Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys

Kaukler, William F.

Workman, Gary L.

English

NASA Technical Reports Server

N90-27283
ARTIFICIAL INTELLIGENCE IN THE MATERIALS
PROCESSING LABORATORY
Gary L. Workman and William F. Kaukler
University of Alabama in Huntsville
Huntsville, AL 35899
INTRODUCTION
Materials science and engineering provides a vast arena for applications of artificial
intelligence. Advanced materials research is an area in which challenging requirements confront
the researcher, from the drawing board through production and into service. Advanced techniques
results in the development of new materials for specialized applications. Hand-in-hand with these
new materials axe also requirements for state-of-the-art inspection methods to determine the
integrity or fitness for service of structures fabricated from these materials.
The many facets of materials science and engineering form a complex mixture of interests
in compositional variances, processing parameters and service environments. All need to be
considered in designing and implementing an advanced material for a particular function. It is
anticipated that artificial intelligence can provide many benefits in sorting out some of the
complex relationships which help to produce ideal materials for extreme conditions. Sorting out
compositions from process parameters is complicated and normally requires expertise from many
sources. These sources can often take the form of humans who have vast experience in a specific
area and thereby are domain experts in a very focussed area. This knowledge may be accessible
from either the persons themselves or from the published literature. On the other hand, with the
rapidly evolving materials technology in today's society, one often must include current results
from actual or simulated experiments to obtain the knowledge required to attain specific goals.
Selection of the expert system implementation or platform most suited to meeting required
goals also presents interesting challenges in the materials world, because the knowledge or
awareness of artificial intelligence is quite new and only within the last few years has any real
effort been made to incorporate new AI technologies into the realm of new materials
technologies, t'_
Two problems of current interest to the Materials Processing Laboratory at UAH are an
expert system to assist in eddy current inspection of graphite epoxy components for aerospace
and an expert system to assist in the design of superalloys for high temperature applications. Each
project requires a different approach to reach the def'med goals. The first project has been in
existence several months now, while the second will be undertaken during Spring of 1990. Hence
this paper will describe results to date for the eddy current analysis, but only the original
concepts and approaches considered will be given for the expert system to design superaUoys.
EDDY CURRENT INSPECTION OF GRAPHITE EPOXY FILAMENT COMPONENTS
Composite materials have many beneficial characteristics which enhance their role in
today's aerospace systems. Lightweight, but still very strong, even at high temperatures, graphite
epoxy filaments have been fabricated to replace structures traditionally constructed of metals.
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https://ntrs.nasa.gov/search.jsp?R=19900017967 2020-03-19T21:14:55+00:00Z
Most activity has occurred in the airframe and missile industries, with some interest currently
being developed in Space structures. A major component of the Space Station is the truss
structure, which is still being proposed to be made of graphite epoxy composites. Several
problems still exist in selecting graphite epoxy for an aerospace structure. No accurate structural
models based on traditional fracture mechanics can predict reliabilities for these structral
members in the presence of flaws. Determining flaws also presents a major difficulty. Flaws can
arise from fabrication errors, impact damage during assembly, and obviously in Space, impact
damage and erosion from atomic oxygen. A major need exists in being able to measure the
integrity of the graphite-epoxy structures during fabrication and in Space. Many research groups
are involved in developing NDE techniques to detect flaws in graphite epoxy structures. Primary
interest is to not only to determine that there is a flaw, but more importantly, the size and nature
of the flaw. This project seeks to develop the capability to utilize simple heuristics types of logic
to determine the flaws in real time, as compared to the more time consuming methods based
