EXPERT SYSTEMS FOR CORROSION PREVENTION AND CONTROL

P.R. ROBERGEDepartment ofChemistry & Chemical EngineeringRoyal Military College ofCanadaKingston, OntarioCanada, K7K 5LO

ABSTRACT: The serious gap that exists between modern corrosion science and the real world,where a heavy toll is continuously paid to corrosion, is a clear indication that the presentknowledge of corrosion mechanisms is not always translated into sound practices. Thedichotomy between prevention principles discovered in a laboratory environment and theirapplication on an industrial scale can ofien befelt at specialized conferences where scientists andoperational engineers seem to be speaking different languages. The application of artificialintelligence to pel:form expert functions has opened new communication channels betweenvarious strata of corrosion knowledge holders. This paper reviews the efforts recently madepublic on the applications ofthe expert system technology to corrosion prevention and control.

1. Introduction

One of the concluding remarks made at UMIST Corrosion and Protection Center 20thanniversary [1] was that the conference had not achieved what is most required forbetterment of corrosion protection i.e. bridging the gap between the world of practitionersof corrosion services and the academic community busying and doing research incorrosion science and engineering. It is the experience of the author that the communityis in fact separated by an abysm which can leave many stranded on the beach ofunpublished information and proprietary consciousness while others are flourishing in aworld of perfectly understood corrosion mechanisms which can only be reproduced withultrapure materials and environments. The acquisition of research knowledge throughexperimental work is a very expensive societal proposition that should be examined in thelight of the information that exists already.The adequate transfer of information covering corrosion problems and solutionsinvolves the development of information processing strategies that can become verycomplex. A typical corrosion engineering task requires handling different types ofknowledge and disciplines such as metallurgy, chemistry, cost engineering, safety andrisk analysis. The expected corrosion behavior of engineering materials is only onecomponent of the multi-facet life cycle management of systems. Databases andknowledge bases are modem tools for the transfer of information from valid sources tousers of the information. Until recently, it was difficult to include expertise derived from

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K. R. Trethewey and P. R. Roberge (eds.J, Modelling Aqueous Corrosion, 129-140.© 1994 Kluwer Academic Publishers.

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years of experience into a form which could be compatible with other computerizedinformation media.The emergence of expert systems (ESs) and other technologies from the broader field ofartificial intelligence is increasingly making it possible to integrate elements of humanreasoning into more neutral information systems. But there are several problems inherentin the current knowledge engineering methodology that contribute to the knowledgetransformation bottleneck and hinder the development of computerized expertise systems[2, 3]. To this date, many tools and techniques have been suggested for the task ofknowledge elicitation or the process of analyzing an expert task. Unfortunately, theavailability of cost effective tools and knowledge elicitation techniques is really only afragment of the complete picture. The eventual integration of an ES prototype in a user'scommunity requires at least the tacit approval of all parties involved during the variousphases of ES development. It also requires the fundamental acceptance of the expertisebeing computerized. This paper is an attempt to review the efforts which have been madepublic, during the last decade, to apply the ES technology to corrosion problems.

2. Corrosion Prevention Expert Systems

The advantages and limitations of using ES technology to mimic expertise were analyzedin great details in an early attempt to combat corrosion with ES tools [4]. The StressCorrosion Cracking (SCC) ES (SCCES) had been created to calculate the risk of variousfactors involved in SCC, such as crack initiation, when evidence was supplied by the user.The main goal of this initial effort was to support the decision process of "general"materials engineers. The system would be initially called to play the role of a consultantbut it was anticipated that SCCES had the potential to become:

• an intelligent checklist• a trainer• an expert sharpener• a communication medium• a demonstration vehicle

Since then most countries have seen groups and organizations formed to master this newinformation technology and make it deliver some of these early promises in the specificfield of corrosion control.

2.1. THE EARLY DAYS

A first account of the experience gained at Harwell in collecting and structuring corrosionknowledge for a computer based ES was published at a symposium on electrochemistry in1984 [5]. In order to understand the problems involved, it was decided to develop twoprototype systems: ACHILLES and MENTOR [6]. ACHILLES was dealing broadlywith localized corrosion and provided general advice on the problems likely to beencountered in process plant and other similar environments. On the other handMENTOR was said to be a faithful advisor of marine engineers. The experience gained

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during these development projects was resumed in a series of conclusions:

• the front-end interface to the user has to be friendly• transparency of the system is essential• a good knowledge base contains a mixture of heuristics and factual information.

