conceptual design

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specification. Materialistic specification. Structural specification. Attributes specification. Product idea forming. Figure 4 The waterfall model of conceptual design ...

Paper Presented at EDIProd 2000, Poland.

CONCEPTUAL DESIGN: INSIDE AND OUTSIDE Professor Dr. Imre Horváth Section of Computer Aided Design and Engineering Department of Design Engineering Faculty of Design, Engineering and Production Delft University of Technology e-mail: [email protected] ABSTRACT This paper gives an insight to some of the intrinsic issues related to the understanding and the computer support of conceptual design. On the one hand, the academic research and development have produced innumerable methods and techniques to support product conceptualization. Reasonable progress has been achieved in (a) the understanding of the fundamental reasoning mechanisms, (b) the development of dedicated aspect models, (c) the application of artificial intelligence techniques in computer support, and (d) clarifying the role of conceptualization in the global product development process. On the other hand, the industry still follows intuitive methodologies and applies less-sophisticated techniques to solve conceptualization problems. With a few exceptions, it is rare when a company uses computer aided conceptual design methods and tools from the academia as a daily routine. The author has tried to explore the reasons of this phenomenon. He has become convinced that the problems originate in the endeavor of the academia to introduce abstract models, to develop highly specialized non-integral tools, and to give preference to automated, rather than highly interactive means. He finds the solution in the development of methods, tools and representations that feature very low level of abstraction, but high level of knowledgeintensiveness. The chunks of knowledge of designers have to be taken into account as patterns of conceptualization that describe the design and other concepts as well as the associations among concepts. Any model created in the course of conceptual design should be transferable to CAD/E systems without any loss of data, and without the need for extreme user involvement. Natural communication means (e.g., speaking, gesturing) have to be used to exteriorize the concepts. In handling, manipulation and further elaboration of concepts, we need smart, knowledge-intensive software agents. KEYWORDS Conceptualization, conceptual design, creativity, classification of techniques, computer-aided conceptual design (CACD) THE INTENT OF THIS PAPER This paper elaborates on the topic of development of computer tools and methods to support conceptual design as well as on a dilemma relating to the industrial application of these means. The dilemma, discovered not only by the author, can be explained in the following way. In the last three decades, the academic research achieved remarkable progress in the understanding of conceptual design as well as in the exploration of its fundamental reasoning mechanisms (Horváth, I., 1998). Important issues such as the mental activities related to conceptualization, the process and activities of conceptualization, the aspects of

Paper Presented at EDIProd 2000, Poland. conceptualization, the potential application of artificial intelligence, and the development of incomplete conceptual models have been studied. The development accompanying the research has produced innumerable specific methods and techniques to support product conceptualization. Thus, the academics offer a wealth of specific techniques for the solution of particular conceptual design problems. At the same time, product conceptualization has been a mystery for the industry for long time. The comprehension of emergence, exteriorization and manipulation of ideas and concepts are not considered important for an average company. They are profit orientated, therefore, pragmatic in thinking and making. The overwhelming majority of the product developer companies have typically delegated the task and responsibility of conceptualization as well as the conversion of the human ideas to representations to the designers. That is why they are still following intuitive methodologies and applying less-sophisticated, sometimes primitive, techniques to solve conceptualization problems. With a few exceptions, it is rare when a company makes use of the computer aided conceptual design methods and tools developed by the academia as a daily routine. The challenge that the companies have to face is that the serendipity cannot be forced or stimulated. Though its importance is recognized, computer support of conceptual design has not yet received proper attention so far. Even the software tool distributors are not exerting sufficient push to get the companies thinking about all possible applications. This paper tries to explore and elaborate on the reasons of these phenomena … WHAT IS CONCEPTUAL DESIGN? The author is fully aware of the fact that a paper discussing issues related to conceptual design is supposed to start with an explanation about what conceptual design is? It would be an easy solution to refer to an already accepted definition and to start the reasoning based on this definition. However, there exists nothing like an unambiguous definition for what we call conceptual design. Of course, several definitions have been published in books and papers dealing with the topic. Taking into account that these typically circumscribe what conceptual design is from given aspects, the author is in trouble now. Although he feels that the existing definitions are not the ultimate ones, he also finds it to be difficult to provide an all-embracing universal definition of the substance of conceptualization. Even if he constructs one, Market Motivation which he believes to be the real solution, it might analysis not be of higher value than the others. Consequently, he takes the easier way, that is, he Product ideas generation tries to explain his ideas about the concerned issues without any form of axiomatization. He believes that it does not reduce the contribution of Requirements exploration the paper. Conceptual design

