)

56.38 W. Stallings: IEEE 8O2.11. Wireless LANs from a to n,

IT Professional 6(5), 32–37 (2004)

56.39 IEEE 802.11 Tutorial:

www.eecs.berkeley.edu/˜ergen/docs/ieee.pdf

(last accessed April 6, 2009), see also http://ayman.

elsayed.free.fr/msc-student/wlan.tutorial.pdf

56.40 A. Willig, K. Matheus, A. Wolisz: Wireless technology

in industrial networks, Proc. IEEE 93(6), 1130–1151

(2005)

56.41 P. Neumann: Wireless sensor networks in process

automation, survey and standardisation, atp 3(49),

61–67 (2007), (in German)

56.42 I.F. Akyildiz: Key wireless networking technologies

in the next decade, IFAC Conf. Fieldbus Technol. FeT

2005, Puebla (2005)

56.43 K. Koumpis, L. Hanna, M. Andersson, M. Johansson:

Wireless industrial control and monitoring beyond

cable replacement, PROFIBUS Int. Conf. Coombe

Abbey, Warwickshire (2005), Paper C1

56.44 Industrial wireless technology for the 21st cen-

tury, Industrial Wireless Workshop, San Francisco

(2002)

56.45 J.-L. Griessmann: HART protocol rev. 7 including

WirelessHART, atp Int.-Autom. Technol. Pract. 2,

21–22 (2007)

56.46 HART 7: HART Protocol Speciﬁcation, Revision 7

(HART Communication Foundation, 2007), see also

http://www.hartcomm.org/ (last accessed April 6,

2009)

56.47 Dust Networks: TSMP Seminar. Online-Präsentation

(2006)

56.48 Dust Networks: Technical Overview of Time Syn-

chronized Mesh Protocol (TSMP), White Paper (Dust

Networks, 2006)

56.49 IBM: Standards and Web services, http://www-128.

ibm.com/developerworks/webservices/standards/

(last accessed April 6, 2009)

56.50 L. Wilkes: The web services protocol stack, Re-

port from CBDI Web Services Roadmap (2005),

http://roadmap.cbdiforum.com/reports/protocols/

(last accessed April 6, 2009)

56.51 Virtual Automation Networks: European Integrated

Project FP6/2004/IST/NMP/2 016696 VAN. Deliverable

D07.2-1: Integration Concept, Architecture Speciﬁ-

cation (2007)

56.52 D. Zuehlke: SmartFactory from vision to reality

in factory technologies, IFAC Congress 2008, Seoul

(2008)

Part F 56

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1001

Automation a

57. Automation and Robotics in Mining

and Mineral Processing

Sirkka-Liisa Jämsä-Jounela, Greg Baiden

Mines and mineral processing plants need in-

tegrated process control systems capable of

improving plant-wide efﬁciency and produc-

tivity. Mining automation systems today typically

control ﬁxed plant equipment such as pumps,

fans, and phone systems. Much work is under-

way around the world in attempting to create the

moveable equivalent of the manufacturing as-

sembly line for mining. This technology has the

goals of speeding production, improving safety,

and reducing costs. Process automation systems

in mineral processing plants provide important

plant operational information such as metal-

lurgical accounting, mass balances, production

management, process control, and optimization.

This chapter discusses robotics and automation for

mining and process control in mineral processing.

Teleoperation of mining equipment and control

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

57.2 Mining Methods

and Application Examples .....................1004

57.3 Processing Methods

and Application Examples .....................1005

57.3.1 Grinding Control ........................ 1005

57.3.2 Flotation ................................... 1007

57.4 Emerging Trends ..................................1009

57.4.1 Teleremote Equipment................ 1009

57.4.2 Evaluation of Teleoperated Mining1011

57.4.3 Future Trends in Grinding

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

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

strategies for grinding and ﬂotation serve as

examples of current development of ﬁeld.

57.1 Background

Mining is the act of extracting mineral determined to

be ore from the earth to be processed in a mineral pro-

cessing operation. All mining operations have a least

some limited mineral processing available on site. Usu-

ally the sophistication of the complex is determined by

unit process operations needed to make the product,

or distribution and transportation costs (Fig.57.1). The

mineral extraction process can occur using many po-

tential mining methods. Some of the methods include

open pit, caving, bulk stoping, and/or selective mining

techniques such as cut and ﬁll, as well as room and

pillar [57.1]. Each method and suite of mining equip-

ment has the aim of extracting the mineral at a proﬁt for

processing.