ACHILLES later became the comer-stone of the ACHILLES Club Project with amandate to develop a series of expert system modules which would incorporate asubstantial digest of expertise in particular areas of corrosion and corrosion control [7].The first two modules dealt with cathodic protection and microbial corrosion. Theintention was to integrate a number of these modules into a global ES structure whichcould access individual modules during the course of a user consultation. This pioneeringwork also led to the creation of SPICES, an inference engine based on PROLOG, whichwas said to be particularly adapted to the multidisciplinary nature of corrosionphenomena [8].As better software became available, SCCES, which had been primarily developed toevaluate the ES technology, became the seed for a larger ES, Auscor. Auscor dealt withthe corrosion of stainless steels in a wide variety of environments [9]. The 1986 versionof Auscor was based on the Savoir ES software [10] and covered 28 alloys up toHastelloy C 276 and other modem ferritic, austenitic or duplex alloys. A user couldhandle a wide range of liquid environments in the temperature range 0-3000 C.As the Auscor developing group had previously established a solid experience withmathematical models for the prediction of localized corrosion problems [11-13], it was anatural exercise for them to compare their experience with the newest softwaretechnology. In this context, the ES approach was recognized as possessing the followingadvantages over mathematical modeling:

• ability to reach conclusions with incomplete information.• ability to provide information on request• less programming extensive• flexible knowledge representation schemes.

The ES approach was also recognized to have some limitations. While the probabilisticreasoning used by an ES of the Savoir type was found well suited for the development ofa predictive model, it was found limited for contexts which required quantitativeconclusions [14].On the European continent, work on ES for Corrosion Technology (ESCORT)conceived in 1984 [15,16] served to seed the establishment of a link to the EuropeanStrategic Program on Information Technology (ESPRIT) and the creation of a series ofefforts for the development of specialized modules. While ESCORT was to deal with theintegration of corrosion related issues such as troubleshooting and selection of preventivemeasures (materials, coatings or inhibitors), each module was to be specialized andarranged in a structure similar to the organization adopted by the Achilles Project Club.PRIME, which stood for Process Industries Materials Expert, was the first of thesemodules. PRIME specifically dealt with the selection of materials typically encounteredin the Chemical Process industries (CPl). PRIME could consider complex chemical

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processes equipment in contact with a wide range of environments. The materialsdescriptors were complete with generic information and specialized corrosion behavior.During the same period, but across the ocean, the National Association of CorrosionEngineers (NACE) and the National Bureau of Standards (NBS, currently NTIS) wereestablishing a collaborative program to collect, analyze, evaluate and disseminatecorrosion data [17]. In April 1986, the Materials Technology Institute (MTI) of theChemical Process Industries decided to sponsor the development of ESs for materialselection. During the following year, MTI initiated a project within the NACE-NISTCorrosion Data Program to develop a series of knowledge-based ESs concerningmaterials for handling hazardous chemicals.

2.2. PRESENT STATUS

The transfer of expertise into ES prototypes was since then attempted in several otherprojects. The NACE conference proceedings contain a series of papers which illustratethe growing interest in this technology and the increasing progress made to the toolsavailable [18]. The ES tool kits were becoming both easier to master and more portable.A recent survey of the open literature [19] revealed the existence of quite a few systemsdealing with many important aspects of corrosion prevention and control. The followinglist indicates the major areas for which some systems have been reported:

• Cathodic protection• Cooling waters• Diagnostics• Inhibitors• Materials selection• Petroleum industries• Reinforced concrete• Risk analysis

Unfortunately, many systems reported in the literature have never been commercialized.This has resulted in a lack of impartial and practical information concerning theperformance and accuracy of these systems. It is indeed very difficult to believeeverything that is said in a paper even when the information is apparently there. In orderto remedy this situation, the European Federation of Corrosion (EFC) and MTI haveperformed two surveys, between 1988 and 1990, requesting recognized developers of ESsin corrosion related areas to provide very specific information concerning the availability,scope and performance of their systems.

2.2.1. The EFC Survey. In the EFC survey, developers of ESs were asked to elaborateon the following salient features of their system:.

