Expert Systems with Applications 38 (2011) 10484–10492
Contents lists available at ScienceDirect
Expert Systems with Applications
journal homepage: www.elsevier.com/locate/eswa
Ontological functional modeling of technology for reusability
Janghyeok Yoon a, Joohyung Lim a, Sungchul Choi a, Kwangsoo Kim a,⇑, Cheol-Han Kim b
a
b
Department of Industrial and Management Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Namgu, Pohang 790-784, Republic of Korea
Department of IT Management Engineering, Deajeon University, Daejeon, Republic of Korea
a r t i c l e
i n f o
Keywords:
Functional models
Ontological functional modeling
Technology reuse
a b s t r a c t
Technology reuse is important in that it dramatically reduces lead-time, efforts and costs in R&D activities coping with market drivers. In this perspective, understanding technologies from a functional viewpoint helps us search reusable technologies from various technology domains and reuse them. Function is
the concept to abstract intention and ways of a technology from a technological standpoint, and reusable
function as the core function is representative of the technology. Functional model which formalizes function is represented as an affecting action and one or more affected objects. If technologies and their reusable functional models are stored together in a knowledge base, it is possible to develop a foundation of
the environment that allows us to find out reusable technologies by function-based search without
regard to technology domains. In this environment, therefore, identifying reusable functionalities from
a technology and representing their meanings clearly are the basis to stimulate technology reuse. As a
part of constructing the environment for technology reuse, this paper suggests an ontological functional
modeling methodology of technology which is composed of a procedure for extracting reusable functionalities and a WordNet-based representation to define ontological functional models.
Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction
Functional specification defines what the functionalities will be,
but not yet how these functionalities will be implemented. According to Altshuller (1984) and Mann (2002), keywords- and categories- based search provides us with the possible new solutions
restricted within specific technology domains, but function-based
search offers a useful starting point to first identifying and then
finding out more about what alternatives there may be. That is,
function-based search is a very effective way of finding out and
reusing technologies stripping away the boundaries that exist between different industries and scientific disciplines (Mann, 2002).
Currently there are many definitions of function (Kitamura,
Kashiwase, Fuse, & Mizoguchi, 2004). However, function in this paper is the concept to abstract intention and ways of a technology
from a technological standpoint, and reusable function as the core
function is representative of the technology. Functional model
which formalizes function is represented as an affecting action
and one or more affected objects. If technologies and their reusable
functional models are stored together in a knowledge base, it is
possible to develop a foundation of the environment that allows
⇑ Corresponding author. Tel.: +82 54 279 2195, fax: +82 54 279 5998.
E-mail addresses: janghyoon@postech.ac.kr (J. Yoon), yanzi@postech.ac.kr (J.
Lim), blissray@postech.ac.kr (S. Choi), kskim@postech.ac.kr (K. Kim), chkim@dju.kr
(C.-H. Kim).
0957-4174/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.eswa.2011.02.090
us to find out reusable technologies by function-based search without regard to technology domains.
As shown in Fig. 1, from a functional viewpoint a technology
can be abstracted by one or more reusable functional models. Conversely, if we understand the technological functionalities that are
required to develop a technology, we can search the alternative
technologies that deliver the functionalities and have already
developed. For example, in Fig. 1 it is possible to reuse the technologies that deliver the functional model ‘filter gas’. Engineers can
find out the technology TA and TE by the function-based search.
After reviewing how these alternative technologies deliver the
functional model, they can adopt one of the alternative technologies which provide a solution to the problem they are facing. Finally they reuse the way of the selected technology directly or after
proper modifications. This function-based search allows us to find
out reusable technologies domain-independently and supports
technology reuse effectively. Technology reuse helps reduce leadtime, efforts and costs to cope with market drivers (Petrick &
Echols, 2004). Therefore issues about identifying and representing
the reusable functionalities of technology are important to construct the environment for technology reuse.
Most researches on functional modeling have mainly focused
on the functional details description of mechanical systems and
the formalized terms for functional models. Researches on functional structure are not adequate for identifying and representing
reusable functionalities from a technology because their objectives
are to describe hierarchical functional details of mechanical
J. Yoon et al. / Expert Systems with Applications 38 (2011) 10484–10492
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Fig. 1. Functional viewpoint of technologies and function-based technology search.
systems (Kitamura et al., 2004; Stone & Wood, 2000; Stone, Wood,
& Crawford, 2000). Many researches about how to represent functional models arrange the terms used in functional modeling
(Hirtz, Stone, McAdams, Szykman, & Wood, 2002; Hundal, 1990;
Pahl & Beitz, 1984) but it is difficult for their approaches to support
the function-based search effectively because they lack in how to
represent the semantic meanings of the terms explicitly. To solve
these problems, this paper suggests an ontological functional modeling methodology composed of a functional modeling procedure
and an ontological functional model representation.