The aim of a mineral processing operation is to con-

centrate a raw ore for the subsequent metal extraction

stage. Usually, the valuable minerals are ﬁrst liberated

from the ore matrix by comminution and size separation

processes (crushing, grinding, and size classiﬁcation),

and then separated from the gangue using processes

capable of selecting the particles according to their

physical 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 role

in the mineral process industries and is gaining mo-

mentum in mining extraction operations as mobile

robotics 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., is

widespread in many sectors (Fig.57.2). Information-

based technologies are responsible for making mineral

Part F 57

1002 Part F Industrial Automation

Gyratory

crusher

Sag mill

Electrowinning

Concentrate

thickener

Anode

Anode casting wheel

Cyclones

Rougher

flotation cells

Extraction

Flotation and thickeners

Smelter

Extraction and leaching

Stock pile

Ball mill

Oxide ore

Strip tank

Pregnant

solution tank

Filter

press

Thickener

Solvent extraction

and leach tanks

Scavenger/cleaner

flotation 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 in

a safe and environmentally sound manner. One critical

step in achieving these objectives is to develop and ap-

ply improved control systems across the full range of

applications from mining to processing and utilization.

While mineral processing has had extensive use of

many advanced technologies, standard mining applica-

tions such as pumping, dewatering, hoist control, and

power distribution remain the norm with some individ-

ual exceptions in ventilation systems and other mine

wide systems. Overall, the complication and scale of

mining operations has delayed the wide adoption of

advanced technology. Several stand alone technologies

have seen successful implementation in mining and pi-

lot projects; full scale mine implementation have been

attempted with extremely encouraging results. The In-

telligent Mine Program in Scandinavia and the Mining

Automation Program [57.3] in Canada were two main

projects attempted in the 1990s and early 2000s. The

main technology drivers were seen to be: telecommuni-

cations, positioning and navigation, integrated software

systems, and mobile robotic equipment. The Intelli-

gent Mine Program explored the issues from a rock

and process characteristic point of view and the Min-

ing Automation Program from an equipment point of

view.

The optimization of the economics of the pro-

cess operations is the key driver for the application

of 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 discussed

by Herbst and Pate [57.4]. In the application, they used

an expert system and online process models to ﬁnd the

optimum feed rate. A Kalman ﬁlter was used to esti-

mate unmeasured variables such as mill ﬁlling and ore

hardness that were required by the expert system. An

8% improvement in feed rate over manual control was

achieved with the control system. In the multivariable

control application on a two-stage milling circuit at the

East Driefontein Gold Mine in South Africa, the aver-

age throughput t/h was increased from 73.1to79.2,

and the average grain size % < 75 μm from 76.5to

78.5. The standard deviation of the grain size values

was reported to decrease from 3 to the 0.9 [57.5]. Suc-

cessful economic results and beneﬁts from 13years of

computer control in ﬂotation have been reported by Mi-

ettunen [57.6].

The economics of the application of intelligent

robotics for mining was seen as having substantial ben-

eﬁts. These were discussed in Baiden [57.7]. This report

showed that the fundamental deﬁnition of ore would be

altered by the projected results of cost reduction and

mining rate improvements. Further, robotic operation

would improve the safety of miners as it would drop

exposure levels. Subsequently, the Intelligent Mine Pro-

gram and Mining Automation Program showed through

ﬁeld feasibility experimentation that these projections

were realistic. Several projects around the world now

are investigating the opportunity for robotic and teleop-

erated equipment in particular applications.

Part F 57.1

Automation and Robotics in Mining and Mineral Processing 57.1 Background 1003

Operator

workstation

Reliance electric IQ

intelligent“ motor

with PreAlert“

technology

A-B DeviceLink“

adapter with limit switch

A-B

RediStation

pushbutton

A-B

ControlLogix“

system

DODGE EZLINK

bearing

A-B DTAM“

message display

A-B

Photoelectric

sensor 9000

A-B

PLC-5/80“

controller

Reliance electric

E-master

AC motor

A-B 1329

AC motor

A-B 1329

AC motor

Reliance electric

medium voltage

AC motor

A-B CENTERLINE

motor control center

A-B Bulletin 1557/1557M

SCI medium voltage drive

A-B

Powermonitor II

A-B Dataliner

message 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 II

drive

A-B PanelView“ 550

operator terminal

DeviceNet

Plant

historian

Supervisory process control

(Rockwell software RSView32

and RSLogix Frameworks“ software)

