- Email: [email protected]
Intelligent knowledge-based systems for tribological coating selection
Thin Solid Films,
109 (1983) 305-3
METALLURGICAL
INTELLIGENT TRIBOLOGICAL A. MATTHEWS Department
(Received
11
AND PROTECTIVE
305
COATINGS
KNOWLEDGE-BASED SYSTEMS COATING SELECTION
FOR
AND K. G. SWIFT
q/Engineering
Design and Manyfacture,
April 18, 1983; accepted
University
of Hull,
HUN HU6 7RX (Gt. Britain)
July 22. 1983)
The problems facing the engineering designer in the selection and specification of surface coatings are outlined. In particular the benefits and difficulties of the systems concept in coating selection are discussed. A computer-based technique utilizing artificial intelligence principles has been developed to assist the designer in this area. Two programs POLYCOAT and TRIBCOAT are under development which can be interrogated in an interactive response-oriented mode by the nonexpert designer. Knowledge is encoded in a series of rules of the situation+action form which can represent the scientifically inexact factors in coating selection. In effect these “expert systems” emulate the performance of a human consultant in the field, having a capability for decision making in open-ended domains.
1. INTRODUCTION
The benefits of surface coatings in engineering are well known. The majority of engineering failures occur because of surface-initiated effects, e.g. wear, corrosion and fatigue. Coatings offer the potential to prevent failure and often to reduce cost. Until comparatively recently, engineering designers who wished to specify coatings were beset by two problems. Firstly the quality and reproducibility of certain coating techniques left much to be desired. With the advent of improved process control, and particularly since the establishment of ion plating as a commercially viable process, many of these deficiencies have been removed. The second obstacle facing the design engineer, however, has not yet been fully overcome. This relates to the difficulty which he may have in comparing and selecting from the hundreds of available coatings. Although coating design guides and handbooks are available, they tend to be process specific, formatting information in different ways for different coating processes. Indeed it is often virtually impossible to obtain directly comparable data about the relative friction, wear and corrosion performance of particular coatings. The designer would need to be an expert on all competing techniques to make a meaningful comparison. Such levels of knowledge are rare amongst non-specialists. There is, however, scope for making the necessary information available via a computer, which in effect acts as the expert and can operate in an interactive consultation mode. A research programme has been instigated at the University of Hull which aims to introduce such a computer-aided technique into the coating selection process. 0040~6090/83/$3.00
0 Elsevier Sequoia/Printed
in The Netherlands
306 2.
COATING
A. MATTHEWS,
K. G. SWIFT
SELECTION
A useful aid in the problem of information organization and encapsulation is the systems concept, as promulgated most effectively in the tribology field by Czichos’. Johnson2 has outlined a systems rationale for tribological coatings. This identifies ten operating variables (e.g. load and sliding velocity) and 30 system structure determinant processes (e.g. frictional conditions and environment) which must be considered in designing a tribological coating system. There are many problems to be overcome in utilizing such a model. Although a great deal of theoretical and empirical data exist in the tribological field, performance is often influenced markedly by slight changes to the operating mode. Thus the influence of a failure of some part of the operating system must be allowed for. For example, the ingress or generation of particulate matter in a tribosystem can be catastrophic3. Similarly, the addition of even a poor lubricant can transform the performance of most counterfacing materials. Different characteristics are recorded even on apparently similar materials. The hardness of titanium nitride for example can be as low as 1400 HV or over 3000 HV depending on the phases present and the coating morphology4. Of greater concern is the variability in the recorded wear coefficients. As Rabinowicz5 points out, the wear coefficient measured experimentally can sometimes differ by an order of magnitude from the theoretical value. Even if adequate comparative data can be found, the decision on a suitable coating cannot always be a straight hierarchical one, where a number of different techniques and materials are classified according to their suitability for a particular application in straight cost preference order. The decision-making process goes much deeper. Coating selection will probably influence the design of the component, and in turn possibly its method of manufacture. There are therefore often more complex economic factors to take into account. The reliability required and factors relating to the terotechnology or life cycle costs of the component must also be considered within the cost equation. The cost-benefit aspects thus need to be considered. One may feel that a certain functional or economic requirement takes precedence over another; this implies that some weighting factors need to be introduced into the decision process. The systems approach is further complicated by the different properties exhibited