First, the functional modeling procedure which uses the FAST
Diagram in Value Engineering (Miles, 1972) is a procedure to extract reusable functions from a technology. For example, in Fig. 1
it is needed to address how to derive the reusable functions such
as ‘filter gas’ and ‘absorb gas from liquid–gas’ from the technology
TA. Employed as a technique to analyze functional relations of a
technology in this paper, the FAST Diagram is being used widely,
and helps functional modelers structurize a technology and extract
reusable functions from it.
Second, the functional model representation to explicitly define
the meaning of functional models adopts an ontological approach.
Consider the functional model ‘clear particle’ in Fig. 1. Because in
the functional model the action ‘clear’ itself cannot explain
whether its meaning is ‘rid of obstructions’ or ‘make bright, light,
or translucent’, it is needed to represent its semantic meaning
explicitly. An ontology is an explicit specification of a conceptualization (Gruber, 1995). The ontology includes definitions of concepts and an indication of how concepts are inter-related which
collectively impose a structure on the domain and constrain the
possible interpretations of terms (Uschold, 1998). The ontology is
used to improve communication between either humans or computers (Uschold & Jasper, 1999). Therefore ontological functional
models can explicitly represent intention and ways of a technology. Additionally they make the function-based search effective
and accurate owing to their machine processability.
This paper is organized as follows. In Section 2, related works
are discussed. Section 3 suggests an ontological functional modeling methodology that consists of a functional modeling procedure
and an ontological functional model representation. An example of
functional modeling of technology corresponding to the proposed
methodology is illustrated through Section 3. In Section 4, a prototype software for the function-based search is introduced. Finally
Section 5 concludes the paper.
2. Related works
Researches on functional models have been conducted in
many areas such as Value Engineering, Engineering Design, and
Functional Representations. Their interests are in causal-root relation analysis between functions (Miles, 1972), standardized term
definition for functional model representation (Hirtz et al., 2002;
Hundal, 1990; Pahl & Beitz, 1984), hierarchical functional structure of mechanical systems (Kitamura et al., 2004; Stone & Wood,
2000; Stone et al., 2000), ontology-based engineering knowledge
sharing (Kitamura & Mizoguchi, 2003; Kitamura & Mizoguchi,
2004; Kitamura et al., 2004), application in the computer aided
design (Zahng, Tor, & Brinton, 2002), etc. Among these researches,
Stone et al. (2000) suggests a heuristic method to figure out
mechanical components with modularity by diagramming the
function chain of mechanical systems. But their work is not adequate for identifying and representing the reusable functionalities
from a technology which are available in other technology domains because it focuses only on describing functional structure
and identifying modular components of mechanical products. Hirtz, Stone, McAdams, Szykman, and Wood (2002) categorize possible terms into three-level class types to add formality to
functionality representation. The set of terms for functionality
representation is called a functional basis (Hirtz et al., 2002).
The functional basis by them is believed to be the most advanced
since it incorporates the previous efforts by Altshuller (1984),
Hundal (1990) and Pahl and Beitz (1984). But their work has limitations in that the terms constituting the functional basis is limited within mechanical systems (Chulvi & Rosario, 2009) and they
do not sufficiently provide the explicit meanings of terms. Despite
these limitations, the term classification scheme by them is
remarkable. Therefore this paper adopts the term classification
scheme in order to suggest how to define a domain-specific functional basis in Section 3.2. Kitamura et al. (2004) and Kitamura
and Mizoguchi (2003) suggest an ontology-based hierarchical
functional structure representation of mechanical systems to
share engineering knowledge effectively between engineers. The
researches define a functional concept ontology and a device
ontology using OWL, an XML-based ontology definition language.
The concepts defined in these ontologies constitute functional
models. Although their researches seem similar to this paper in
the aspect of using ontology, their works are not adequate for
how to extract reusable functionalities from a general technology
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because they focus on describing and searching hierarchical functional structure of mechanical systems.
