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Page 1: Concept space connected to knowledge processing for supporting creative design

E L S E V I E R Knowledge-Based Systems 10 (1997) 29 35

Knou~ledge-13ased _~VSTEI"I~----

Concept space connected to knowledge processing for supporting creative design

K o i c h i H o r i *

Department ~[ Aeronautics and Astronautics, School ~f Engineering, University ~f Tokyo. 7-3-1 Hongo, Bunkyo-ku. Tokyo 113. Japan

Received 6 March 1997: accepted 10 March 1997

Abstract

This paper describes a system that supports creative design. The system presents the user with a "'concept space" in which fragments of requirements and design parameters are arranged as the result of knowledge processing. Interacting with the concept space, the designer can apply design strategies which are different from those used in daily design, which may lead to creative design. © 1997 Elsevier Science B.V.

Keywords: Creativity support: Creative design; Strategic knowledge

1. Introduction

This paper describes a system that supports "creat ive des ign" . The concept "c rea t ive" has long been studied extensively from various viewpoints [1-5] . Especially in the last few years much attention has been paid to the cog- nitive aspects of creativity [6-8] .

We have at least two approaches to the big problem of creativity. One is to study creativity itself - through obser- vation or cognitive experiments on people ' s creative activ- ity. Another is Io study how computer systems can support creativity and investigate the nature of creativity through the change of people 's work with and without support systems. The work presented in this paper belongs to the latter. We consider a system to support creativity in the field of design. The exemplar domain dealt with is the design of aeroplanes.

The system has the feature of using "concept space" as the interface to support the designer in applying design stra- tegies. The concept space is connected to knowledge pro- cessing and the designer can try a design strategy which is different from the dai ly-used strategies, thereby acquiring stimulation to creative design in the form of a peculiar design solution.

In the following sections, we first describe the problem of creativity in design and compare our work with related work. Then we consider the use of strategic knowledge for creative design. We propose to use a concept space

* Tel.: +81 3 3812 2111 ext. 6642: fax: +81 3 3818 7493; e-mail: hor- i @ ai.rcast.u-tokyo.ac.jp

0950-7051/97/$1700 © 1997 Elsevier Science B.V. All rights reserved PII S0950-7(151(97)0001 I-7

connected to knowledge processing to stimulate the creativ- ity of designers. The results of some experiments are shown and the effectiveness of the system is discussed.

2. Creativity in design

The human activity of design is always, in some sense, creative. For example, in the domain of design, we may find a certain creativity of the designer even in so-called routine design; the designer can be creative in giving a novel com- bination of values to design parameters. But usually, when we think of creativity in design, we think that some unusual novelty is essential. Moreover in design, as opposed to crea- tivity in art, the creative work should be acceptable from the viewpoint of manufacturing and use.

Gero classified design into (1) routine design, (2) innova- tive design, and (3) creative design [9]. Routine design was defined as that design activity which occurs when all the necessary knowledge is available. Innovative design was defined as that design activity which occurs when the con- text which constrains the available ranges of the values for the variables is jet t isoned so that unexpected values become possible. Creative design was defined as that design activity which occurs when a new variable is introduced into the design.

Boden says an idea is P-creative if the person in whose mind it arises could not have had it before, and, by contrast, an idea is H-creative if it is P-creative and no one else has ever had it before [6]. Boden investigated the role of

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30 K. Hori/Knowledge-Based Systems 10 (1997) 29 35

exploring a conceptual space and transforming a conceptual space in creativity.

The difficult central problem of how the system supports creative design is how the system aids the designer to transform the conceptual space, in Boden's term. Fischer's group claims that this can be done only through human- problem domain interaction, not through human-computer interaction, and that the "breakdown" evokes the jump to creative design [10]. The author of this paper shares Fischer's claim that the designer's creativity can be evoked in the problem domain, not in the manipulation of the computer interface. Thus, the question dealt with in this paper is whether the system can artificially trigger the "breakdown", which stops the routine mental process and forces the designer to jump into other mental spaces, and whether the artificial breakdown is effective for the designer.

3. Strategic knowledge

Designers have certain strategies on design. They are sometimes articulated and sometimes tacit. Some strategy leads to modest design that satisfies every requirement on average, and some strategy may lead to peculiar design that concentrates on some special requirement. The designers control the process of design consciously or unconsciously according to those strategies. Our expectation in building the system for creativity support is that the support system may trigger a change of the design strategy.

While the design strategies that lead to creative design need much more study, we have tested two sorts of strategy. One is "abandonment strategy" and the other is "new knowledge strategy".

The designers often stick to the strategy which leads to the design that satisfies all requirements. But abandoning some requirements may change the search space of design to a very different space. This largely corresponds to the "innovative design" in Gero's term. Incorporating new knowledge may also be effective for changing the space of design. This largely corresponds to the "creative design" in Gero's term.

In the interaction with the "concept space" described in the next section, these strategies can be applied by the designer for divergent exploration of design; the system does not force the designer to use one of these strategies, but the designer may notice that such strategies can be used in the interaction with the problem domain through a repre- sentation of concept space on a computer.

