Synectical Building of Representation Space: a Key to Computing Education Sebastian Koziolek1 and Tomasz Arciszewski2 1
Wroclaw University of Technology, Institute of Machine Design and Operation, Lukasiewicza 7/9, 50-371 Wroclaw, Poland, (Fall 2010, Visiting Professor, George Mason University, Fairfax, VA, USA), phone: 0048-71-320-4285, e-mail:
[email protected] 2 George Mason University, the Volgenau School of Engineering, Civil, Environmental and Infrastructure Engineering Department, 4400 University Drive Fairfax, VA 22030, USA, phone: (703) 993-1513, email:
[email protected] ABSTRACT This paper proposes a method for building a design representation space capturing domain knowledge and at the same time creating an opportunity to acquire knowledge outside the problem domain. This dual emphasis increases the potential for producing novel designs. The method combines the advantages of heuristic thinking based on Synectics with traditional systematic and analytical thinking and is intended mostly for use in computing education. It will allow students to develop a fundamental understanding how to acquire knowledge necessary for conceptual design while preserving their ability to explore various domains and to expand a representation space. INTRODUCTION Design innovation depends on the novelty of design concepts, products of conceptual design. Unfortunately, very often design concepts are simply a reflection of the present customer needs and the entire design process is focused only on satisfying these needs. In such a process mostly the problem-specific knowledge is exploited and it rarely produces truly innovative design concepts, i.e. patentable concepts advancing evolution of engineering systems [11]. From the knowledge perspective, conceptual design can be considered as a two- or three-stage process. First, design knowledge is acquired. In the case of conceptual design entirely conducted by humans, the acquired knowledge is used directly in the second stage of concept development. When computers are used, in the second stage the acquired knowledge must be formally presented as a knowledge representation space, in the form of decision rules, and/or of ontologies. Then, in the third stage this formal knowledge may be used for the concept development. In both cases of human and computer-aided design the nature of acquired knowledge is crucial for the conceptual design process and its results. If knowledge is acquired only from the problem-specific domain, the subsequent development of design
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concepts can be considered as exploitation of a design representation space prepared only for a specific domain. If knowledge is acquired also from outside this domain, from other engineering or science domains, then the development of design concepts can be considered as exploration. Obviously, this type of conceptual design is much more effective than exploitation-based design as far as innovation is concerned [6]. Presently, engineering education is focused mostly on the analytical aspects of design and does not sufficiently address issues associated with conceptual design. If conceptual design is discussed at all, it usually is considered as an exploitation process, which can be deductively conducted using, for example, various search methods. To advance engineering design education, a much better and complex understanding of conceptual design based on exploration must be developed, including understanding of methods, and tools. This paper is focused on the fundamental issue how to acquire knowledge to be used in computer-aided conceptual design, knowledge which will allow exploration and ultimately will create opportunities for the development of novel design concepts. As a result of our studies a method is proposed, which is intended for use in engineering education to prepare future engineers for their challenges as explorers and inventors. INVENTIVE CONCEPTUAL DESIGN METHOD The proposed method is based on the following assumptions: It is intended for inventive conceptual design Inventive conceptual design is a process leading to the development of design concepts, which are new, non-obvious and surprising, as well as potentially patentable concepts A design concept is an abstract description of a given engineering system in terms of mostly symbolic attributes Inventive conceptual design is a process of learning/knowledge acquisition related to the problem and of acquiring knowledge about inventive design concepts [2] It is intended for a team conceptual design It uses Synectics [8] for knowledge acquisition and for generation of design concepts Knowledge acquisition is conducted using “Knowledge Acquisition Network” “Knowledge Acquisition Network” utilizes both internal and external knowledge acquisition processes The method is based on a five-stage process (Fig. 1), including such stages as: Problem identification, Team selection, Problem formulation, Knowledge acquisition and development of design concepts, Concept evaluation and selection. The first three stages are preparation for the most important and difficult Stage 4 [3], called „Knowledge Acquisition and Development of Design Concepts”. In the first
