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Trends in Automation 8.2 Current Trends 135

Fig. 8.9 Trend towards object-oriented modeling, e.g., visual ﬂowsheet modeling; combined commodity models with

proprietary knowledge; automatic generation of stand-alone executable code

The huge success of wireless technology in other

areas of daily life raises the question of whether this

technology can also be applied to automation prob-

lems. As recent developments have shown, this trend is

continuously gaining momentum [8.10]. Different ap-

proaches are distinguished as a function of how power

is supplied, e.g., by electrical cable, by battery or by

power harvesting from their process environment, and

by the way the communication is implemented.

As with wired communications, also wireless sum-

marizes a variety of technologies which will be

discussed in the following sections.

Close Range. In the very close range, serial com-

munication today very often makes use of Bluetooth

technology. Originating from mobile phone accessory

integration, similar concepts can also be applied in sit-

uations in which devices need to communicate over

a short distance, e.g., to upgrade ﬁrmware, or to read

out diagnostics. It merely eliminates the need for a se-

rial cable, and in many cases the requirement to have

close-range interaction with a device has been removed

completely, since it is connected to the system through

other serial buses (such as a ﬁeldbus) that basically al-

low the user to achieve the same results.

Another upcoming technology under the wire-

less umbrella is radio frequency identiﬁcation (RFID).

These small chips are powered by the electromagnetic

ﬁeld setup tocommunicate by the sensing device. RFID

chips are used to markobjects (e.g.,items in a store), but

can also be used to mark plant inventory and keep track

of installed components. Chapter 49 discusses RFID

technology in more detail.

RFID can not only be used to read out information

about a device (such as a serial number or technical

data), but to store data dynamically. The last mainte-

nance activity can thus be stored on the device rather

than in a plant database. The device keeps this informa-

tion attached while being stored as spare part, even if it

is disconnected from the plant network. When looking

for spares, the one with the fewest past operating hours

can therefore be chosen. RFID technology today allows

for storage of increasing amounts of data, and in some

cases is even capable of returning simple measurements

from an integrated sensor.

Information stored on RFID chips is normally not

accessed in real time through the automation system,

but read out by the maintenance engineer walking

through the plant or spare parts storage with the corre-

sponding readingdevice.To displaythe full information

on the device (online health information, data sheet,

etc.) a laptop or tablet personal computer (PC) can

then retrieve the information online through its wireless

communication capability.

Part A 8.2

136 Part A Development and Impacts of Automation

Mid-range. Apart from distributing online data to mo-

bile operator terminals throughout the plant, WiFi has

made its entrance also on the plant ﬂoor.

The aforementioned problem, where sensors can-

not easily be wired to the main automation system, is

increasingly being solved by the use of wireless com-

munication, reducing the need and cost for additional

cabling.

Applications where the installation of wired instru-

ments is difﬁcult are growing, including where:

•

The device is in a remote location.

•

The device is in an environment that does not allow

for electrical signal cables, e.g., measurements on

medium- or high-voltage equipment.

•

The device is on the move, either rotating, or mov-

ing around as part of a production line.

•

The device is only installed temporarily, either for

commissioning, or for advanced diagnostics and

precise fault location.

The wide range of applications has made wireless de-

vice communication one of the key topicsin automation

today.

Long Range. Once we leave the plant environ-

ment, wireless communication capabilities through

GSM (global system for mobile communication) or

more advanced third-generation (3G) communication

technologies allow seamless integration of distributed

automation systems.

Applications in this range are mostly found in dis-

tribution networks (gas, water, electricity), where small

stations with low functionality are linked together in

a large network with thousands of access points.

However, also operator station functionality can

be distributed over long distances, by making thin-

client capabilityavailable to handheld devices ormobile

phones. To receive a plant alarm through SMS (short

message service, a part of the GSM standard) and to be

able to acknowledge it remotely is common practice in

unmanned plants.

Nonautomation Data. In addition to real-time plant

information that is conveyed thorough the plant au-

tomation system, plant operation requires much more

information to run a plant efﬁciently. In normal opera-

tion as well as in abnormal conditions, a plant operator

or a maintenance engineer needs to switch quickly

between different views onthe process.The processdis-

play shows the most typical view, andtrend displays and

event lists are commonly use to obtain the full picture

on the state of the process. To navigate quickly between

these displays is essential.To call up the process display

for a disturbed object directly from the alarm list saves

critical time.