Product From a methodological point of view, the very embodiement early phase of a product development process that succeeds MPT (market-product-technology) Detail investigation, product idea generation and some design sort of requirement exploration is called conceptual design. It is shown in Figure 1, Manufacturing Production planning together with the subsequent steps. Conceptual design is a multi-faceted creative process, which Figure 1 The environment of conceptual relies on many roots, as it is presented in Figure 2. design process

Paper Presented at EDIProd 2000, Poland. technology technology Conceptual design of product resource resource platform platform allocation plan sustainability market provides abstract, sometimes market allocation plan sustainability life lifecycle cycle incomplete, solutions that are investigation plan plan expected to satisfy the requirements of the consumers business product plan plan conceptualization and users from all functional, economy, technology, and competitor competitor artifact servicing and other points of evaluation modeling views. The intention of product product product product human human conceptual design to explore history history ideas ideas capacities capacities the best alternatives comes from the desire of high quality Figure 2 The roots of product conceptualization products, which are of good value to customers. The output of conceptual design is one or more new design concepts that can be used as a basis for embodiment and detail design. Since it more or less determines the achievable technical merit of the product and its encountered costs, this early phase of design is the most crucial part of the whole product design process.

In addition to the methodological interpretations, there are ontological ones, which typically go back to the epistemological roots. The term concept originates in Latin word conceptus. In epistemology ‘conceptus’ (i.e., a concept) means several things, for instance, (a) a general notion related to cognitive knowledge, (b) a mental impression or image of human mind, and (c) an abstract or generalized idea of a class of objects. The term ‘conception’ in epistemology indicates (a) beginning of a process of existence, and (b) deriving or forming an idea of something. The notion of ‘concept’ in knowledge processing denotes (a) an individual logical unit of reasoning, (b) an informal representation of a mental image, (c) a chunk of human cognitive knowledge, and (d) a new invention to help create a commodity. To give a proper circumscription of what a concept is, we have to take into account each interpretation. Research explored that conceptual design is not only supported by, but also depends on human cognitive capabilities such as (a) conjectures, (b) hypothesizing, (c) ideation, (d) generalization, (e) abstraction, (f) creativity, and (g) analysis. It is not known how the ideas happen, but imagination definitely triggers conceiving of design concepts. Based on these aforementioned fundamental notions, psychological and artificial intelligence research suggests that conceptualization is a blend of (a) creating contextual associations between intuitive and learnt concepts represented by some chunks of knowledge, (b) application of intuitions and heuristics in quasi-rational problem solving in a target area, (c) exteriorization of human mental images for observable representations, and (d) creative composition driven by human intuitions, conjectures, experiences and reasoning. For the time being, conceptual design is the least understood and therefore the less formalized field of activities in designing of artifacts. Apparently, many things influence the manifestation of conceptual design. First, its focus and orientation depend on the field of application (e.g. mechanical engineering, industrial design, electronics, etc.), although there are common principles, tasks and procedures (French, M, J., 1985). In addition, it depends on the type of the conceptualized product (e.g., hardware products, software products, or servicing products). Conceptual design is also influenced by the extent of the requested conceptualization (i.e., new design, redesign, or modification). Finally, the practical manifestation depends on the way of implementation of the conceptualization activities (i.e., intuitive, computer aided, or artificial intelligence supported).