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stage, called „Problem Identification”, the Team Leader indentifies the problem and presents it in a desriptive form. Next, he/she determines the relative position of the problem with respect to the State of the Art (SOTA). In the second stage, the Team Leader selects team members, called „Synectors”. The ideal team of Synectors should be balanced considering at least eight main characteristics, listed below: 1. Domain Differentiation: Synectors should represent various domains, for example four engineers and two-three professionals from non-engineering domains (for example, biology, law, history, etc.) 2. Emotional involvement: differentiated levels of motivation 3. Thinking styles: global and local thinkers, members with legislative, executive, and judicial thinking styles, etc. 4. Differentiated Age: optimal age is 25-40, but all ages are acceptable 5. Administrative Experience: one or two experienced executives understanding managment 6. Entrepreneurship: one or two entrepreneurs focused on action 7. Job Experience: Synectors should be experienced and successful 8. Differentiated Education: as many domains as possible, including Art, Engineering, Biology, etc. 9. The “Almost” Individual included: people who are not very successful at work but have potential 4
Knowledge Acqusition and Development of Design Concepts
Constrains
1 Problem Identification Problem Description SOTA Relative Position
Principles of Selection
2 Identified Problem
3
Team Selection
Synectors
Analogies and Metaphors
Problem Formulation
Task
Internal Synectics Session
5 Concept Evaluation Idea Selection Design Concepts
Function Description
Technical Specification
Atributes Determination
External Synectics Session
Assumption of Value Limits
Needs Questioning system
Figure 1. Conceptual design process In the Stage 3, called “Problem Formulation”, the entire team is building a group understanding of the problem and is working on the formulation of the specific design tasks. In the Stage 4, called “Knowledge Acquisition and Development of „Design Concepts,” all knowledge is acquired and design concepts are developed. This integrated process is based on the assumption that human development of new ideas (design concepts in our case) requires knowledge and is inspired by knowledge from various domains. For this reason, the process of knowledge acquisition in the proposed method is conducted using Synectics and both internal and external Synectics sessions. Our idea of using Synectics for knowledge acquisition has been inspired by great inventors, who also learned using unconventional methods. For example, Leonardo da Vinci learned human anatomy using human carcasses to improve his inventions [5] and Thomas Edison sought knowledge in poetry, which his mother taught him while schooling him at home [6]. Another great inventor,
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Genrich Altshuller [18] learned inventive knowledge studying thousands of patents and looking for patterns in the evolution of various engineering systems. In the proposed methods, the integrated process of knowledge acquisition and development of design concepts is called the “Knowledge Acquisition Network”. In this case, knowledge and new design concepts come from internal and external Synectors participating in Synectics sessions. First, an internal Synectics session is conducted. In this session, six-eight Synectors use the problem description and the problem formulation and try to acquire knowledge both from the problem domain and from other unrelated domains. This initial knowledge is then reformulated and its context changed using four analogies (Figure 2), including: Personal Analogy, Direct Analogy, Symbolic Analogy and Fantasy Analogy.
Figure 2. Illustration of Synectics Analogies When an internal Synectics session is conducted, the most fantastic and infeasible concepts are created. They are not useless because they can be considered as seeds in an evolutionary process, which may ultimately lead to novel and feasible. Next, the initial concepts created using Analogies are transformed by Synectors in accordance with selected metaphors [4]]. As a result of this, the concepts gradually become better and their feasibility is improved. This part of the session is very important, because the conducted process leads to the seed questions for the External Synectics Session. Then, all Synectors distribute the questions through the entire Knowledge Acquisition Network, searching for new sources of inspirations and concepts, if possible. An External Synectic Session could be something small like a short conversation with friends or family, or something big like an international teleconference or a forum on the Internet. All knowledge acquired from these interactions is then presented in the second internal Synectics Session [8]. In this session the most interesting, novel, and plausible design concepts are produced. After the development of a class of design concepts, Stage 5, called “Concept Evaluation” is conducted (Figure 1). In this stage, the produced design concepts are evaluated first and next the best concept, or several comparable concepts in terms of their