Once the device needs further analysis, this nor-

mally requires the availability of the plant documenta-

tion. Instead of ﬂipping through hundreds of pages in

documentation binders, it is much more convenient to

directly open the electronic manual on the page where

the failed pump is described together with possibilities

to initiate the required maintenance actions.

Availability of the information in electronic format

is today not an issue. Today, all plant documentation

is provided in standard formats. However, the infor-

mation is normally not linked. It is hardly possible

to directly switch between related documents without

manual search operations that look for the device’s tag

or name.

An object-oriented plant model that keeps refer-

ences to all aspects of a plant object greatly helps in

solving this problem. If in one location in the system,

all views on the very same object are stored – process

display, faceplate,event list, trend display, manufacturer

instructions, but also maintenancerecords andinventory

information – a more complete view of the plant state

can be achieved.

The reaction to process problems can be much

quicker, and personnel in the ﬁeld can be guided to

the source of the problem faster, thus resolving issues

more efﬁciently and keeping the plant availability up.

We will see in Lifecycle Optimization how maintenance

efﬁciency can even be increasedby advanced asset man-

agement methods.

Security. A general view on the future of automation

systems would not be complete without covering the

most prominent threat to the concepts presented so far:

system security.

When systems were less integrated, decoupled

from other information systems, or interconnected by

4–20mA or binary input/output (I/O) signals, system

security was limited to physical security, i.e., to pre-

vent unauthorized people access the system by physical

means (fences, building access, etc.).

Integrating more and more information systems into

the automation system, and enabling them to distribute

data to wherever it is needed (i. e., also to company

headquarters through the Internet), security threats soon

become a major concern to all plant owners.

The damage that can be caused to a business by neg-

ligence or deliberate intrusion is annoying when web

Part A 8.2

Trends in Automation 8.2 Current Trends 137

sites are blocked by denial-of-service attacks. It is sig-

niﬁcant if it affects the ﬁnancial system by spyware

or phishing attacks, but it is devastating when a coun-

try’s infrastructure is attacked. Simply bringing down

the electricity system already has quite a high impact,

but if ahacker gainsaccess to an automation system, the

plant can actually be damaged and be out of service for

a signiﬁcant amount of time. The damage to a modern

society would be extremely high.

Security therefore has to be at the top of any list

of priorities for any plant operator. Security measures

in automation systems of the future need to be con-

tinuously increased without giving up some of the

advantages of wider information integration.

In addition to technical measures to keep a plant se-

cure, security management needs to be an integral part

of any plant staff member’s training, as is health and

safety management today.

While security concerns for automation systems are

valid and need to be addressed by the plant manage-

ment, technical means and guidance on security-related

processes are available today to secure control systems

effectively [8.11]. Security concerns should therefore

not be the reason for not using the beneﬁts of informa-

tion integration in plants and enterprises.

Engineering Integration

The increased integration of devices and systems from

plant ﬂoor to enterprise management poses another

challenge for automation engineers: information inte-

gration does not happen by itself, it requires signiﬁcant

engineering effort. This increased effort is a contra-

diction to the requirement for faster and lower-cost

project execution. This dilemma can only be resolved

by improved engineering environments. Chapter 86,en-

terprise integration and interoperability, delves deeper

into this topic.

Today, all areas of plant engineering, starting at

process design and civil engineering, are supported by

specialized engineering tools. While their coupling was

loose in the past, and results of an engineering phase

were handed over on paper and very often typed into

other tools again, the trend towards exchanging data

in electronic format is obvious. Whoever has tried to

exchange data between different types of engineering

tools immediately faces the questions:

•

What data?

•

What format?

The question about what data can only be answered

by the two parties exchanging data. The receiver only

knows what data he needs, and the provider only

knows what data she can provide. If the two parties

are within different departments of the same company,

an internal standard on data models can be agreed

on, but when the exchange is between different busi-

ness partners, this very often results in a per-project

agreement.

In electrical systems, this issue has been addressed

by IEC 61850. In addition to being a communication

standard, it also covers a data model. Data objects

(logical nodes) are deﬁned by the standard, and en-

gineering tools following the standards can easily

integrate devices of various vendors without project

speciﬁc agreements. The standard was even extended

beyond electrical systems to cover hydropower plants

(and also for wind generators in IEC 61400-25). So far,

further extensions into other plant types or industries

seem hardly feasible due to the variance and company

internal-grown standards.