• Shell used• Area of application• Language (user language? programming language ?)• Hardware (platform and peripherals)

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• Development expenditure• Field evaluation status

Tables I and 2 summarize the answers given on 30 systems, developed in 6 countries,during this survey which was made in early 1989. A summary of the survey itselfindicated that the development effort reported on 22 systems averaged to 4.1 person/year(PY) with a median of 2 PYs, two of the systems representing efforts exceeding 10 PYs[20]. The expenditures for development were reported for 11 systems for an average of$490,000/year, with a median of $127,000/year. Only 4 systems were available at thetime of the survey but some were expected to be put on the market later. A total of 17different software shells were used by the developers, each developer tending to stay witha specific shell once a project had started.

2.2.2. The MTI Survey. In the MTI survey, developers ofESs were asked to notch, in awell defined grid, some slightly more specific questions than in the EFC survey, such as:

• Availability outside own organization (price, terms)• Primary objective of the system• Description of development team• Application: diagnostics, prescriptive, monitor/control, design/planning, training• Development effort and expenditure• Hardware (development, delivery)• Audience

The MTI survey encompassed descriptions for 36 systems, developed in 9 countries,with only 9 systems overlapping the EFC survey. Most systems reported were focused onthe prescription, diagnosis and training for corrosion prevention. Only a few systemsdealt with the monitoring and planning aspects of corrosion prevention and control. Themedian development time, for the 26 systems for which values were given, was 1 to 3years, with two systems again exceeding 10 years. The average budget, for 16 systemsdescribed, was $ I26,000/year with a median of $1OO,OOO/year.The survey also revealed that a total of 18 different software shells were used by thedevelopers, each developer again tending to stay with a specific shell once a project hadstarted. Most systems were developed and distributed on personal computers (PCs),which is very different than the practice reported for the early days of ES development.Seven systems were available for purchase at the time of the MTI survey but the surveyfailed to request information on the validation of the products themselves.

2.2.3. The Literature Survey. A compiled list of the 57 systems reported in the EFCand MTI surveys was compared to the literature survey [19] published in 1992. Table 3contains the fraction of these systems, approximately half of the total number surveyed byEFC and MTI, which were covered and referenced in the literature survey.The systems which had not been revealed by the literature search are listed in Table 4under different categories. These categories are an attempt to define the reason why, in afield of information processing, some systems remained invisible to a search of theliterature based on the generic keywords of (expert system(?)) AND (corrosion). Most

TABLEI

ResultsoftheEFCsurveyonexpertsystemsincorrosion.

Nam.

Country

Shell

Rules

Applications

pa

B6

Eva

luat

ion

AC

ACHILLES

UK

SPICES

Dia

gnos

is,P

redi

ctio

n.,P

reve

ntio

n3

660

ALUSELECT

Sweden

ORACLEFOCUS

200

SelectionofAlwninumAlloys

2.S

127.S

AURORA

Finland

LEVELS

830

Pred

ictio

n.Fa

ilure

Ana

lysi

s,M

ater

ials

Sele

ctio

n3.3

312

+Feedback

Buy

AURORA·STACOR

Finland

LEVELS

126

Prediction(StainlessSteel.)

I.S120

AUSCOR

UK

SAVOIR

Prediction(AusteniticStainlessSteel.)

6825

BANDMAT

Italy

DBCLIPPER

Mat

eria

lsSe

lect

ion,

Mai

nten

ance

,Mon

itori

ngEN!Consult.

BENTEN

UK

ADVISOR

200

SelectionInhibitor

2CAMS4

UK

KnowledgeBa.eSy.tem(?)

COMETA

Italy

DataBase(?)

byexperts

COREX

France

GENESTAll

80Prevention(LowAlloySteel,Atmospheric)

Inuse(EDF)

CORRBAS

Sweden

FOCUS

20D

iagn

osis

O.S

22.5

CORREAU

Fran

ceSPECIAL

ISO

CopperTubing

IBuy

CORSER

Fran

ceSPECIAL

SOOO

Mat

eria

lsSe

lect

ion,

Dia

gnos

is,P

reve

ntio

n3

CRAI

Belgium

KEE

Training,Material.Selection

I.2S

100

DB·CTW

20W

ater

Tre

atm

ent

4DOCES

Italy

PC+

120

Boilers

ERiCE

Italy

PC+

200

Monitoring,Diagnosi.(powerPlant)

2EXPRESS

UK

Xl+

1000

Pipeline,Risk

2II

S.5

GRADIENT

Belgium

KEE

CAD(HeatExchangen)

2ICompany

H2DATA

Fran

ceDataBa.e(?)