by the same material when deposited by different techniques. For example, electroplated chromium can be hard, especially if thick. Vacuum-deposited chromium is usually softer and thus less wear resistant. This arises partly because of the strengthening effect of internal stresses within the electroplated coating. In a similar context, vapour deposition methods can be used to produce particular preferred crystallographic orientations which influence the tribological behaviour of the coatings4. Such variability in properties makes the compilation of a meaningful “morphological box”6 for coatings a quite daunting task. This view is further endorsed when the amount of experimentation which would be required to cover the whole range of surface coatings is considered. Czichos’ contends that it would be necessary to isolate and study independently each of the wear processes which may operate in any given tribosystem. This implies that for any given surface coating selection problem all possible materials pairings must be studied separately under conditions in which only one of the four basic wear mechanisms prevails. This task
TRIBOLOGICAL
COATING
307
SELECTION
would be extremely time consuming and expensive to carry out for the many thousands of materials pairings which might be met. However, some individuals have over many years managed to accumulate experience of the most common materials pairings, and certain couples can immediately be ruled out for certain types of wear. The problem then is how to incorporate expert know-how and unquantified “rules of thumb” into the decision-making process. Our studies have centred on the feasibility of expert systems or intelligent knowledge-based systems (IKBSs) as a means of solving this complex and “openended” problem. These are computing systems which embody organized knowledge concerning some specific area of human expertise. They can be used in an interactive mode by an engineering designer, the computer taking the place of the expert consultant. 3.
KNOWLEDGE-BASED
SYSTEMS
AND THEIR
CHARACTERISTICS
IKBSs or expert systems are the product of recent work by computer scientists researching artificial intelligence. Workers operating in this field are frequently termed “knowledge engineers”. The best-known applications currently developed are in the medical and geological fields’. Medical diagnosis systems have performed the task of an authoritative consultant in a particular area ofmedicine quickly and at low cost. By feeding in symptoms, the non-specialist can obtain a reasoned diagnosis which also takes account of inexact data. The PROSPECTOR program’ can evaluate from geological evidence the likelihood that a particular area will yield a certain ore. The knowledge stored within these programs may previously only have been held by a few experts in the world. The computer can now match their performance; indeed there is some evidence that human intuitive performance is now being surpassed by the reasoning systems incorporated within these programs. Most expert systems are based on a set of rules of the situation-+action form. These rules can have the following general layout: IF:
(antecedent
i)
(antecedent,,) THEN:
(consequent,)
(certainty,)
(consequent,)
(certainty,)
One major difference between such knowledge-based programs is the separation of the expert knowledge (the rules) from the general reasoning mechanism. In addition to this knowledge base the programs incorporate an inference system which manipulates rule certainty and uncertainty from user responses. The programs try to mimic at least to some extent the way in which experts make decisions. The antecedents can be thought of as patterns which can be matched against entries in the data base obtained by questioning the user and consequents as actions that can be performed or conclusions that can be deduced.
308
A. MATTHEWS,
4. COMPUTER-BASED
COATING
K. G. SWIFT
SELECTION
An outline structure of the coating selection program developed at Hull is shown in Fig. 1. The specialized computational aspects of the program, its control strategies, inference system and rule acquisition concepts (learning) will be reported elsewhere. For the purpose of this paper we shall highlight our objectives in developing a tribological coating expert system and emphasize the benefits which this approach may bring to the coating field. Initially a demonstration program POLYCOAT was developed which was designed to evaluate the feasibility of the expert system approach. POLYCOAT is a polymeric coating expert system. Using rules pertaining to operating temperature, abrasion conditions, component flexing, adhesion requirements, colour retention requirement, solvent contact, environmental acidity-alkalinity etc. it recommends the optimum polymeric coating material. The knowledge is encoded as a modular set of rules of the situation--+action form. Each rule represents a piece of knowledge meaningful to the domain. The rule antecedents (operating conditions) are elements of a structure that can be checked against entries in the data base to deduce consequents-conclusions (i.e. the coating processes) if the antecedents match. POLYCOAT currently incorporates 50 such rules. The program investigates its hypotheses (coating materials) and asks the user
PROBLEM
USER
DYNAMIC DATA
BASE
(ON-GOING RECORD)
EXPLANATION rv-
AND
REPORTING SYSTEM
V CONSULTATION CONCLUSION
Fig. 1. General
structure
of the consulting
system.