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novelty, utility, or feasibility are selected. At this stage, concepts are usually presented in the descriptive form. Their descriptions are used then to identify symbolic attributes and their values. Next, other possible values for the individual attributes are determined and in this way the entire ranges of variation are obtained for all identified attributes. Finally, these attributes and their values are used to construct the design knowledge representation space for a given problem. The developed design representation space allows the preparation of patent claims and/or of design specifications for the detailed design. VALIDATION OF METHOD An Internal Synectics Session was held at George Mason University in November, 2010. There were four team members with different personal and professional backgrounds, who represented various engineering domains, and were at different stages in their respective professional careers. Members of the team included an MS student, a Ph.D. student, a junior faculty, and a 75-year old student and inventor with 50 patents. Problem Identification. Today a threat to the lake fisheries and recreation industry in the Great Lakes is in the form of two related invasive species (Asian Carp and Silver Carp) that escaped into the Mississippi River in Arkansas during the mid1990s and have been moving upstream through the watershed ever since. Both carps are voracious eaters, and they crowd out native species. They also create hazards to boaters, as they are easily stimulated to jump out of the water by the sound/vibration of motors. These fish may grow to 50 pounds or more, and are dangerous projectiles to boaters when jumping. Problem Formulation. The problem was finally formulated as follows: Keep the Asian and Silver Carp population out of the Great Lakes and satisfy the following requirements: 1) Minimal change to the time required for barge transit, and minimal additional operating costs. 2) Strong assurance that the new system will prevent the invasive species from entering the Great Lakes through Lake Michigan. Personal Analogy. Concept development using the Personal Analogy is the third step in the Synectics Session. All concepts developed with the Personal Analogy describe personal ability to keep the Asian Carp out of the Great Lakes. Thus the ideas involve sentences such as “I eat”, “I block”, “I kill”, etc. It is important to use this concept development in the Personal Analogy Stage of Synectics Session. Synectors usually have a tendency to use all analogies at the same time. Direct idea formulation keeps Synectors focused on using one analogy at the time, thereby maximizing the effectiveness of the session. Direct Analogy. In this analogy, Synectors look for similarities in different systems. The most powerful effect of this part of the session is the use of the Direct Analogy in the context of energy. Application of different form or source of energy to keep the Asian Carp out of the Great Lakes was the task in this stage of the session. The selected results from the Direct Analogy Stage of Synectics Session are presented in Table 1.
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Table 1. First class of selected concepts developed using Direct Analogy DA Item 1 2 3 4 …
Concepts High frequency sounds to repel fish movement Turbulence in the water to prevent fish movement Temperature barriers to prevent fish movement into Great Lakes Pressure barriers to prevent fish movement into Great Lakes …
Symbolic Analogy. One of the most powerful analogies is Symbolic Analogy. This analogy shows a logical unit represented by a symbol. Very often, the symbols in this analogy are the natural objects, such as human body parts, trees, leaves, etc. Often ideas generated by the symbolic analogy could equally well be developed using a direct analogy. But the mere fact of looking for symbols affects the development of new solutions. Thus, despite the seemingly similar results, application of only one of them may be insufficient. The selected results from the Symbolic Analogy Stage of Synectics Session are presented in Table 2. Table 2. 1st , 2nd & 3rd class of concepts developed using Symbolic Analogy SA Item
1 …
1st class of concepts
2nd class of concepts
Human heart used as a pump in water exchange in the river
Valves of combustion engine used to control water pumping Dialysis Machine used to clean the water in rover
3rd class of concepts Canal Lock System (with the use of water exchange system)
…
Fantasy Analogy. Another analogy used is Fantasy Analogy. It is the simplest analogy for development of the first class of concepts. However, this part of the Synectics Session is the most difficult in terms of evolutionary concepts. The transformation of fantastic ideas from the first class of concepts into the next one is the crucial part of the session. This is because the transformation requires the change of a fantasy into a real, possible concept. Attributes determination. After concept selection, the function tree has been decomposed into various attributes in order to describe each function. Conclusions. The proposed method is intended to bridge an important gap in computing education between education focused on the traditional analytical use of computers and education dealing with advanced use of computers in design, including inventive conceptual design. In both cases a knowledge representation space is a must. However, in the case of analysis, a knowledge representation space is usually known or easy to prepare as a result of repetitive nature of computations. In the case of inventive conceptual design the situation is entirely different. Usually solving inventive problems requires exploration of knowledge and that leads to building a representation of knowledge from the problem domain and from other