The discussion on the format today quickly turns

into a spreadsheet-based solution. This approach is very

common, and most tools provide export and/or import

functionality in tabular form. However, this requires

separate sheets for each object type, since the data

ﬁelds may vary between objects. A format that supports

a more object-oriented approach is required.

Recently, the most common approach is to go to-

wards XML-based formats. IEC 61850 data is based

on XML, and there are standardization tendencies that

follow the same path. CAEX (computer aided engineer-

ing exchange, an engineering data format) according

to IEC 62424 is just one example; PLCOpen XML or

AutomationML are others.

The ability to agree on data standards between en-

gineering tools greatly eases interaction between the

various disciplines not only in automation engineering,

but in plant engineering in general.

Once the data format is deﬁned, there still remains

the question of wording or language. Even when us-

ing thesame language,two different engineering groups

may callthe samepiece ofinformation differently. Ase-

mantic approach to information processing may address

this issue.

With some of these problems addressed in a nearer

future, further optimization is possible by a more par-

allel approach to engineering. Since information is

revised several times during plant design, working with

early versions of the information is common. Updates

of the information is normally required, and then up-

dating the whole engineering chain is a challenge. To

work on a common database is a trend that is evolving

Part A 8.2

138 Part A Development and Impacts of Automation

in plant design; but also in the design of the automa-

tion system, a common database to hold various aspects

of automation engineering is an obvious idea. Once

these larger engineering environments are in place, data

exchange quickly becomes bidirectional. Modiﬁcations

done in plant design affect the automation system, but

also information from the automation database such as

cabling or instrumentation details should be fed back

into the plant database. This is only possible if the data

exchange can be done without loss of information, oth-

erwise data relations cannot be kept consistent.

Even if bidirectional data exchange is solved, more

partners in complex projects easily result in multidirec-

tional data exchange. Versioning becomes even more

essential than in a single tool. Whether the successful

solution of data exchange between two domains can be

kept after each of the tools is released in a new version

remains to be seen. The challenges in this area are still

to be faced.

Customer Value

The overall value of integration for owners is appar-

ent on various levels, as we have shown in the previous

Sections.

The pressure to shorten projects and to bring down

costs will increase the push for engineering data inte-

gration. This will also improve the owner’s capability

to maintain the plant later by continuously keeping the

information up to date, therefore reducing the lifecycle

cost of the plant.

The desire to operate the plant efﬁciently and keep

downtimes low and production quality up will drive

the urge to have real-time data integrated by connect-

ing interoperable devices and systems on all levels of

the automation system [8.12]. The ability to have com-

mon event and alarm lists, to operate various type of

equipment from one operator workplace, and to obtain

consistent asset informationcombined inone systemare

key enablers for operational excellence.

Security concerns require a holistic approach on the

level of the whole plant, integrating all components into

a common security framework, both technically and

with regard to processes.

8.2.2 Optimization

The developments described up to now enable one fur-

ther step in productivity increase that has only been

partially exploited in the past. Having more informa-

tion available at any point in an enterprise allows

for a typical control action: to close the loop and to

optimize.

Control

Closest to the controlled process, closing the loop

is the traditional ﬁeld of automation. PID controllers

(proportional-integral-derivative) mostly govern today’s

world of automation. Executed by programmable logic

controllers (PLC)orDCS controllers, they do a fairly

good job at keeping the majority of industrial processes

stable.

However, even if much more advanced control

schemes are available today, not even the ancient PID

loops perform where they could if they were properly

tuned. Controller tuning during commissioning is more

of an art done by experienced experts than engineering

science.

As we have already concluded in Process Inte-

gration, several advantages favor the application of

advanced control algorithms. Their ability to keep pro-

cesses stable in a narrower band allows either to choose

smaller equipment to reach a given limit, or to increase

the performance of existing equipment by running the

process closer to boundaries.

However, controllers today are mostly designed

based on knowledge of a predominantly ﬁxed process,

i.e., plant topology and behavior is assumed to be as-

designed. This process knowhow is often depicted in

a process model which is either used as part of the con-

troller (e.g., model predictive control) or has been used

to design the controller.

Once the process deviates from the predeﬁned

topology, controllers are soon at their limits. This can

easily happen when sensors or communication links

fail. This situation is today mostly solved by redundant

design, but controllers that consider some amount of

missing information may be an approach to increase the

reliability of thecontrol system evenfurther. Controllers

reacting more ﬂexibly to changing boundary conditions

will extend the plant’s range of operation, but will also

reduce predictability.