Design strategy can be represented as meta-knowledge, which is knowledge concerning how to use some domain knowledge, in the knowledge processing system for the design support. We use a knowledge processing system named KAUS built by Ohsuga [11] that has the feature of explicit representation and processing of multi-layer meta-knowledge.

4. Concept space and knowledge processing

The author's group has implemented and tested several systems that map the conceptual space in the designers' mental worlds into Euclidean spaces and thereby stimulate the designers' further concept formation [ 12-17]. The basic idea underlying these systems is that even the tacit dimen- sion in the human mental world can be articulated little by little through the interactive configuration of the conceptual space presented on the system and this sometimes leads to creative concept formation.

In those previous systems, the user inputs several words (or short phrases) and identify the relations among the words, which become the partial reflection of the user's mental world. The system calculates distances among the words based on relations designated by the user and config- ures concept spaces using the method of multi-dimensional scaling. Unexpected configuration of the space, e.g. empty regions, works as the stimuli for the user's further concept formation.

In the system proposed in this paper, the relations among words come from the result of knowledge processing, while previous systems used the relations given by the user. This mechanism provides the user with an environment to deal with design strategies.

Fig. 1 shows an example of concept space presented by the system during aeroplane design. In this space, fragments of design requirements and related design parameters are configured. For example, the rectangle with the word takeOffDistance in the space means that the designer holds the requirement on take-off distance in his mental world. The designers consciously or unconsciously know which requirements are important, which requirements are not so important, and which requirements are strongly related to which requirements. The concept space shown in the figure can intuitively show the designer's mental world if the designer moves the positions of the require- ments in the space according to his/her ideas on the relation among the requirements. In the case of the system presented in this paper, although the user can change the space freely, the system also automatically presents a space resulting from knowledge processing, which can sometimes evoke the "breakdown" to the designer's usual thinking, because the resulting concept space may be different from the one held in the designer's mind.

The knowledge used for the calculation of the space con- figuration comes from the domain knowledge of aeroplane design. In the current implementation of the system, the main parts of the knowledge on aeroplane design are given in such formulas as

FR~(v) *--- DPi(x) n DPjO') n F~(x, y, v)

This formula reads as "in order to get the value v of FR~, get the value x of DPi and the value y of DPj, then use the function F~(x,y,v)," where FR (functional requirement) is a predicate concerning functions or properties of the

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K. Hori/Knowledge-Based Systems 10 (1997) 29-35 31

Fig. 1. An example of concept space. PitchingMomentStability and YawingMomentStability are strongly related,

aeroplane, DP (design parameter) is a predicate concerning the design parameters, and F is a function to calculate the values. For example, when FR,~ is Yawing_Moment_Stability, DPi is Wing_Size, DPj is Engi- ne_Thrust, and so on.

From the design knowledge represented in the formula as shown above, the distance between FR~ and FR~ is esti- mated for building the concept space. In the current system, we use a heuristic rule that estimates the distance smaller if the formula of FR~ and the formula of FR~ have more common design parameters. For example, if FR~ and FR~ share only one design parameter and FR~ and FR~ share three design parameters, the distance between FR~ and FRv can be estimated to be about three times smaller than the distance between FR,~ and FR~. This estimation of the distance is carried out by the meta-knowledge processing function built into the KAUS knowledge processing system [11]. Since the knowledge used in design depends on con- text of design and the used functions are often non-linear, several other heuristics are also used for estimation of the distance. Based on this estimation of distance among

functional requirements and design parameters, concept space is calculated by the multi-dimensional scaling method. Fig. 1 is an example of the result of the calculation.

The concept space presented by the system is connected to the knowledge processing for design. Pointing to the icon showing the requirement, e.g. Yawing_Moment_Stability, in the space by mouse operation, the designer can place the requirement value and priority of the requirement using a pop-up menu. Those values having been entered, the system calculates the candidate values of design parameters by the knowledge processing method proposed by Ohsuga [ 18].

Through this cycle of operation, the designer can change the design strategy. For example, if the designer places high priority on some requirements and very low priority on other requirements, this operation means that the designer has adopted the abandonment strategy, i.e. the requirements of low priority are abandoned.

Looking at the concept space presented by the system, the designer sometimes wishes to change the relations among the requirements and design parameters. For example, if some requirements are too strongly mutually related and

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32 K. Hori/Knowledge-Based Systems 10 (1997) 29--35

Fig. 2. An example of concept space. PitchingMomentStability and YawingMomentStability are separated but YawingMomentStability and PayLoad are strongly related.

thus placed at a short distance, this makes the design diffi- cult because this means the designer cannot determine those requirements independently. The designer wants to make the distance between the interrelated requirements larger but this requires new knowledge. This corresponds to use of new knowledge strategy. If the designer can successfully provide new knowledge, the constraints among the require- ments change, and this may lead to creative design.

Examples of the use of such strategies are shown in the next section.

5. Experiment

A graduate student in an aeronautics and astronautics course tested the system and the resulting aeroplane design was shown to four professors in the course.