Paper Presented at EDIProd 2000, Poland. The per se conceptual design set off with a specification, which circumscribes the requested product, the technical and other requirements, the conditions of realization and the constraints/opportunities (Polak, P., 1976). The requirements are converted to ideas about functions, first principles, structural arrangements, materialization and forms. All these happen simultaneously, in a hard to analyze synergy. There are still uncertainties about the intrinsic rules of product conceptualization. There is no scientific understanding on, for instance, (a) how can requirements be mapped onto a system of functions or potential operations, (b) how can the best matching between the targeted functions and the first principles and physical processes be achieved, (c) how can the constituents of the conceptualized artifact be identified, (d) how can a structure be derived from first principles, (e) how can the potential operations be transferred to shape, (f) how can an arrangement of functions be mapped to a structural arrangement, (g) how can the syntagmatic and paradigmatic aspects of shape definition be integrated, (h) how does the materialization influence the contextual aspects of conceptualization, (i) how is the morphology determined by the operation and the structure, (j) how can the modality be treated in idea generation and elaboration, (k) how can the behavioral processes be modeled together with the morphology of the artifact, and (l) how can we cope with the abstraction, incompleteness, and uncertainties in conceptual modeling? Progress has been achieved, but we are still far from the ultimate explanation of how the humans’ physical, mental and sensory capabilities collaborate to enable us to conceptualize? It also needs further efforts to scrutinize how the social, scientific, technological, financial and intellectual conditions authorize us to define products. These essential concerns are reflected in the perception of the phenomenon of conceptual design. Namely, there are two faculties of thoughts, which start out from different platforms of apprehension. One apprehends conceptual design as a specific problem solving methodology. The other understands conceptual design as an engineering activity. In the specific problem-solving framework, the original intuitive and creative capabilities of the human beings play more dominant role (Osborn, A. F., 1963). This is claimed, for instant, in architectural design, industrial design and graphics design. The other school considers systematized decision making as the key element, and therefore, even computer automation of conceptual design has been considered. Representatives can be found in electronics design, mechanical design and mechatronics. According to the understanding of the author, observable conceptual design is a combination of the two things. CONCEPTUAL DESIGN AS A HEURISTIC PROBLEM SOLVING ACTIVITY As a specific problem solving methodology, conceptual design is exclusively based on the inherent human capabilities such as intuition, creativity, analysis and synthesis. Psychological and AI research suggests that the cognitive mechanisms that support conceptualization are imagination and associations (Madanshetty, S. I., 1995). Imagination gives an unscripted glimpse of the subject and together with a subconscious selection leads to auto-serendipity. Association makes it possible to relate various chunks of knowledge in problem solving and helps finding insight by bisociation (Koestler, A., 1964). It also plays an important role in auto-serendipity. In principle, all types of concepts can be associated. In reality, however only those, whose form and other details of appearance are somewhat compatible. The objective of conceptualization by heuristic problem solving is to provide a representation of the solution, which condenses concepts, speculations and feelings. It is difficult to provide a formal model for a conceptualization that is based on an intuition triggered problem solving. The author has proposed a vague model that identifies overlapping

Paper Presented at EDIProd 2000, Poland. focuses of attention (Figure 3). The vagueness of the model comes Shape from the fact that it does not Materialization concepts concepts generation specify any scenario for the Product generation idea execution of the process. It only generation indicates the contextual domains Life cycle concepts on which the intuitive problem Presentation generation Functional concepts Production concepts solving process is supposed to generation concepts generation zigzag through. Nevertheless, generation conceptualization progresses through the contextual domains Figure 3 A model identifying the problem solving driven by an internal logic, domains in conceptual design depending on the application field. For instance, shape concept generation precedes the other activities in industrial design, while mechanical conceptualization typically gives priority to functional concept generation. In general, the problem solving process is accompanied by another process, called creative composition that selects and arranges the concepts instinctively with a view to the possible contextual associations. Heuristics plays a very important role in this process, since it facilitates sudden perception of matching concepts, and inclusion of novel concepts. Although articulates creative awareness, the vague model is weak from a cognitive point of view, because it does not elaborate on the creative leap (Frinke, R. A., Ward, T. B., Smith, S. M., 1992). It does not introduce a methodology that could give us certainty in the generation of ideas during conceptual design and could guide us towards learning cycles of ideation. Advantage is that it does not impede the thinking effort by an invasive framework. CONCEPTUAL DESIGN AS A SYSTEMATIC ENGINEERING ACTIVITY A problem not mentioned above is that cognition-driven problem solving may restrict itself to singular definitive solution principles to solve the problem at hand. From an industrial point of view, it is better solution to convert the requirements for a product to more than one design concept. Consequently, conceptual design of products is seen as the process of systematized exploration and composition of applicable concepts, i.e., the sub-solutions. Interpreted as an engineering activity, conceptual design becomes Product idea forming the front-end of the other Requirement Product idea downstream processes of forming specification product development Functional Requirement specification (Andersson, K., Makkonen, Exploration of P., Persson, J. G., 1995). The physical principles process of conceptual design Structural produces the input for the specification other design activities, such Morphological specification as embodiment, detailing Materialistic and documentation (Sturges, specification R. H., O’Shaughnessy, K., Geometric Reed, R., 1993). specification To express the architectural basis of the systematic