Mann (2002) takes a function-based approach to technology reuse. In his book ‘Hands-On Systematic Innovation’, he arranges
physical, chemical and biological effects by function, each of which
acts as an inspiration to solve the technological problems that
engineers face. Through the website of the CREAX function database that is based on his idea, engineers can search various scientific effects to solve specific problems using functions generated
from 46 actions and 4 objects (solid, liquid, gas, field) (CREAX,
2009). A distinctive feature of the CREAX function database is that
an effect does not always belong to only one function. Namely one
or more functions can be derived from an effect according to the
functional viewpoint (Mann, 2002). For example, the effect
‘absorption effect’ belongs to the function ‘deposit solid’, ‘extract liquid’ and ‘move liquid’. The functional modeling procedure introduced in Section 3.1 of this paper adopts this feature. But the
number of the objects suggested by Mann is only 4, and the actions
are outdated because they are originated from the patents until
1984. Therefore it is insufficient to describe intention and ways
of the evolving present-day technologies (Chulvi & Rosario,
2009). Additionally Mann does not consider how to extract reusable functionalities from a technology and represent their semantic
meanings. That is because his interest is on the basic effects which
people can intuitively derive reusable functionalities from. This paper has a differentiation from the Mann’s work in that it deals with
how to extract reusable functionalities from various technologies
not restricted to the basic effects and how to represent the functionalities formally and semantically.
In addition to the above works, researches about engineering
reuse by Antelme, Moultrie, and Probert (2000) and Dahmus,
Gonzalez-Zugasti, and Otto (2001) are inadequate for identifying
and representing reusable functionalities because they focus on
product platform, design, standardized parts and product family.
3. Ontological functional modeling of technology
As shown in Fig. 2, the final objective of this paper is to suggest
how to define reusable ontological functional models from a technology. To do this, first a functional modeling procedure as a
preprocessing procedure for ontological functional model representation is suggested to derive reusable functions from a technology. Next a method to represent them into ontological functional
models follows. Therefore Section 3.1 suggests a functional modeling procedure using the FAST Diagram in Value Engineering. Section 3.2 addresses how to define ontological functional models
using the approach of WordNet (Miller, 1995).
The patent US-5031156 ‘method and apparatus for detecting
and counting articles’ which has been registered in the United
States Patents and Trademark Office is introduced as an example
through this chapter. As shown in Fig. 3, the patent is an invention
to count the number of articles moving on a conveyer belt in the
magazine, newspaper or publishing companies. Using an elastic
stick, the previous method counted the number of articles grazing
by it. This method had to replace the worn stick periodically with a
new one because the worn stick could cause a problem in article
counting. Therefore, issues about cost by stick replacement and
accuracy by stick wear had arisen. The new method makes the articles vibrate by blowing compressed air, and then sound by the
vibration is used to count the number of articles. Owing to the
new method, stick replacement became unnecessary and accuracy
of counting articles was highly improved.
3.1. A functional modeling procedure for identifying reusable functions
Fig. 4 shows a procedure suggested in this paper to derive reusable functions from a technology. The 4-steps, ‘gather key sentences from a technology’, ‘list functions’, ‘make a FAST Diagram’
and ‘select reusable functions’, constitute the procedure. During
the procedure, 3 or more domain experts participate to adopt the
feature that various reusable functions can be derived from a technology according to the functional viewpoint (Mann, 2002). The
suggested procedure uses the FAST Diagram as a tool for identifying reusable functions.
The FAST (Function Analysis System Technique) Diagram suggested by Miles (Miles, 1972) is a diagram to structurize interrelations between cause and effect functions rather than to simply
describe hierarchical functional details composed of whole and
part functions, and is called the Function Diagram. Relating functions according to the ‘How-Why’ logic, it helps people figure out
the functions that a system requires and understand relations between functions more effectively. Differently from identifying
modular components from mechanical systems by diagramming
the function chain (Stone et al., 2000), the objective of the functional modeling procedure in this paper is to identify the reusable
functions which are available in other technology domains. The
FAST Diagram is adopted because it is widely accepted in many
areas and relatively easy to use. In addition, with key sentences
of a technology and their functional relations, the FAST Diagram helps understand the core of a technology (Yoon, Choi, Kim,
Kim, & Seo, 2010). Fig. 4 shows the steps in the functional modeling
procedure together with an example of the above stated patent.