Another typical case of a plant deviating from the

designed stateis ageing or equipmentdegradation. Con-

trollers that can handle this (e.g., adaptive control) can

keep the process in an optimal state even if its com-

ponents are not. Furthermore, a controller reacting on

performance variations of theplant cannot onlyadapt to

it, but also convey this information to the maintenance

personnel to allow for efﬁcient plant management and

optimization.

Part A 8.2

Trends in Automation 8.2 Current Trends 139

Plant Optimization

At a plant operation level, all the data generated by

intelligent ﬁeld devices and integrated systems comes

together. To have more information available is posi-

tive, but to the plant operator it is also confusing. More

devices generating more diverse alarms quickly ﬂood

a human operator’s perception. More information does

not per se improve the operation of a plant. Information

needs to be turned into knowledge.

This knowledge is buried in large amounts of data,

in the form of recorded analog trend signals as well

as alarm and event information. Each signal in itself

only tells a very small part of the story, but if a larger

number of signals are analyzed by using advanced

signal processing or model identiﬁcation algorithms,

they reveal information about the device, or the system

observed.

This ﬁeld is today known as asset monitoring. The

term denotes anything from very simple use counters

up to complex algorithms that derive system lifecycle

information from measured data. In some cases, the in-

ternal state of a high-value asset can be assessedthrough

the interpretation of signals that are available in the au-

tomation system already used in control schemes. If the

decision is between applying some analysis software

or to shut down the equipment, open it, and visually

inspect, the software version can in many cases more

directly direct the maintenance personnel towards the

true fault of the equipment.

The availability of advanced asset monitoring al-

gorithms allows for optimized operation of the plant.

If component ageing can be calculated from measure-

ments, optimizing control algorithms can put the load

on less stressed components, or can trade asset lifecy-

cle consumption against the quick return of a fast plant

start-up.

The requirement to increase availability and pro-

duction quality calls for advanced algorithms for asset

monitoring and results in an asset optimization scheme

that directly inﬂuences the plant operator’s bottom line.

The people operating the plant, be it in the opera-

tions department or in maintenance, are supported in

their analysis of the situation and in their decisions by

more advanced systems than are normally in operation

today.

When it comes to discrete manufacturing plants, the

optimization potential is as high as in continuous pro-

duction. Advanced scheduling algorithms are capable

of optimizing plant utilization and improving yield. If

these algorithmsare ﬂexible to allow a reschedulingand

Control Process

Reference Actuation

Sensing &

estimating

Economic life cycle

cost estimate

Context, e.g. market price,

weather forecast

Life cycle

cost model

Economic

optimization

Fig. 8.10 Trend towards lifecycle optimization

production replanning in operation to accommodate ur-

gent ordersat runtime, plant efﬁciency canbe optimized

dynamically and have an even more positive effect on

the bottom line.

Lifecycle Optimization

The optimization concepts presented so far enable

a plant owner to optimize OEE on several levels

(Fig.8.10). We have covered online production opti-

mization as well as predictive maintenance through

advanced asset optimization tools. If the scope of the

optimization can be extended to a whole ﬂeet of plants

and over a longer period of time, continuous plant im-

provement by collecting best practices and statistical

information on all equipment and systems becomes fea-

sible.

What does the automation system contribute to

this level of optimization? Again, most data origi-

nates from the plant automation system’s databases.

In Plant Optimization we have even seen that asset

monitoring provides information that goes beyond the

raw signals measured by the sensors and can be used

to draw conclusions on plant maintenance activities.

From a ﬁxed-schedule maintenance scheme whereplant

equipment is shut down based on statistical experience,

asset monitoring can help moving towards a condition-

based maintenance scheme. Either equipment operation

can be extended towards more realistic schedules, or

emergency plant shutdown can be avoided by early de-

tecting equipment degradation and going into planned

shutdown.

Interaction with maintenance management sys-

tems or enterprise resource planning systems is today

evolving, supported by standards such as ISA95.

Enterprise-wide information integration is substantialto

Part A 8.2

140 Part A Development and Impacts of Automation

be continuously on top of production and effectiveness,

to track down inefﬁciencies in processes both technical

and organizational.

These concepts have been presented over the

years [8.13], but to really close the loop on that

level requires signiﬁcant investments by most industrial

companies. Good examples of information integration

on that level are airline operators and maintenance

companies, where additional minutes used to service

deﬁciencies in equipment become expensive. Failure

to address these deﬁciencies become catastrophic and

mission critical.