Loa

nMATEDS

Sweden

FOCUS

300

Sele

ctio

nA

lum

inum

Allo

ys2

90Buy

PETROCRUDE

Belgium

KEE

Prediction(Refinery)

2DemoOnly

PRIME

Belgium

KEE

Material.Selection

2S2S00

3Companies

PROP

Italy

700

Monitoring,Diagnosi.,Pollution(ThermalPowerPlant)

12Used(87)

R1ACE

Italy

IBMISE

500

Malerial.Selection(SeaWater,Exchangers)

3SECOND

Belgium

KAPPA

Control(CoolingTower)

750

Used3plants

SMI

Sweden

Material.Selection

STMIH20MON

Italy

ART

200

OperatorSupportPowerPlant

4VASMIT

Finland

DBASE

Fatigue

0.8

VULCAlN·BDM

France

(Minitel)

DataBase(?)

Loan

aDevelopmenteffortinpenon'year;bDevelopmentbudget(kSUS);CAvailability.

w +-

TABLE2

ResultsoftheMTIsurveyonexpertsystemsincorrosion.

Name

Country

Shell

Applications

Rol

esa

Targetb

pc

Bd

Ae

Oi

P,

PdM

PITr

ExP

rN

ACHILLES

UK

SPICES

Prev

entio

n•

••

••

·•

·10

200

ACORD

Japan

OPS83

Prediction(Seawater)

··

I140

ADVICE

USA

Prediction(HighTemperature)

··

327

AURORA-STACOR

Finland

LEVELS

Prediction(SSs)

··

•·

··

594

AUSCOR

UK

SAVOIR

Prediction(AusteniticSSs)

••

·•

10100

BENTEN

UK

ADVISOR

Sele

ctio

nIn

hibi

tor

··

·3

BLEACH

USA

EX.X"YS

MaterialsSelection(BeachPlant)

•·

·I

100

BLEACHER

Finland

KEE

MaterialsSelection(BeachPlant)

··

··

·5

BWR

Japan

OPS5

Prediction(IGSCC)

CHEM·COR

USA

KES

MaterialsSelection(HazardousChemicals)

··

·3

177

Buy

CL2

USA

LEVELS

MaterialsSelection(C12Service)

··

··

0.5

CORRCON

Israel

OPS5

DesignDiagnosis

•·

•·

·0.5

CORREAU

Fran

ceNOVYS

CopperTubing

··

··

·3

20Buy

CORRES

Japan

SOHGEN

Prediction

CORSER

Fran

ceM

ater

ials

Sele

ctio

n,D

iagn

osis

,Pre

vent

ion

··

··

•·

50236

CR

Al

Belgium

KEE

Tra

inin

g.M

ater

ials

Sele

ctio

n•

175

DESAD

Usa

PC+

Prevention(DesalterUnit)

•·

•·

·0.5

DIASCC

Japan

OPS83

RiskOISCC(SSs)

·•

·0.5

Buy

ECHOS

Japan

ESHELL

Prediction,Maintenance,Shutdowns

FERPRED

USA

PC+

FerriteinWelds

··

·Buy

GENERAL

UK

MaterialsSelection,Prediction

JUNIPER

UK

AuthoringTools

KISS

Gennany

NEXPERT

MaterialsSelection(CPI)

·•

··

··

··

3355

MATGEO

NewZealand

KES

MaterialsSelection(GeothennalPlanls)

••

•·

0.5

58OILSTO

Japan

Prediction,Inspection

PBCORR

UK

CAMS4

COlTOSionofLead

••

•·

·3

Buy

PC6493

UK

CAMS4

DefectAssessment(PC6493)

•••

399

PETRQ-CORI

NewZealand

KES

MaterialsSelection(SuckerRod

Pum

ps)

•·

•·

·3

75Buy

PO

UR

BA

IXBelgium

••

••

PRIME

Belgiwn

KEE

MaterialsSelection

··

•·

150

REFMAIN

Japan

On-LinePrediction<Refmery)

SECOND

Belgiwn

KAPPA

Control(CoolingTower)

••

•50

SSCP-PHI

USA

PC+

MaterialsSelection(H2S)

WEWPLAN

Japan

OPS83

Advise(WeldParameter)

WELDSEL

USA

PC+

Advise(WeldRod)

•·

Buy

WELDSYM

USA

PC+

Advise(Symbol)

••

Buy

aDiagnose(Oi),Preseihe(ps),Predict(Pd),Monitor(M),Train(Tr);bExpert(Ex),Professional(Pr),Novice(N);cDevelopmenteffortinpenon·year;dDevelopmentbudget(kSUS);eAvailability.

w Ul

136

of these categories are self explanatory.