The student first placed nine requirement items. They are TakeOff Distance, RollMomentStability, Payload, LandingDistance, CruiseRange, YawingMomentStability,

MaxVelocity, LoiterTime, and PitchingMomentStability. The system had knowledge about those requirements and gave the space shown in Fig. 1. Fifteen design parameters - ThrustWeightRatio, WingLoading, GravityCenter, and so on - were placed in the space by the system. In this case, these were all that appeared in the space, but even if the designer forgets to indicate some requirements, they may automatically appear in the space because the system can judge, using the design knowledge, that those requirements are related to the requirements given by the user.

Looking at the space shown in Fig. 1, the user wondered if he could make the distance between YawingMomentSt- ability and PitchingMomentStability larger. The user con- sulted recent literature on aeronautics and decided to use new Quasi-Strip Theory and incorporated two new design parameters - Elbone and TwistOfMain Wing - and added some design knowledge. As a result, the concept space was changed into the space shown in Fig. 2, where YawingMomentStability and PitchingMomentStability were successfully separated. Looking at the space shown

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K. Hori/Knowledge-Based Systems 10 (1997) 29-35 33

Fig. 3. An example of concept space. YawingMomentStability and PayLoad are separated.

in Fig. 2, the user furthermore wondered if he could separate PayLoad and YawingMomentStability. He invented an idea of a kind of Active Flight Control and added some design knowledge. This resulted in the space shown in Fig. 3.

Interacting with the space shown in Fig. 3, the user gave high priority to stabilities and arrived at the candidate design solution shown in Fig. 4.

These results were shown to four professors in the Department of Aeronautics and Astronautics. All the pro- fessors first laughed at the result and said how stupid the system and the student were. (Since the author of this paper has a background not in aeronautics but in computer science, the author could not understand why the results were so funny.) But after they laughed, an interesting dis- cussion began. They began to examine why such a peculiar design solution was given by the system. As a result of discussion, the professors admitted that the idea acquired in the interaction between the student and the system might lead to a domain of design solution that has not been tested much so far, although the candidate design solu- tion itself given by the system could not be adopted. This

suggests that the funny result acquired through use of the system stimulated the creativity of the professors, because the resulting solution itself was funny but included some new ideas.

Unfortunately, this experiment ended at this point. If we repeat the cycle of (1) build the concept space, (2) change the concept space, and (3) get the design solution, we believe we can achieve more real creative design.

6. Discussion

The effectiveness of the concept space connected to knowledge processing lies in providing a designer with an environment for rapidly testing the cycle of giving a new idea and getting the design result according to the new idea. Although this may be done even in existing environments, the concept space presented by the system stimulates the designer more directly for using design strategies different from those used daily, because the designer can visually reflect on the relations among design requirements.

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34 If. Hori/Knowledge-Based Systems 10 (1997) 29-35

alrcraft,actlveFCS,1.0). alrclllft,welghtTO,5000.0). alrcraft,gravltyCenter,60.0). englne,thrustWelghtRatlo,0.§0). fullelage, leflgth, 14.0). wlng,wlngLoadlng,240.0). wlng,aspectRatlo,11.0). wlnO,taperRatlo,0.6). wlng,vertl(:alPoslUon,20.0). wlng,sweepBackAngle,45.0). wlng,dlhedralAngle,0.0). wlng,clmu,2.0). vertlcalTall,vtMomentArm,50.0). verUcalTall,vtSIze,2.0).

Fig. 4. A candidate design solution. Requirements on stabilities were given high priority.

The "abandonment strategy" and "new knowledge strat- egy", which may lead to creative design, are not forced on the user, but the designer naturally notices them through interaction with the concept space. Explicit recommenda- tion of strategies might be possible, but we do not think that professional designers like it. Moreover, there is the possi- bility that the designer uses his own strategies. We believe the system proposed in this paper promotes a trial of differ- ent strategies, because the routine design strategy cannot change the configuration among the requirements in the concept space.

The aeroplane design given by the system shown in Fig. 4 reminds us of the "funny bike" sketched by the designer Mike Burrows during a period of attempting the creative design of bicycles [19]. Professional designers draw many interesting sketches when they think of a new design. The experiment shown in the previous section suggests that the funny result given by the system can provide stimulation for further consideration on creative design, since the funny result came from knowledge processing and included many seeds of new ideas.

design. The system shows a designer a concept space in which design requirements and design parameters are con- figured. The space is connected to a knowledge processing system and the designer can try to design using peculiar design strategies such as abandonment strategy and new knowledge strategy. The resulting design solution given by the system in the experiment was funny but included interesting seeds of new ideas and effectively evoked dis- cussion on new knowledge among the experts. Although the experiment carried out is not large enough and needs further quantitative and qualitative evaluation, it suggested that the system can support creative design. We are now improving the system's functions of explaining its behaviour and of incorporating new knowledge.

Acknowledgements

The author thanks Tetsuya Nagao who implemented the system.

7. Conclusions

This paper described a system for supporting creative

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