8.3 Outlook

The current trends presented in the previous Sections

do show beneﬁts, in some cases signiﬁcant. The push to

continue the developments along these lines will there-

fore most probably be sustained.

8.3.1 Complexity Increase

One general countertrend is also clearly visible in many

areas: increased complexity to the extent that it be-

comes a limiting factor. System complexity does not

only result in an increase in initial cost (more in-

stalled infrastructure, more engineering), but also in

increased maintenance (IT support on plant ﬂoor).

Both factors inﬂuence OEE (Fig.8.1) negatively. To

counter the perceived complexity in automation sys-

tems it is therefore important to facilitate wider

distribution of the advanced concepts presented so

far.

Control, equipment

design optimization

Operating procedure

optimization

Many others

Yield

accounting

Soft sensing

Diagnosis and troubleshooting

Optimization (steady state + dynamic)

Decision support

Linearization

Data reconciliation

Parameter estimation

Fitted

model

Plant

Raw

plant

data

Reconciled

plant

information

Initial

model

Offline

Online

Plant data

Estimation

Linear models

[A,B,C,D]

Model predictive control

Linearized modelsAdvanced MPC

Up-to-date

model

Fig. 8.11 Trend towards automation and control modeling and model reuse

Modeling

Many of the solutions available today in either asset

monitoring or advanced control rely on plant models.

The availability of plant models for applications such

as design or training simulation is also essential. How-

ever, plant models are highly dependent on the process

installation, and need to be designed or at least tuned

to every installation. Furthermore, the increased com-

plexity of advanced industrial plants also calls for wider

and more complex models. Model building and tuning

is today still very expensive and requires highly skilled

experts. There is a need common to different areas and

industries to keep modeling affordable.

Reuse of models could address this issue in two

dimensions:

•

To reuse a model designed for one application in an-

other, i. e., to build a controller design model based

Part A 8.3

Trends in Automation 8.3 Outlook 141

on a model that was used for plant design, or de-

rive the model used in a controller from one that

is available for performance monitoring. The plant

topology that connects the models can remain the

same in all cases.

•

To reuse models from project to project, an ap-

proach thatcan also be pursued with engineering so-

lutions to bring down engineering costs (Fig.8.11).

Operator Interaction

Although modern operator stations are capable of in-

tegrating much more information to the operator or

maintenance personnel, the operator interaction is not

alwaysthe mostintuitive. In plant diagnostics and main-

tenance this may be acceptable, but for the operator it

is often difﬁcult to quickly perceive a plant situation,

whether good or bad, and to act accordingly. This is

mostly due to the fact that the operator interface was

the plant and the automation function, and not the plant

environment where the operator needs to navigate.

An operator interface closer to the plant opera-

tor’s natural environment (and therefore to his intuition)

could improve the perception of the plant’s current

status.

One way of doing this is to display the status in

a more intuitive manner. In an aircraft, the artiﬁcial

horizon combines a large number of measurements in

one very simple display, which can be interpreted intu-

itively by the pilot by just glancing at it. Its movement

gives excellent feedback on the plane’s dynamics. If we

compare this simple display with a current plant op-

erator station with process diagrams, alarm lists, and

trend displays, it is obvious that plant dynamics can-

not be perceived as easily. Some valuable time early in

critical situations is therefore lost by analyzing numbers

on a screen. To depict the plant status in more intuitive

graphics could exploit humans’ capability to interpret

moving graphics in a qualitative way more efﬁciently

than from numerical displays.

Automated Engineering

As we have pointed out in Modeling, designing and

tuning models is a complex task. To design and tune

advanced controllers is as complex. Even the effort to

tune simple controllers is in reality very often skipped,

and controller parameters are left at standard settings of

1.0 for any parameter.

In many cases these settings can be derived from

plant parameters without the requirement to tune online

on site. Drum sizes or process set-points are docu-

mented during plant engineering, and as we have seen

in Engineering Integration, this data is normally avail-

able to the automation engineer. If a control loop’s

settings are automatically derived from the data found

in the plant information, the settings will be much better

than the standard values. To the commissioning engi-

neer, this procedure hides some of the complexity of

controller ﬁne-tuning.

Whether it is possible to derive control loops auto-

matically from the plant information received from the

plant engineering tools remains to be seen. Very simple

loops can be chosen based on standard conﬁgurations of

pumps and valves, but a thorough check of the solution

by an experienced automation engineer is still required.