Operator

workstations with

Rockwell software

RSView32“

active

display

Operator

workstations with

Rockwell software

RSView32

active

display

Bridge or

modem

Reliance electric FlexPak

3000 drive

Reliance electric

RPM“ III

DC motor

Reliance electric

RPM“ AC motor

A-B Redi

PANEL“

terminal

DODGE EZLINK

bearing

DODGE

TORQUE-ARM“

reducer

A-B FLEX I/O“

module

Field device I/O

Remote site 1

A-B SLC controller

Remote I/O

A-B PanelView“

operator workstation

A-B SMM“

protection relay

A-B MV dialog

Plus“ controller

through 8000 HP

A-B Medium voltage

drive through

10000 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 faced

with many challenges. At the present time it is not pos-

sible to measure, on a real-time basis, the important

physical or chemical properties of the material pro-

cesses. This is particularly true for the fresh ore feed

characteristics (mineral grain size distribution, mineral

composition, mineral association, grindability) and the

ground material properties (liberation degree, particle

composition distribution, particle hydrophobicity). An

essential feature ofcontrol andoptimization strategies is

the availability of mathematical models that accurately

describe the characteristics of the process. Satisfactory

mathematical models are not, however, available for

mineral processingunit processes due to the fact thatthe

physics and chemistry of the sub-processes involved are

poorly understood. Models for process analysis and op-

timization for comminution circuits are usually based

on population balance models and the use of break-

age and selection functions. Numerous empirical and

phenomenological models based on various assump-

tions for ﬂotation have been proposed in the literature.

Among the many ﬂotation models, the classical ﬁrst-

Part F 57.1

1004 Part F Industrial Automation

order kinetic model is widely used and can be utilized

to optimize the design of the ﬂotation circuit and its

control strategy. Recently progress has been made in

grinding circuit modeling using the discrete element

method (DEM) [57.8–12], and efforts have been made

in 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 only

real opportunity that existed. For example, the absence

of communication systems limited the types of pro-

cess control that could be applied. In the last two

decades work has been underway to change this. The

portable size of computers and the availability of net-

works to connect them to spawned growth in the

application of process control to mining. The basics

of main distribution systems such as water and power

are now the norm. Networks have further enabled the

installation of rock mechanics systems such as micro-

seismic systems. While these systems are important

they do not get to the actual main production technolo-

gies because the machine systems for production are

mobile.

Both the Intelligent Mine Program and the Min-

ing Automation Program worked to change this and the

concepts behind telemining started to gain momentum

in the mid to late 1990s. Telemining (mobile process

control for mining) is the application of remote sensing,

remote control, and the limited automation of mining

equipment 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 software

systems

•

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 equipment

and personnel, resulting in increased revenue and lower

costs.

Advanced high capacity mobile computer networks

form 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 centers

undergroundor onthe surface. Severalopportunities ex-

ist for communication, depending on the environment.

Surface mines have trended towards network systems

such as the 802.11 standard [57.14]. Whereas under-

ground mines have focused on much higher bandwidth

systems consisting of a high capacity backbone linked

to 2.4GHz capacity radio cells for communication. The

high capacity allows the operation of not only data

systems but mobile telephones, handheld computers,

mobile computers on board machines, and multiple

video 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. Positioning

systems that have sufﬁcient accuracy to locate the mo-

bile equipment in real-time at the tolerances necessary

for mining have been developed [57.17, 18]. Practical

uses of such systems include machine set-up, hole loca-

tion, and remote topographic mapping. Surface systems

use GPS for location and several of these systems have

been developed. In underground mines, some of the

most advanced positioning equipment consists of laser

reference positioning, ring-laser-gyro (RLG), and ac-

celerometers. Units are mounted on all types of drilling

machines so that operators can position the equipment.

These types of systems are just beginning to make their

presence known over conventional surveying; several

manufacturers offer this new product [57.19]. RLG sys-

tems track the location of mobile machinery in the

Mining

methods

Process engineering,

monitoring and control

Positioning and

navigation systems

Underground

telecommunication system

Mining equipment

Mining process systems

Fig. 57.3 Conceptual representation of the key technolog-

ical components (after [57.1])

Part F 57.2