Attributes specification

Figure 4 The waterfall model of conceptual design

Paper Presented at EDIProd 2000, Poland. composition, typically the waterfall model is used (Figure 4). The origins of the waterfall model are in the German school of systematic design thinking (Roth, K. H., 1979). This process model arranges the activities in an order that reflects the epistemological way of acquiring and processing knowledge about concepts and concept structures. The sequence of activities that must be fulfilled during product conceptualization corresponds to the one indicated by the vague cognitive model. The power and soundness of this process model can be best judged for an artifact, which has never existed before. The creative composition appears in the waterfall model as an activity framework, i.e., as a set of logically arranged actions towards the intended goals. The goals are set by the time, quality, cost, and function (TQCF) requirements of production. During systematic conceptual design, we look for conceptual solutions in standardized catalogues at all milestones of the waterfall model. An important element of a systematized conceptual design is reasoning about the functions and structures of functions. The concepts providing the needed functionality are composed into promising configurations based on morphological charts (Zwicky, F., 1969). An advantage of systematic conceptual design is that it increases the level of knowledge intensiveness. In addition to it, a systematic conceptual design methodology facilitates the inclusion of computer-based support tools. However, as a critique of the conceptual design methodology implied by the waterfall model we have to mention that it arranges the activities in a pure sequential order, which is to some extent against the practice. It has already been clarified that it makes no sense to give preference or privilege to any aspect of conceptualization. Consequently, the activities are supposed to appear simultaneously. The reason is that finding the solutions from a given aspect needs a weighted comprehension of all related aspects. WHAT HAS THE ACADEMIA DONE FOR CONCEPTUAL DESIGN Conceptual design has been in the focus of academic design research for many decades (Horváth, I., Vergeest, J. S. M., 2000). Many efforts have been devoted to epistemological Techniques for conceptual design

Functional modeling techniques

Grammarsbased techniques

Multi-level functional modeling

Specific ideation


Quantitative process techniques

Symbolic structural modeling

Preliminary geometric modeling


Modeling by shape grammars

Bond graph modeling

Mathematical process modeling

Attributed graph-based modeling

Computer aided sketching

Case-based conceptual modeling

Process-based functional modeling

Modeling by principle catalogues

Petri-net Petri-net modeling

Physical simulation

Spatial relationship modeling

Skeleton based modeling


Information flow based modeling

Modeling by solution catalogues

Qualitative physics based modeling

Symbolic scheme modeling

Fast surface modeling

Feature-based conceptual modeling

Kinematic modeling

Virtual claying

Analogy-based conceptual modeling


functional modeling

Patent based ideation

Qualitative process

conceptual modeling

Physical claying Oriented particle modeling

Figure 5

A classification of the conceptual modeling techniques

Physical concept modeling

Paper Presented at EDIProd 2000, Poland. and ontological understanding as well as to exploration of the intellectual and creative mechanisms that enable human beings to be successful in conceptual design. The early research intended to explore some sort of comprehensive theory of product conceptualization and conceptual design. Later on, the issues of developing abstract, schematic and/or simplified representations got into the focus. A realistic picture has been formed about the potential of applied artificial intelligence and the necessity of using incomplete models. Pragmatism became governing and many researchers started to develop dedicated methods and techniques for well-formed problems of conceptual design. During the years, the academia produced enormous number of tools for conceptual design. Examples are tools for requirement specification, functional representation and synthesis, structural and morphological modeling, symbol-to-form mapping, shape conceptualization, and qualitative behavioral simulation (Forbus, K. D., 1996). Conceptualization of mechanical systems proved to be one of the most fertile grounds. Nevertheless, it was found that only partial models could be generated for conceptual mechanical design. Each of them has their advantages and shortcomings. Figure 5 shows a classification of the techniques dedicated to this field of application. The techniques are classified based on the activities they are aiming at. Some of the techniques support representation of concepts; the others enable reasoning about and with concepts. Note this classification is merely a methodological one, that is, it has nothing to do with the actual process. Nevertheless, the techniques can be arranged in a structure, which follows the typical flow of activities in conceptual design. This structure gives a surprisingly good covering of a common conceptual design process. There are however hidden problems as discussed below. By a deeper investigation of these techniques we can reveal some specific characteristics. For instance, almost all techniques embed a given level of abstraction. The models that capture some scientifically recognizable properties of the artifact to be conceptualized are in general of lower level of abstraction, that the ones that operate on scientifically non-recognizable properties. We can see it by comparing, for instance, a hierarchical function modeling scheme with a fast surface modeling technique. The outputs of the techniques are usually symbolic, procedural and/or physical representations that are difficult to convert to the typical input of the commercialized computer aided design and manufacturing systems. Therefore, whenever the results of conceptualization have to be transferred to embodiment or detailing, further information and efforts are needed from the designer. The problem of automatic conversion seems to be unsolvable in this case. Again an example; a shape grammar scheme can hardly be automatically converted to the input to a feature oriented assembly and part modeler due to the lack of semantic information about the features. It is also very challenging to integrate the mentioned techniques, because they are based on incompatible theoretical platforms and the used representations are significantly different. For example, it is difficult to connect a Petri-net-based process model to virtual claying, or combine a bond-graph model with a physical concept modeling. Though in principle the complete product conceptualization process could be covered with the available specific techniques, the difference in the supporting theories and representations practically prevents it. It is obvious that all pieces of knowledge needed for conceptual design cannot be included in any single model at the same level of abstraction. That is the reason why the issue of metamodels has come into the scene of many researchers (Kiriyama, T., Kurumatani, K., Tomiyama, T., Yoshikawa, H., 1989). A metamodel is a qualitative model of causal relationships among all concepts used for representation of, and reasoning about artifacts. The problem with metamodels is that they further increase the level of abstraction. Furthermore, there is no enough resolution in non-quantitative representations to reason about functions,