TRIBOLOGICAL
COATING
309
SELECTION
for information regarding the part design and its environmental and operational requirements. Thus the data base is built up interactively by the design engineer. The confidence in each response is requested on a scale from 0 to 10. As the dialogue continues, if the evidence rules out a particular coating then the user is informed. In its current stage of development, if unable to identify an ideal single dominant solution from the evidence available, the computer will indicate those processes which are likely to be suitable, allocating a suitability rating on the scale &lo. We feel that any consultation system to be used by industry should be able to justify its decisions, not least because engineers would be unlikely to adopt recommendations from computer-based systems without being informed of the decision basis. POLYCOAT can be asked “why?’ a particular line of questioning is being followed by the computer, and it will then display the rules that it is trying to satisfy. Having drawn a conclusion the system will display the rules that it has used to deduce the selected coating. A simple illustrative example of a POLYCOAT dialogue is shown in Fig. 2. A particular benefit of POLYCOAT, and indeed all expert systems, is that the rules occupy their own sector of the program and are therefore separately identifiable, rather than being scattered throughout the program. Updating the rule file is therefore conveniently achieved. In many ways, POLYCOAT is still in its initial stages. It uses data which are readily available and has a comparatively small number of rules in comparison with PROSPECTOR for example which has about 1600 rules. Our current project, the TRIBCOAT expert system, is far more wide ranging than POLYCOAT and will eventually tackle the whole domain of coatings for friction and wear (including tribocorrosion). In spite of the difficulties mentioned earlier for the systems approach, we still feel that this method can be of benefit when coupled with IKBS computer techniques. Following the recommendations implicit in Johnson’s paper2, vacuum deposition processes have been incorporated into TRIBCOAT first of all. These ease the task of system development for several reasons. Please would you tell me if ‘part comes into contact with acetic acid’ is true or false (or why if you wish me to explain my line of reasoning)? f Please tell me your confidence of this I 5 Please would you tell me if ‘environmental temperature < 200 deg C is true or false (or why if you wish me to explain my line of reasoning)? W
am trying to use rule 20 IF NOT, part comes into contact with acetic acid and environmental temperature < 200 deg C and NOT, part requires colour retention and NOT, part is required to flex during service THEN, epoxy ester coating (0.85 confidence) Please would you tell me if.. (The consultation continues with many additional resultant deductions) I
Fig. 2. Sample POLYCOAT
dialogue.
questions
and
310
A. MATTHEWS,
K. G. SWIFT
Firstly coating thickness can be finely controlled (unlike for example those produced by plasma spraying). This is very important, as coating thickness can have a marked effect on tribological performance. Reduced thickness may improve the fatigue strength’ but can increase the friction coefficient’. Also, vacuum deposition methods can offer greater control over surface finish, which influences (for example) the abrasive wear and the frictional ploughing terms. Examples of antecedents currently incorporated into TRIBCOAT are mutual compatibilities (influencing adhesive wear and friction), operating temperatures, environmental conditions and contact pressure. Other antecedents are being added continuously together with more consequents-hypotheses. A systems representation of the factors considered in building the knowledge base can be found in Fig. 3. I
I
COATINGS
I
AND PROCFSSES
I I
1
FRICTION AND
ENVIRONMENTAL
KNOWLEDGE
WEAR
UASE
CONDITIONS
AND
(SYSTEM
THERMAL
RULES)
(Adhesion needs etc.)
A
REOUIREMENTS
properties
Fig. 3. Simplified representation
5. DISCUSSION
etc.)
of knowledge
input.