upon statistical and computationally intensive methods. _
Eddy current inspection is a nondestructive testing technique which utilizes a high
frequency electromagnetic field to induce eddy currents in the material under test. The magnitude
of the eddy currents induced in the materials provides a response of the material which should
indicate a measure of the integrity of the material. Since graphite fibers have a measurable
conductivity, eddy current methods can be applied for inspection purposes. Unfortunately, due
to the very low conductivity, the signals are weak. Several methods have been developed to
increase the signal-to-noise ratio, including signal processing schemes and design of special eddy
current transducers. A horseshoe or E-probe design has advantages in that it can concentrate more
magnetic flux within the fiber, in addition to providing directional selectivity. Finite element
models of the two types are shown in Figure 1, where a.) is the normal pancake probe and b.)
is a horseshoe or E-probe. 79
A number of defects exist for composite materials, as shown in Table 1.The goal of the
expert system is to assist in the determination of the nature, size and location of the flaws using
knowledge which relates changes in resistance and reactance of the component being tested to
identify a flaw type and depth. Knowledge is incorporated into the expert system through
heuristics gained by measurements on known flaws and through finite element calculations on
simulated defects. The location and size of the flaw will be determined to a large extent by the
scanning parameters.
The eddy current inspection facility is a robot-scanned facility using an Indellidex 550
Robot The scanning manipulator has 5 degrees of freedom and uses a programmable computer
controller for trajectory and task programming. At this time no off-line programming tools exist.
The system supervisor and the platform for the expert system is a Macintosh II using a Maclvory
engine. The robotic cell layout is shown in Figure 2. A major part of the problem, in addition
to the expert system development, is the integration of the components making up the cell into
a flexible and productive inspection facility. Developing off-line programming tools for the
facility will become a major goal in later work.
The overall expert system architecture is shown in Figure 3. As mentioned earlier, the
knowledge base consists of two types, computed and measured. This type becomes the principal
6O
form of knowledge in domains where few experts reside, but the availability of knowledge
applicatble to a specific domain required for real-time processing of signals will most often take
the form of a measured quantity.
The Macintosh II platform was chosen for its enhanced user interface and graphical
environment. The Maclvory board set represents a state-of-the-art symbolics processor residing
inside the Macintosh computer. The two enviroments are accessible through program calls, but
do not run on top of one another. The rationale for choosing this platform for the expert system
was to establish the capability of the system to support the various tasks required in taking eddy
current data, processing computationally and symbolically to determine flaw sizes and locations,
and then to generate three-dimensional graphic representations of the structure and the flaws. The
over-all task description is very robust and represents a good test of the capabilities of the
Maclvory envirornent. In any case, the computer controller for the robot can perform as the robot
cell controller, allowing for the Macintosh to function solely as a data acquisition and analysis
module. Both cases will be tested.
Expert System for the Design of Superalloys
This section presents some of the concepts which evolved in developing a proposal to
create such an expert system. The primary rationale behind the choice of an expert systems to
be applied to the problem is that there is a lot of experimental data existing in the literature
which presents a very complicated, and often ambiguous description of the essential elements or
processing required to prepare a superalloy with specfic attributes. For example, in the proposed
study, in order to basically weed out what are the most important parameters for stability to
hydrogen environment, the literature repeatedly contradicts itself, i.e. there is a conflict between
the experts.
Figure 4 shows the original concept for an expert system to assist in the design of
superalloy system.ts. To implement such a robust system, will obviously take several man-years