Step1 (Gather key sentences from a technology): Step1 is to
gather key sentences from a technology. Because functions representative of a technology, or reusable functions, are what
abstracts a technology, the gathered sentences have to be about
the core intention, inventive principles, ways rather than technological details. For example, details of a circuit design are not
in the scope of key sentence gathering. The key sentences in
Fig. 4 are ‘articles, moving along a delivery path, are counted
by directing a stream of pressured air. . .’, ‘sensors arranged
Fig. 2. 2-Steps to define ontological functional models.
J. Yoon et al. / Expert Systems with Applications 38 (2011) 10484–10492
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Fig. 3. The Patent US-5031156.
Fig. 4. A functional modeling procedure.
about the air stream detect the acoustic signal which varies
with. . .’, the detected acoustic signal is divided. . .’, ‘averaged
to reduce the effect of noise. . .’, ‘to generate count signal. . .’,
etc. At this step, that 3 or more domain experts individually perform from Step1 to Step4 is required. That is because reusable
functions are finally identified by the discussion and expert voting based on individual functional modeling results.
Step2 (List functions): Step2 is to list the functions generated
from the gathered key sentences. Terms and format for the
function representation are not restricted. But they need to
meet the form of a natural language which has at least one
action and one or more objects. The exemplary functions in
Fig. 4 are ‘count the number of articles’, ‘vibrate articles to make
sound’, ‘directing a stream of pressured air’, ‘the detected acoustic signal is divided into frequency ranges’, ‘average to reduce
the effect of noise’, ‘generate count signal’, etc.
Step3 (Make a FAST Diagram): Step3 is to make a FAST Diagram to analyze causal relations between the listed functions.
There is the description about modeling notation and diagramming procedure for the FAST Diagram (Miles, 1972). In the FAST
Diagram, logical relations between intention and ways represented as functions are structurized effectively. Functions about
‘How’ are on the right side and functions about ‘Why’ are on the
left side. Therefore, it is easy to understand the technology at a
glance. In the FAST Diagram, functions not main in the technology do not have to be analyzed further. For example, the function ‘rotate roller’ and ‘put article on a conveyer’ in Fig. 4 belong
to the listed functions in Step2 but subordinate functions of
them are not a matter of concern.
Step4 (Select reusable functions): Step4 is to select reusable
functions from the functional relation analysis in Step3. In the
example of Fig. 4, the reusable functions that domain experts
finalized through discussion and expert voting are ‘recognize
counting signal’ and ‘vibrate articles’. To check reusability of
each function, followings are considered.
1) The function is reusable in other technology domains.
2) The function is the core in the technology.
3) The function is independent and modular.
4) The function represents the engineering intention and
ways from a technological standpoint.
3.2. Ontological functional model representation
A functional basis is a set of verbs and nouns used to formalize
functionalities (Hirtz et al., 2002). The functional basis by Hirtz
et al. (2002) is currently believed to be the most advanced and
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Fig. 5. Functional basis by Hirtz et al. (2002).
has the structure of primary, secondary and tertiary classes as
shown in Fig. 5. The left table of Fig. 5 is a set of verbs, which are
called actions in this paper, and the right table is a set of nouns,
which are called objects. Terms that have the similar meaning to
each class name belong to correspondents. However, a limitation
that its terms are limited to mechanical systems was pointed out
(Chulvi & Rosario, 2009). In addition, there is not the semantic representation of terms in the functional basis. Consequently with the
functional basis, it is difficult to represent and understand the explicit and accurate meaning of the functional models identified in
Section 3.1.
In order to solve the above problems, this paper suggests how to
define a functional basis and make the meaning of functional models clear by adopting the approach of WordNet. The WordNet suggested by Cognitive Science Laboratory of Princeton University
(2009) is an ontology database that defines English terms. The
WordNet defines the meaning of terms by establishing various
semantic relations between terms (Miller, 1995). As shown in (A)
of Fig. 6, it defines English nouns, verbs, adjectives, and adverbs
and links them through the semantic relations that determine
word definitions. (B) of Fig. 6 shows the semantic relations in
WordNet, such as a similar relation, an opposite relation, a subor-
Fig. 6. An example of WordNet search and the semantic relations in the WordNet (Miller, 1995).
J. Yoon et al. / Expert Systems with Applications 38 (2011) 10484–10492
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Fig. 7. Functional basis definition and ontological functional model representation.
dinate relation, and so on. For example, the 4th sense of the term
‘absorb’ has a similar relation to the 13th sense of ‘take in’ and
the 11th sense of ‘take up’, and has an opposite relation with the
2nd sense of ‘emit’. Through these semantic relations, the WordNet
forms a semantic network of terms. Therefore, the WordNet is adequate for defining terms of functional models because it focuses on
defining and understanding the semantic meanings of words.