l
AND CONCLUSIONS
The research program on TRIBCOAT is only in its early stages. Certain difficulties have already been identified. It is not possible to avoid completely the need for experimental data where this does not already exist. The computer approach will, however, in most cases ease this situation by identifying the irrelevant or redundant information which may be called-up by a “manual” systems analysis. It is evident from early results on POLYCOAT that the TRIBCOAT expert system has the potential at least to match the performance of human consultants in the field. We have emphasized in our current research the use of IKBSs for coating selection by the non-expert. The technique can also be used in many other areas of
TRIBOLOGICAL
COATING
311
SELECTION
coating technology, and even by coating specialists to improve their own performance. It is intended, for example, to utilize these methods to assist in the design of coating equipment. Taylor and Ferrari lo have identified a systematic approach to metallization equipment design, and Paton et al.” have discussed a system for the design of electron beam coaters. These papers form a useful base for the development of an equipment design system. A company, in designing coating equipment, will invariably have a basic design package, which may be scaled up or down or modified to suit a particular need. Often full records are not kept of all the design stages taken in specifying each plant. The result is that certain design processes are wastefully repeated each time that a plant order is received. Additionally the company may place too great a reliance on the memory ofcertain key personnel. We can see therefore that another benefit of the expert system approach is that it provides a record of the decision-making route, giving economic and tactical benefits. The main purpose of this paper is to report the existence of the research project into expert systems for tribological coatings. As with any computer-based technique the quality of information which comes out is dictated by the quality of information which is put in. With this in mind we are seeking, at this early stage in the project, to involve as many interested parties as possible. This should ensure that all possible viewpoints are taken into account in the system development. ACKNOWLEDGMENTS
The authors wish to record their considerable gratitude to Professor W. David Morris for his enthusiastic support and encouragement. Thanks are also due to Dr. M. Sabin and Dr. C. H. Morgan for their invaluable assistance with the computational aspects of the project. REFERENCES
1
to the Science and Technology of Friction, 1978. R. L. Johnson, Thin Solid Films. 73 (1980) 235-244. M. B. Peterson and W. 0. Winer (eds.), Wear Confrol Handbook, American Society of Engineers, New York, 1980. A. Matthews and H. A. Sundquist, Proc. Int. Ion Engineering Congr., Kyoto. 1983, Electrical Engineers of Japan, Tokyo, 1983. E. Rabinowicz, in M. B. Peterson and W. 0. Winer (eds.), Wear Confrol Handbook, Society of Mechanical Engineers, New York, 1980, pp. 475-506. F. Zwicky, Morphological Astronomy, Springer, Berlin, 1957. D. Michie, Expert Systems in the Microelectronic Age, Edinburgh University Press, 1979. M. M. Farag, Materials and Process Selection in Engineering, Applied Science, London, J. Hailing, Tribologia, I (1982) 15-29. K. A. Taylor and E. G. Ferrari, Thin SolidFilms, 109(1983) 295. B. E. Paton, N. V. Podola and E. 0. Mischchenko, submitted to Thin Solid Films.
H. Czichos,
Tribology:
A Systems Approach
Lubrication
and Wear, Elsevier, Amsterdam,
2 3 4 5 6 7 8 9 10 11
Mechanical Institute
of
American
Edinburgh, 1979.
109 (1983) 305-3
METALLURGICAL
INTELLIGENT TRIBOLOGICAL A. MATTHEWS Department
(Received
11
AND PROTECTIVE
305
COATINGS
KNOWLEDGE-BASED SYSTEMS COATING SELECTION
FOR
AND K. G. SWIFT
q/Engineering
Design and Manyfacture,
April 18, 1983; accepted
University
of Hull,
HUN HU6 7RX (Gt. Britain)
July 22. 1983)
The problems facing the engineering designer in the selection and specification of surface coatings are outlined. In particular the benefits and difficulties of the systems concept in coating selection are discussed. A computer-based technique utilizing artificial intelligence principles has been developed to assist the designer in this area. Two programs POLYCOAT and TRIBCOAT are under development which can be interrogated in an interactive response-oriented mode by the nonexpert designer. Knowledge is encoded in a series of rules of the situation+action form which can represent the scientifically inexact factors in coating selection. In effect these “expert systems” emulate the performance of a human consultant in the field, having a capability for decision making in open-ended domains.
1. INTRODUCTION
The benefits of surface coatings in engineering are well known. The majority of engineering failures occur because of surface-initiated effects, e.g. wear, corrosion and fatigue. Coatings offer the potential to prevent failure and often to reduce cost. Until comparatively recently, engineering designers who wished to specify coatings were beset by two problems. Firstly the quality and reproducibility of certain coating techniques left much to be desired. With the advent of improved process control, and particularly since the establishment of ion plating as a commercially viable process, many of these deficiencies have been removed. The second obstacle facing the design engineer, however, has not yet been fully overcome. This relates to the difficulty which he may have in comparing and selecting from the hundreds of available coatings. Although coating design guides and handbooks are available, they tend to be process specific, formatting information in different ways for different coating processes. Indeed it is often virtually impossible to obtain directly comparable data about the relative friction, wear and corrosion performance of particular coatings. The designer would need to be an expert on all competing techniques to make a meaningful comparison. Such levels of knowledge are rare amongst non-specialists. There is, however, scope for making the necessary information available via a computer, which in effect acts as the expert and can operate in an interactive consultation mode. A research programme has been instigated at the University of Hull which aims to introduce such a computer-aided technique into the coating selection process. 0040~6090/83/$3.00
0 Elsevier Sequoia/Printed
in The Netherlands
306 2.