TABLE 3Cross compilation of the expert systems identified in the literature survey [19] with the

EFC and MTl surveys of developers.

Name Country EFC MTIACHILLES UK • •ADVICE USA •AURORA Finland •AURORA-STACOR Finland • •AUSCOR UK • •BENTEN UK • •CAMS4 UK •CHEM*COR USA •COMETA Italy •COREX France •CORREAU France • •CRAI Belgium • •DOCES Italy •ERICE Italy •EXPRESS UK •GRADIENT Belgium •JUNIPER UK •MATGEO New Zealand •PETRO-COR I New Zealand •PETROCRUDE Belgium •PRIME Belgium • •PROP Italy •RIACE Italy •SECOND Belgium • •SSCP-PHI USA •STM/H20MON Italy •

It is natural to expect, for example, that systems developed in Japan would take a longtime to become visible in mainstream scientific publications and would thus have littlepoints of reference. The fact that the MTl survey indicated that none of the Japanesesystems were available supports this conclusion. The list in Table 4 contains also a seriesof systems, reported in the MTl survey, which had only very indirect links to corrosionand would thus never show up in a search restricted to corrosion issues. Anothercategory describes a series of Data Bases, reported mostly in the EFC survey, whichwould not be associated under the keyword of expert system(?).The two systems under the 'to be developed' category could have made their way to the

137

TABLE 4Expert systems identified in the EFC and MTI surveys of developers but absent from the

literature survey [19].

Name Country EFC MTISpecialized Systems

BLEACH USA •BLEACHER Finland •CL2 USA •CORSER France • •DESAD USA •KISS Gennany •PBCORR UK •

To be DevelopedCORRCON Israel •GENERAL UK •

Data BasesBANDMAT Italy •CORRBAS Sweden •DB-CTW •HYDROGEN DATA France •POURBAIX Belgium •SMI Sweden •VASMIT Finland •VULCAIN-BDM France •

Japanese SystemsACORD Japan •BWR Japan •CORRES Japan •D1ASCC Japan •ECHOS Japan •OILSTO Japan •REFMAIN Japan •WELDPLAN Japan •

Indirectly RelatedALUSELECT Sweden •FERPRED USA •MATEDS Sweden •PC6493 UK •WELDSEL USA •WELDSYM USA •

138

open literature since many such systems are regularly reported on the basis ofphilosophical and other developmental issues. The final category of specialized systemscontains systems dealing with the prevention of corrosion problems associated with veryspecific processes. These specialized systems apparently deal only incidentally withcorrosion problems and this would explain why they have not been reported in theliterature as corrosion related systems. The distribution of expert systems between thesecategories and the overlap with the literature search is presented in Fig. I.

Literature46%

Data Bases14%

Japanese14% Specialized

12%

4%

Indirect11%

Fig. / Distribution ofexpert systems reported in the EFC and MT/ surveys as a function oftheircategories (Table 4) and overlap (Table 3) with the /992 literature search [/9].

3. Conclusion

The past low availability of expert systems dealing with corrosion problems may changein the future but it appears that the success of previous development efforts was directlyrelated to the degree of specialization of the systems developed. But while such systemsmay have found an important in-house usage, they are the most difficult systems toexport. The proprietary nature of the information often contained in these systemscombined with a multitude of hardware and software particularities add to make the

139

transfer of these systems to a broader audience very difficult. The extremely rapidevolution of the information processing tools themselves is forcing developers to adoptnew strategies. The tremendous energy required to produce and maintain softwaresystems, only a few years ago, was making a good fraction of the high price ofdevelopment of expert systems.While visions of systems which would answer all questions and solve all corrosionrelated problems are slowly fading away, very focused ESs are being integrated in largerdesign and control systems in order to prevent corrosion damages. Other very focusedESs are also being built and tested to simplify the requirements for multidisciplinaryexpertise associated with corrosion engineering practices. A few of these computerizedmethodologies have already reached mainstream applications and are readily available.On a very general note it can be said that the knowledge engineering aspect of developingESs for corrosion applications is directly related to the continuous progress in thesoftware and hardware tools which are made available. The fact that these tools areimproving at an incredible speed is very promising for the future. Another aspect ofdeveloping ESs is more related to a societal attitude toward the value of preservingknowledge and extending the life of existing systems. This aspect of corrosionprevention reflects the degree of maturity an organization or a society has acquired. Thequestions associated with the newly available answers will have to be addressed In arealistic mindframe. This story will be an interesting one to follow.