Fig. 7 shows how to define a functional basis and how to represent the semantic meanings of functional models. First, the starting
point for a functional basis is to define a functional ontology. The
functional ontology is composed of the WordNet and the domain
ontology. Because most of the terms used for functional models
representation are general English terms, the WordNet is adequate
as an ontology for general English terms. The domain ontology is
defined for the domain-specific terms according to the above stated approach of WordNet by domain experts. Developing a functional basis is completed by choosing the required terms from
the functional ontology and arranging them with the term classification scheme by Hirtz et al. (2002). To develop a functional basis
like this is needed to guarantee the consistency of functional model
representation. Next, functional models that are in the form of
‘verb-noun’ or ‘verb-noun1-preposition-noun2’ are represented
with the terms in the developed functional basis. Then, the functional models naturally imply the semantic meanings because their
terms are in the functional basis where each term refers to a sense
of a word in the functional ontology based on the approach of
WordNet.
Consider the reusable functions identified by the functional
modeling procedure in Section 3.1. As shown in Fig. 8, the function
‘recognize counting signal’ and ‘vibrate articles’ can be converted
into the formalized function ‘recognize oscillatory signal’ and ‘vibrate plate’ respectively. To formalize the functions is based on a
domain-specifically defined functional basis. Then, each term of
the formalized functions, or functional models, refers to the functional ontology. Ontological representations of the functional
models are ‘recognize(WordNet2.1-recognize-verb-3) oscillatory
signal(Mustard1.0-oscillatory signal-noun-1)’ and ‘vibrate(WordNet2.1-vibrate-verb-1) plate(WordNet2.1-plate-noun-1)’. The reference ‘WordNet2.1-recognize-verb-3’ of the term ‘recognize’ is
the 3rd sense of the verb ‘recognize’ in the WordNet. The reference
‘Mustard1.0-oscillatory signal-noun-1’ of the term ‘oscillatory signal’ is the 1st sense of the noun ‘oscillatory signal’ in the domain
ontology ‘Mustard’. Likewise, the reference ‘WordNet2.1-vibrateverb-1’ of the term ‘vibrate’ is the 1st sense of the verb ‘vibrate’
Fig. 8. An example of ontological functional model representation.
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Fig. 9. Snapshots of a prototype system.
J. Yoon et al. / Expert Systems with Applications 38 (2011) 10484–10492
in the WordNet. The reference ‘WordNet2.1-plate-noun-1’ of the
term ‘plate’ is the 1st sense of the noun ‘plate’ in the WordNet.
In the aspect of using ontology, the functional model representation of this paper seems to be similar to the approach of
Kitamura et al. (2004) and Kitamura and Mizoguchi (2003). But
this paper has a differentiation in that the functional model representation is not restricted within mechanical systems and based on
the approach of WordNet. The WordNet which this paper uses is
currently a widely-used and well-defined ontology database that
defines the semantic meaning of English terms. Therefore it is possible to cut down the cost and time to develop an ontology for
general English terms. In addition, semantic relations defined by
the approach of WordNet effectively can support various
function-based searches for technology reuse such as similar,
opposite, subordinate functional model search, etc.
4. Implementation of a prototype system
If ontological functional models derived by the ontological functional modeling methodology in Section 3 are stored together with
their technology documents in a knowledge base, then the
function-based technology search is possible. This chapter introduces a .NET-based prototype system to define ontological functional models, store technologies and their functional models in a
functional knowledge base, and support the function-based search.