On the other hand, the information contained in en-

gineering data can be used to check the consistency of

the manually designed code. If a plant topology model

is available that was read out of the process & in-

strumentation diagram, also piping & instrumentation

diagram (P&ID) tool information, automatic measures

can be taken to check whether there is an inﬂuence of

some sort (control logic, interlock logic) between a tank

level and the feeding pump.

8.3.2 Controller Scope Extension

Today’s control laws are designed on the assumption

that the plant behaves as designed. Failed components

are not taken into consideration, and deteriorating plant

conditions (fouling, drift, etc.) are only to some extent

compensated by controller action.

The coverage of nonstandard plant conﬁgurations

in the design of controllers is rarely seen today. This

is the case for advanced control schemes, but also for

more advanced scheduling or batch solutions, consider-

ation of these suboptimal plant states in the design of

the automation system could improve plant availabil-

ity. Although this may result in a reduction of quality,

the production environment (i.e., the immediate mar-

ket prices) can still make a lower-quality production

useful. To detect whether this is the case, an integra-

tion between the business environment, with current

cost of material, energy, and maybe even emissions,

and the production information in the plant allows to

solve optimization problems that optimize the bottom

line directly.

8.3.3 Automation Lifecycle Planning

In the past, the automation system was an initial

investment like many other installations in a plant.

Part A 8.3

142 Part A Development and Impacts of Automation

It was maintained by replacing broken devices by

spares, and kept its functionality throughout the years.

This option is still available today. In addition to

I/O cards, an owner needs to buy spare PCs like

other spare parts that may difﬁcult to buy on the

market.

The other option an owner has is to continuously

follow the technology trend and keep the automation

system up to date. This results in much higher life-

cycle cost, but against these costs is the beneﬁt of

always having the newest technology installed. This

in turn requires automation system vendors to contin-

uously provide functionality that improves the plant’s

performance, justifying the investment.

It is the owner’s decision which way to go. It is not

an easy decision and shows the importance of keeping

total cost of ownership in mind also when purchasing

the automation system.

8.4 Summary

Today’s business environment as well as technology

trends (i.e., robots) are continuously evolving at a fast

pace (Fig.8.12). To improve a plant’s competitiveness,

a modern automation system must make use of the

advancements in technology to react to trends in the

business world.

The reaction of the enterprise must be faster, at the

lowest level to increase production and reduce down-

time, and at higher levels to process customer orders

efﬁciently and react to mid-term trends quickly. The

data required for these decisions is mostly buried in the

automation system; for dynamic operation it needs to

be turned into information, which in turn needs to be

processed quickly. To improve the situation with the au-

tomation system, different systems on all levels need

to be integrated to allow for sophisticated information

processing.

The availability of the full picture allows the opti-

mization of single loops, plant operation, and economic

performance of the enterprise.

Fig. 8.12 Trend towards more sophisticated robotics

The technologies that allow the automation system

to be the core information processing system in a pro-

duction plant are available today, are evolving quickly,

and provide the means to bring the overall equipment

effectiveness to new levels.

References

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Roadmap Automation 2015+, ZVEI Automation

(2006), in German

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for Cold Rolling Mills: The next generation of

Automation Systems and Solutions, IFAC Work-

shop New Technol. Autom. Metall. Ind. (Shanghai

2003)

8.3 IEC 61508, Functional safety of electrical/elec-

tronic/programmable electronic safety-related sys-

tems

8.4 IEC 61850, Communication networks and systems in

substations

8.5 R. Zurawski: The Industrial Information Technology

Handbook (CRC, Boca Raton 2005)

8.6 IEC 61158, Industrial communication networks –

Fieldbus speciﬁcations

8.7 C. Brunner, K. Schwarz: Beyond substations – Use of

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61850 (April 2007)

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tegrator (2007) http://www.nettedautomation.com/

download/IEC61850-Peopleware_2006-11-07.pdf

8.9 ARC Analysts: The top automation trends and tech-

nologies for 2008, ARC Strategies (2007)

Part A 8

Trends in Automation References 143

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8.11 M. Naedele: Addressing IT Security for Critical Control

Systems, 40th Hawaii Int. Conf. Syst. Sci. (HICSS-40)

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8.13 Center for intelligent maintenance systems,

www.nsf.gov/pubs/2002/nsf01168/nsf01168xx.htm

Part A 8

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