of effort. However, by developing the overall concept in modules which can provide a useful
benefits for functions such as stability in hydrogen environments, the capabilities are appreciated.
Rapid prototyping only one of the modules at a time will allow the system to evolve in
conjunction with the ability to generate experimental data also.
Expertise for designing superalloys exists in a few researchers and within organizations
desiring proprietary handling of data. Consequently the knowledge required for this effort is not
only scattered, but also, in some cases, of such proprietary nature that one company will not
share their knowledge with another organization. Computations on phase formations and kinetics
of metallurgical reactions for particular compositions also are required for microstructural
predictions. Hence the problem solving approach consists of heuristics, data from established
databases, and computations as required. Choosing an expert system shell to prototype the system
was difficult.
Several expert systems shells were considered for this project. Among all the choices
available, Nexpert Object was chosen because of its capabilities. Both forward and backward
chaining are allowed, program calls to computational or other types of procedures are allowed
61
and a very easy to usehumaninterfaceallows for simplerule constructionand inferencing.
Dynamicinferencingthroughits non-monotonicreasoningcapabilityareessentialin orderto deal
with thecomplexitiesof superalloys.
The projectwill beginin January,1990with thegoal to develop a prototype system to
design a superalloy system with optimal stability against hydrogen embrittlement within six
months. The results will be interesting. Successful completion of the preliminary goals will
obviously provide a foundation upon which to add other modules in order to build up the
capabilities of the system. Also we anticipate that other expert systems for advanced materials
design will be attempted in the near future.
ACKNOWLEDGEMENTS
This work was performed under contract from Marshall Space Flight Center on NAS8-
36955. The eddy current inspection activity has been performed by graduate students, Mr.
Morgan Wang and Mr. Sung Lee at UAH and Craig Bryson in the NDE Laboratory at Marshall
Space Flight Center.
Bibliography
1. D.E. Marinaro and J.W. Morris, Jr., "Research Towards an Expert System for Materials
Design", Artificial Intelligence Applications in Materials Science, ASM, Metal Park, OH, 1989,
pp 49-78
2. I. Hulthage, M. Przystupa, M.L. Farinacci, and M.D. Rychener, "The Metallurgical Database
of ALADIN - An Alloy Design System", Artificial Intelligence Applications in Materials Science,
ASM, Metal Park, OH, 1989, pp105-122
3. W.A. Boag Jr, D.B. Reiser, D.O.Sprowls, and M.D. Rychener, "Cordial - A Knowledge-Based
System for th Diagnosis of Stress Corroison Behavior in High Strength Alloys", Artificial
Intelligence Applications in Materials Science, ASM, Metal Park, OH, 1989, pp123-145
4. K.C. Maddux and S.K. Jain, "Manufacturing Process Simulation: A Building Block in an
Artificial Intelligence System for the Manufacturing Engineer", Artificial Intelligence
Applications in Materials Science, ASM, Metal Park, OH, 1989, ppl3 - 34.
5. P.G.Doctor, T.P. Harrington, T.J. Davis, C.J. Morris, and D.W. Fraley, " Pattern-Recognition
Methods for Classifying and sizing flaws using eddy Current Data", pp464-483
6. L. Upda and W. Lord, "An AI Approach to the Eddy Current Defect Characaterization
Problem", QNDE 6, 1986, pp 900 - 906.
7. S.N. Vernon, "Probe Properties Affecting the Edy Current NDI of Grpahite Epoxy", QNDE,
vol.5, pp 1113 - 1123.
8. S.N. Vernon and P.M. Garnmell,"Eddy Current Inspection of Broken Fiber Flaws in Non-
62
metallic Fiber Composites", QNDE 4, 1984, pp. 1229 - 1237.
9. M.J. Donachie, Jr., "Introduction to Superallo.ys", Superalloys Source Book, published by
ASM, Metals Park, OH, 1984, pp 3-15.
TABLE 1
DEFECTS IN COMPOSITE MATERIALS
FABRICATION DEFECTS
VOID CONTENT
STATE OF RESIN CURE
FIBER/MATRIX INTERFACE
FOREIGN INCLUSIONS
TRANSLAMINAR CRACKS
DELAMINATIONS
FIBER ALIGNMENT
SERVICE DEFECTS
MOISTURE INGRESS
ULTRAVIOLET DEGRADATION
TEMPERATURE EXTREMES
MATRIX CRACKING
DELAMINATION
FIBER/MATRIX DEBONDING
FIBER BREAKAGE
IMPACT DAMAGE
63
FIGURE 1. Finite element models for a.) pancake probe and b.) E-probe for 5 megahertz
electromagnetic coupling to graphite fiber. The coil is wrapped around the center bobbin in both
cases. Note that the pancake probe produces a field 360 ° around the centerline, while the E-
probe produces a flux across the direction of the fiber.
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