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domains. Also, the nature and extend of such knowledge representation has a direct impact on the novelty of produced design concepts and often also determines if a given problem can be solved. The proposed method has been developed as a result of extensive research on methods and tools for building design knowledge representation space. It has been tested with a group of students and modified as a result of the provided feedback. The method is not easy to use and it is appropriate only for students familiar with Inventive Engineering and with Synectics. Also, all team members must be carefully selected and prepared for their participation in the team efforts. During the entire process the team cohesion must be maintained and team members constantly motivated and encouraged to be involved and to contribute to the process. The method is also sensitive to the internal group balance, i.e. no group member is supposed to dominate the team and the Team Leader must constantly react to the changes in the group’s dynamics. The conducted experiments were successful. The team efforts produced a continual flow of concepts and all members contributed in various ways, reflecting their knowledge and personalities. Most likely, the team size (four members) was too small and that might have negative impact on results because all team members needed to be fully engaged all time, sometimes nearly impossible to maintain. Our experiments clearly demonstrated that it is possible to develop a transdisciplinary design representation space for inventive conceptual design and that this goal can be accomplished in a systematic manner. Synectics proved to be difficult to use but it helped to acquire a rich body of knowledge. The method still requires refinements but even in its present form it can be used for teaching how to acquire transdisciplinary knowledge and how to use it to develop a design knowledge representation space. REFERENCES [1] Arafat G., Goodman B., Arciszewski T., "Ramzes: A Knowledge-Based System for Structural Concepts Evaluation," Special Issue on Artificial Intelligence in Civil and Structural Engineering, International Journal on Computing Systems in Engineering, pp. 211-221, 1992. [2] Arciszewski, T., Grabska, E., Harrison, C., “Visual Thinking in Inventive Design: Three Perspective”, Soft Computing in Civil and Structural Engineering, Topping, B.H.V. and Tsompanakis, Y, (Editors), chapter 6, pp. 179-202, Saxe-Coburg Publications, UK, 2009. [3] Arciszewski, T., Successful Education. How to Educate Creative Engineers, Successful Education LLC, pp. 200, December, 2009. [4] Brewbaker J., Metaphor making through Synectics, Exercise Exchange, Spring 2001, Vol. 46, No. 2. ProQuest Education Journal, pp. 6. [5] Gelb. M., How to Think Like Leonardo da Vinci: Seven Steps to Genius Every Day, Dell Publishing, 1998 [6] Gelb. M., Miller Caldicott S., Innovate Like Edison: The Five-Step System for Breakthrough Business Success, Dutton Books, 2007. [7] Gero, J., “Computational Models of Innovative and Creative Design Processes, special double issue, “Innovation: the key to Progress in
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Technology and Society,” Arciszewski, T., (Guest Editor), Journal of Technological Forecasting and Social Change, North-Holland, Vol. 64, No. 2&3, June/July, 2000. [8] Gordon W. J., Synectics: The Development of Creative Capacity, Harper and Row, 1961. [9] Harrison C., “Inventive Design, Neuroscience and Cognitive Psychology,” an invited lecture, CEIE 896, “Design And Inventive Engineering, George Mason University, 2010. [10] Kano N., Nobuhiko S., Fumio T., Shinichi T.: Attractive quality and MustBe Quality, Hinshitsu, 1984. [11] Karlinski J., Rusinski E., Lewandowski T., New generation automated drilling machine for tunnelling and underground mining work, Automation in Construction, vol. 17, nr 3, s. 224-231, 2008. [12] Kicinger R, Presentation on Bioinspired Design. IT 896 – DESIGN AND INVENTIVE ENGINEERING, George Mason University, 2010. CHANGE [13] Kleyner A. Sandborn P., Boyle J., “Minimization of Life Cycle Costs Through Optimization of the Validation Program – A Test Sample Size and Warranty Cost Approach”, Reliability and Maintainability, 2004 Annual Symposium – RAMS, 26-29 January, 2004. [14] Kolb E. M. W., Hey J., Hans-Jürgen S., Agogino A. M., “Generating compelling metaphors for design”, Proceedings of the 20th International Conference on Design Theory and Methodology, DTM 2008, August 3-6, 2008, New York City, New York, USA. [15] Lerdahl E., “Using Fantasy Story Writing and Acting for Developing Product Ideas”, Proceedings of EURAM, 2002. [16] Shelton, K., Arciszewski, T., “Formal Innovation Criteria,” International Journal of Computer Applications in Technology,” pp. 21-32, January, 2008. [17] Yi-Luen Do E., Gross M. D., “Drawing Analogies: finding visual references by sketching”, Proceedings of Association of Computer Aided Design in Architecture (ACADIA) 1995, Seattle WA , pp 35-52. [18] Zlotin B., Zusman A., Directed Evolution: Philosophy, Theory and Practice, Ideation International Inc., 2001. ACKOWLEDGEMENTS This article is a result of research conducted by the first author at George Mason University and in cooperation with the second author. The Synectics session was held at George Mason University in November, 2010. The authors thank all synectors for their participation and numerous contributions, including Mario Cardullo, David Flanigan and Ali Adish. Finally, the authors would like to acknowledge contributions of Izabela Koziolek (
[email protected]) who has prepared all drawings used in Figure 2.
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