(A) of Fig. 9 is a functional basis based on a WordNet-based
functional ontology and the term classification scheme by Hirtz
et al. (2002). Users utilize the functional basis to formalize the
reusable functions derived by the functional modeling procedure
in Section 3.1. In (A) of Fig. 9, the ontological functional model ‘ABSORB GAS FROM GAS-GAS’ is defined. Because each term in the
functional basis has the semantic reference to the functional ontology, the defined functional model has a clear and accurate meaning. (B) of Fig. 9 shows details of the functional model referring
to a sense of a term in the functional ontology. In the example,
the ontological functional model is ‘ABSORB(WORDNET2.1-ABSORB-VERB-4) GAS(WORDNET2.1-GAS-NOUN-1) FROM GASGAS(MUSTARD1.0-GAS GAS-NOUN-1)’. (C) of Fig. 9 shows a graphical user interface to make relations between technologies and
ontological functional models. These relations imply that a functional model can be delivered by various technologies and a technology can be abstracted by one or more functional models. If
these technologies and their ontological functional models are
stored together in a knowledge base, the function-based technology search is possible as shown in (D) of Fig. 9. Because the functional ontology based on the approach of WordNet defines
semantic relations such as a similar relation, an opposite relation,
a subordinate relation, a part relation and a manner relation, terms
of functional models as the search condition can be used to search
the reusable technologies that deliver the same functional models,
similar functional models, etc. The software, as a prototype system,
supports to search technologies with the semantically same functional models to the functional model in the search condition.
For example, in the WordNet, ‘ABSORB(WORDNET2.1-ABSORBVERB-4)’ has the same meaning to ‘TAKE UP(WORDNET2.1-TAKE
UP-VERB-11)’ or ‘TAKE IN(WORDNET2.1-TAKE IN-VERB-13)’. And
‘GAS-GAS(MUSTARD1.0-GAS GAS-NOUN-1)’ also has the same
meaning to ‘GAS-GAS(DMONTOL1.0-MIXED GAS-NOUN-1)’ or
‘GAS-GAS(POSTAS1.0-MIXED GAS-NOUN-1)’. Therefore, if the
search condition for function-based search is ‘ABSORB(WORDNET2.1-ABSORB-VERB-4) GAS(WORDNET2.1-GAS-NOUN-1) FROM
GAS-GAS(MUSTARD1.0-GAS GAS-NOUN-1)’, then technologies that
deliver ‘TAKE UP(WORDNET2.1-TAKE UP-VERB-11) GAS(WORDNET2.1-GAS-NOUN-1)
FROM
GAS-GAS(POSTAS1.0-MIXED
GAS-NOUN-1)’ or ‘TAKE IN(WORDNET2.1-TAKE IN-VERB-13)
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GAS(WORDNET2.1-GAS-NOUN-1)
FROM
MIXED-GAS(DMONTO1.0-MIXED GAS-NOUN-1)’ also appear on the search results list.
5. Concluding remarks and future study
Functional approach can help search the reusable technologies
like the objective of the CREAX function database is to search the
reusable scientific effects that act as an inspiration (CREAX,
2009). That is, if it is possible to extract and represent reusable
functional models from technologies and store them together with
technology documents in a knowledge base, the environment for
reusing the existing technologies without respect to technology
domains will be able to be constructed. Therefore, to identify reusable functionalities from a technology and to represent their meanings clearly and accurately are the key factors to a foundation of
the environment for technology reuse. Therefore, the ontological
functional modeling methodology which is composed of a functional modeling procedure and an ontological functional model
representation suggested in this paper is expected to contribute
to the facilitation of technology reuse. The functional modeling
procedure dealt with how to identify reusable functions from a
technology using the FAST Diagram and the ontological functional
model representation explained how to formalize the identified
functions and define their semantic meanings using the approach
of WordNet.
However, this paper still has several limitations. First, this paper
suggested how to define a functional basis but not how to guarantee its quality. Despite that the quality of a functional basis which
defines terms for functional models affects the quality of ontological functional models, in this paper choosing and finalizing terms
for a domain-specific functional basis completely rely on the decision of domain experts. Therefore a study on how to systematically
arrange the qualified terms for a functional basis is needed in the
future study. Second, this paper did not fully suggest the ontological function-based search mechanism. This paper mainly focused
on the ontological functional modeling of technology, and consequently its prototype system simply dealt with a search of the
semantically same functional models. Additionally in the future
study, using semantic reasoning, the application for function-based
search will have to support searches of similar, opposite, subordinate functional models, and how to rank the searched results.
Third, the suggested ontological functional modeling methodology
requires active participation and cooperation of people. For example, the functional modeling procedure cannot be conducted without participation of domain experts understanding the related
technologies, and the experts need to be familiar with the functional modeling procedure. Therefore a software system and a user
guideline to facilitate ontological functional modeling of technology are needed to be developed in the future study.
Finally, this paper does not intend to replace the existing keyword- and category- technology search into the function-based
technology search. Rather, the function-based search, which
understands technologies from a functional standpoint, is expected
to be one of the alternatives to complement the existing technology search mechanism for technology reuse.
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