COATING
A. MATTHEWS,
K. G. SWIFT
SELECTION
A useful aid in the problem of information organization and encapsulation is the systems concept, as promulgated most effectively in the tribology field by Czichos’. Johnson2 has outlined a systems rationale for tribological coatings. This identifies ten operating variables (e.g. load and sliding velocity) and 30 system structure determinant processes (e.g. frictional conditions and environment) which must be considered in designing a tribological coating system. There are many problems to be overcome in utilizing such a model. Although a great deal of theoretical and empirical data exist in the tribological field, performance is often influenced markedly by slight changes to the operating mode. Thus the influence of a failure of some part of the operating system must be allowed for. For example, the ingress or generation of particulate matter in a tribosystem can be catastrophic3. Similarly, the addition of even a poor lubricant can transform the performance of most counterfacing materials. Different characteristics are recorded even on apparently similar materials. The hardness of titanium nitride for example can be as low as 1400 HV or over 3000 HV depending on the phases present and the coating morphology4. Of greater concern is the variability in the recorded wear coefficients. As Rabinowicz5 points out, the wear coefficient measured experimentally can sometimes differ by an order of magnitude from the theoretical value. Even if adequate comparative data can be found, the decision on a suitable coating cannot always be a straight hierarchical one, where a number of different techniques and materials are classified according to their suitability for a particular application in straight cost preference order. The decision-making process goes much deeper. Coating selection will probably influence the design of the component, and in turn possibly its method of manufacture. There are therefore often more complex economic factors to take into account. The reliability required and factors relating to the terotechnology or life cycle costs of the component must also be considered within the cost equation. The cost-benefit aspects thus need to be considered. One may feel that a certain functional or economic requirement takes precedence over another; this implies that some weighting factors need to be introduced into the decision process. The systems approach is further complicated by the different properties exhibited by the same material when deposited by different techniques. For example, electroplated chromium can be hard, especially if thick. Vacuum-deposited chromium is usually softer and thus less wear resistant. This arises partly because of the strengthening effect of internal stresses within the electroplated coating. In a similar context, vapour deposition methods can be used to produce particular preferred crystallographic orientations which influence the tribological behaviour of the coatings4. Such variability in properties makes the compilation of a meaningful “morphological box”6 for coatings a quite daunting task. This view is further endorsed when the amount of experimentation which would be required to cover the whole range of surface coatings is considered. Czichos’ contends that it would be necessary to isolate and study independently each of the wear processes which may operate in any given tribosystem. This implies that for any given surface coating selection problem all possible materials pairings must be studied separately under conditions in which only one of the four basic wear mechanisms prevails. This task
TRIBOLOGICAL
COATING
307
SELECTION
would be extremely time consuming and expensive to carry out for the many thousands of materials pairings which might be met. However, some individuals have over many years managed to accumulate experience of the most common materials pairings, and certain couples can immediately be ruled out for certain types of wear. The problem then is how to incorporate expert know-how and unquantified “rules of thumb” into the decision-making process. Our studies have centred on the feasibility of expert systems or intelligent knowledge-based systems (IKBSs) as a means of solving this complex and “openended” problem. These are computing systems which embody organized knowledge concerning some specific area of human expertise. They can be used in an interactive mode by an engineering designer, the computer taking the place of the expert consultant. 3.
KNOWLEDGE-BASED
SYSTEMS
AND THEIR
CHARACTERISTICS
IKBSs or expert systems are the product of recent work by computer scientists researching artificial intelligence. Workers operating in this field are frequently termed “knowledge engineers”. The best-known applications currently developed are in the medical and geological fields’. Medical diagnosis systems have performed the task of an authoritative consultant in a particular area ofmedicine quickly and at low cost. By feeding in symptoms, the non-specialist can obtain a reasoned diagnosis which also takes account of inexact data. The PROSPECTOR program’ can evaluate from geological evidence the likelihood that a particular area will yield a certain ore. The knowledge stored within these programs may previously only have been held by a few experts in the world. The computer can now match their performance; indeed there is some evidence that human intuitive performance is now being surpassed by the reasoning systems incorporated within these programs. Most expert systems are based on a set of rules of the situation-+action form. These rules can have the following general layout: IF:
(antecedent
i)
(antecedent,,) THEN:
(consequent,)
(certainty,)
(consequent,)
(certainty,)
One major difference between such knowledge-based programs is the separation of the expert knowledge (the rules) from the general reasoning mechanism. In addition to this knowledge base the programs incorporate an inference system which manipulates rule certainty and uncertainty from user responses. The programs try to mimic at least to some extent the way in which experts make decisions. The antecedents can be thought of as patterns which can be matched against entries in the data base obtained by questioning the user and consequents as actions that can be performed or conclusions that can be deduced.