References

I. Int. Conf. Advances in Corrosion and Protection, University of Science and Technology,28th June- 3rd July 1992, Manchester, U.K.

2. D.W. Rolston, "Principles of Artificial Intelligence and Expert Systems Development,"McGraw-Hili, New York, NY, 1988.

3. C. Williams, "Expert Systems," Knowledge Engineering, and AI Tools - An Overview,"IEEE Expert, Winter 1986, 66-70.

4. A. Basden, "On the Applications of Expert Systems," International Journal ofMan-MachineStudies, Vol 19, 1983,461-472.

5. C. Westcott, D.E. Williams, NJ.M. Williams, G.P. Marsh, J.N. WankIyn andI.F. Croall,"Expert Systems-The Application of New Computer Methods toCorrosion Problems," ComputerAided Acquisition and Analysis of Corrosion Data, M.W. Kendig, V. Bertocci and J.E. Strutt,Eds., The Electrochemical Society, Pennington, MA, USA, 1984, 190-199.

6. J.N. WankIyn and NJ.M. Wilkins, "Development of an Expert System for DesignCosultation on Marine Corrosion," British Corrosion Journal, VoI.20, No.4, 1985, 161-166.

7. "The ACHILLES Club Project - Expert System on Corrosion and Corrosion Control," NPL,Teddington, Middlesex, U.K., October 1986, 1-10.

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8. C. Westcott, D.E. Williams, I.F. Croall, S.Patel and J.A. Bernie, "The Development andApplication of Integrated Expert Systems and Databases for Corrosion Consultancy," Proc.NACE 86 Corrosion Conference, National Association of Corrosion Engineers, March 17-211986, Houston, TX, U.S.A., Paper No. 54.

9. J.G. Hines and A. Basden, "Experience with Use of Computers to Handle CorrosionKnowledge," British Corrosion Journal, Vol. 21, No.3, 1986, 151-156.

10. "Savoir", lSI Ltd., 11 Oakdene Road, Redhill, Surrey, U.K., 1986.

II. J.G. Hines, "Corrosion Information and Computers," British Corrosion Journal, Vol. 21,No.2, 1986,81-85.

12. J.G. Hines, "Analysis of Complex Polarisation Curves," British Corrosion Journal, Vol. 18,No.1, 1983, 10-14.

13. C. Edeleanu and J.G. Hines, "Modelling Approach to Corrosion Prediction," BritishCorrosion Journal, VoLl8, No.1, 1983,6-9.

14. J.G Hines and lG. Basden, "Implications of Relation Between Information and knowledgein Use ofComputers to Handle Corrosion Knowledge," British Corrosion Journal, Vol.21, No.3,1986, 157-162.

IS. A Jadot and L. Lanclus, CL "ESCORT: "Expert Software for Corrosion Technology,"Dissertation, K. V. Leuven University, Belgium, 1985.

16. C. Bolle and I. Van Eester, "The Use ofthe Shell EXSYS in ESCORT, an Expert System forCorrosion Technology," Dissertation, K. V. Leuven University, Belgium, 1986.

17. G.M. Ugiansky, A.C. Van Orden and D.E. Clausen, "The NACE-NBS Corrosion DataProgram," Computers in Corrosion Control, J. Fu, R. Heidersbach and R. Erbar Eds., NationalAssociation ofCorrosion Engineers, Houston, TX, U.S.A., 1986, 15-20.

18. H. Sasaki, "Corrosion-Engineering Database Systems," Corrosion Engineering, Vol. 37,1988, 567-574.

19. P.R. Roberge, "Bridging the Gap Between Corrosion Laboratories and the Real World: theExpert System Approach," Computers in Corrosion Control Vol. 1lI, P. Mayer, AC. Van Ordenand T. Hakkarainen Eds., National Association of Corrosion Engineers, Houston, TX, U.S.A,1992,258/1-13.

20. Report of Task Group I of the Working Party on Expert Systems in Materials Engineering,Materials Technology Institute, St.-Louis, MO, April 1990, 1-124.