308
A. MATTHEWS,
4. COMPUTER-BASED
COATING
K. G. SWIFT
SELECTION
An outline structure of the coating selection program developed at Hull is shown in Fig. 1. The specialized computational aspects of the program, its control strategies, inference system and rule acquisition concepts (learning) will be reported elsewhere. For the purpose of this paper we shall highlight our objectives in developing a tribological coating expert system and emphasize the benefits which this approach may bring to the coating field. Initially a demonstration program POLYCOAT was developed which was designed to evaluate the feasibility of the expert system approach. POLYCOAT is a polymeric coating expert system. Using rules pertaining to operating temperature, abrasion conditions, component flexing, adhesion requirements, colour retention requirement, solvent contact, environmental acidity-alkalinity etc. it recommends the optimum polymeric coating material. The knowledge is encoded as a modular set of rules of the situation--+action form. Each rule represents a piece of knowledge meaningful to the domain. The rule antecedents (operating conditions) are elements of a structure that can be checked against entries in the data base to deduce consequents-conclusions (i.e. the coating processes) if the antecedents match. POLYCOAT currently incorporates 50 such rules. The program investigates its hypotheses (coating materials) and asks the user
PROBLEM
USER
DYNAMIC DATA
BASE
(ON-GOING RECORD)
EXPLANATION rv-
AND
REPORTING SYSTEM
V CONSULTATION CONCLUSION
Fig. 1. General
structure
of the consulting
system.
TRIBOLOGICAL
COATING
309
SELECTION
for information regarding the part design and its environmental and operational requirements. Thus the data base is built up interactively by the design engineer. The confidence in each response is requested on a scale from 0 to 10. As the dialogue continues, if the evidence rules out a particular coating then the user is informed. In its current stage of development, if unable to identify an ideal single dominant solution from the evidence available, the computer will indicate those processes which are likely to be suitable, allocating a suitability rating on the scale &lo. We feel that any consultation system to be used by industry should be able to justify its decisions, not least because engineers would be unlikely to adopt recommendations from computer-based systems without being informed of the decision basis. POLYCOAT can be asked “why?’ a particular line of questioning is being followed by the computer, and it will then display the rules that it is trying to satisfy. Having drawn a conclusion the system will display the rules that it has used to deduce the selected coating. A simple illustrative example of a POLYCOAT dialogue is shown in Fig. 2. A particular benefit of POLYCOAT, and indeed all expert systems, is that the rules occupy their own sector of the program and are therefore separately identifiable, rather than being scattered throughout the program. Updating the rule file is therefore conveniently achieved. In many ways, POLYCOAT is still in its initial stages. It uses data which are readily available and has a comparatively small number of rules in comparison with PROSPECTOR for example which has about 1600 rules. Our current project, the TRIBCOAT expert system, is far more wide ranging than POLYCOAT and will eventually tackle the whole domain of coatings for friction and wear (including tribocorrosion). In spite of the difficulties mentioned earlier for the systems approach, we still feel that this method can be of benefit when coupled with IKBS computer techniques. Following the recommendations implicit in Johnson’s paper2, vacuum deposition processes have been incorporated into TRIBCOAT first of all. These ease the task of system development for several reasons. Please would you tell me if ‘part comes into contact with acetic acid’ is true or false (or why if you wish me to explain my line of reasoning)? f Please tell me your confidence of this I 5 Please would you tell me if ‘environmental temperature < 200 deg C is true or false (or why if you wish me to explain my line of reasoning)? W
am trying to use rule 20 IF NOT, part comes into contact with acetic acid and environmental temperature < 200 deg C and NOT, part requires colour retention and NOT, part is required to flex during service THEN, epoxy ester coating (0.85 confidence) Please would you tell me if.. (The consultation continues with many additional resultant deductions) I
Fig. 2. Sample POLYCOAT
dialogue.
questions
and
310
A. MATTHEWS,
K. G. SWIFT
Firstly coating thickness can be finely controlled (unlike for example those produced by plasma spraying). This is very important, as coating thickness can have a marked effect on tribological performance. Reduced thickness may improve the fatigue strength’ but can increase the friction coefficient’. Also, vacuum deposition methods can offer greater control over surface finish, which influences (for example) the abrasive wear and the frictional ploughing terms. Examples of antecedents currently incorporated into TRIBCOAT are mutual compatibilities (influencing adhesive wear and friction), operating temperatures, environmental conditions and contact pressure. Other antecedents are being added continuously together with more consequents-hypotheses. A systems representation of the factors considered in building the knowledge base can be found in Fig. 3. I
I
COATINGS
I
AND PROCFSSES
I I
1
FRICTION AND
ENVIRONMENTAL
KNOWLEDGE
WEAR
UASE
CONDITIONS
AND
(SYSTEM
THERMAL
RULES)
(Adhesion needs etc.)
A
REOUIREMENTS
properties
Fig. 3. Simplified representation
5. DISCUSSION
etc.)
of knowledge
input.
l
AND CONCLUSIONS
The research program on TRIBCOAT is only in its early stages. Certain difficulties have already been identified. It is not possible to avoid completely the need for experimental data where this does not already exist. The computer approach will, however, in most cases ease this situation by identifying the irrelevant or redundant information which may be called-up by a “manual” systems analysis. It is evident from early results on POLYCOAT that the TRIBCOAT expert system has the potential at least to match the performance of human consultants in the field. We have emphasized in our current research the use of IKBSs for coating selection by the non-expert. The technique can also be used in many other areas of
TRIBOLOGICAL
COATING
311
SELECTION
coating technology, and even by coating specialists to improve their own performance. It is intended, for example, to utilize these methods to assist in the design of coating equipment. Taylor and Ferrari lo have identified a systematic approach to metallization equipment design, and Paton et al.” have discussed a system for the design of electron beam coaters. These papers form a useful base for the development of an equipment design system. A company, in designing coating equipment, will invariably have a basic design package, which may be scaled up or down or modified to suit a particular need. Often full records are not kept of all the design stages taken in specifying each plant. The result is that certain design processes are wastefully repeated each time that a plant order is received. Additionally the company may place too great a reliance on the memory ofcertain key personnel. We can see therefore that another benefit of the expert system approach is that it provides a record of the decision-making route, giving economic and tactical benefits. The main purpose of this paper is to report the existence of the research project into expert systems for tribological coatings. As with any computer-based technique the quality of information which comes out is dictated by the quality of information which is put in. With this in mind we are seeking, at this early stage in the project, to involve as many interested parties as possible. This should ensure that all possible viewpoints are taken into account in the system development. ACKNOWLEDGMENTS
The authors wish to record their considerable gratitude to Professor W. David Morris for his enthusiastic support and encouragement. Thanks are also due to Dr. M. Sabin and Dr. C. H. Morgan for their invaluable assistance with the computational aspects of the project. REFERENCES
1
to the Science and Technology of Friction, 1978. R. L. Johnson, Thin Solid Films. 73 (1980) 235-244. M. B. Peterson and W. 0. Winer (eds.), Wear Confrol Handbook, American Society of Engineers, New York, 1980. A. Matthews and H. A. Sundquist, Proc. Int. Ion Engineering Congr., Kyoto. 1983, Electrical Engineers of Japan, Tokyo, 1983. E. Rabinowicz, in M. B. Peterson and W. 0. Winer (eds.), Wear Confrol Handbook, Society of Mechanical Engineers, New York, 1980, pp. 475-506. F. Zwicky, Morphological Astronomy, Springer, Berlin, 1957. D. Michie, Expert Systems in the Microelectronic Age, Edinburgh University Press, 1979. M. M. Farag, Materials and Process Selection in Engineering, Applied Science, London, J. Hailing, Tribologia, I (1982) 15-29. K. A. Taylor and E. G. Ferrari, Thin SolidFilms, 109(1983) 295. B. E. Paton, N. V. Podola and E. 0. Mischchenko, submitted to Thin Solid Films.
H. Czichos,
Tribology:
A Systems Approach
Lubrication
and Wear, Elsevier, Amsterdam,
2 3 4 5 6 7 8 9 10 11
Mechanical Institute
of
American
Edinburgh, 1979.