Paper Presented at EDIProd 2000, Poland. principles, structure, morphology, materialization and behavior simultaneously and qualitatively. HOW DOES THE INDUSTRY PERFORM CONCEPTUAL DESIGN? The relationship of the industry to conceptual design is completely different. In the industry, product conceptualization and conceptual design are simply reduced to, but supported seemingly successfully by, creative group meetings, activation of experiences, and using the analogies from existing products. Usually, it is rare when a typical company uses computer aided conceptual design methods and tools from the academia on a daily basis. It happens even more seldom when the industry asks for the development and/or implementation of a particular conceptual design tool based on their ideation. As opposed to the market of computer aided design systems, the market of the computer aided conceptual design (CACD) tools is dormant. The industry considers conceptual design as a stepchild and simply discards using the conceptual design tools developed by the academia. Most of the chief technology officers are still willing to pay for an excellent human ‘ideator’ more than for the most sophisticated AI-based conceptual design tool. Of course, there are exceptions and successstories as always, but the global picture of application of dedicated tools is rather questionable. Are there any reasons of the things mentioned above, or they just have happened to be this way? The author claims that there are three obvious reasons of this kind of behavior of the industry. First, almost all of the presently offered conceptual design tools are based on abstract reasoning models or representations. However, the models and representations typically needed by the industry are concrete, since the ultimate goal is manufacturing and assembly. Furthermore, average designers usually have different opinion about abstract representations than scientists. Abstraction facilitates capturing the essence by representations, but needs conventions to make the interpretation unambiguous. The proliferation of CACD tools is also hindered by the fact that they are tailored to specific products or to specific aspects of conceptualization. Second, the output of the available conceptual design tools cannot be directly used as input of the commercialized CAD/E systems. Handling and semantic conversion of incomplete, under-defined or imprecise product data are not solved. Designers are not keen on accepting the overhead that comes from the manual conversions and/or remodeling. Third, the offered conceptual design techniques are generally sophisticated, but synthetic solutions, which are not in harmony with the natural thinking and working of the designers in the course of conceptualization. The goal of conceptual designers is to produce concept variants, rather than polishing their minds by solving tricky application problems. WHAT WOULD BE BETTER TO DO? In spite of the richness of the choice of computer supported conceptualization tools, there is still a long way to go. Namely, in order to achieve better results in conceptual design, we have to bring the academic developments closer to the industry needs. We have to strive after developing methods, tools and representations without unnecessary abstraction. In order to achieve seamless integration, we have to be able to convert abstract representations to concrete ones, and vice versa. At the same time, it seems to be inevitable to implement knowledge-intensiveness in computer-supported conceptualization (Albers, L. K., 1994). Computer systems have to be involved in conceptualization on a higher level of semantics and synergism. The patterns of conceptualization followed by designers have to appear as chunks of knowledge that describe the concepts as well as the associations among them (Horváth, I.,

Paper Presented at EDIProd 2000, Poland. Kuczogi, Gy., Vergeest, J. S. M., 1998). Smooth transition has to be achieved from mental ideation models to comprehensive initial modeling. Since the global concepts of products appear as a totality, artifact and process representations have to be integrated in common models. To achieve it, efforts have to be made towards unifying representations and reasoning frameworks that enable us to consider the aspects of conceptualization concurrently. We need computational models that can equally well be interpreted by humans and computers and, at the same time, facilitate the transition from conceptual phase to system and geometry modeling phases of design. The possible ways of application of incomplete, but knowledgeintensive, models have to be explored. A conceptual model created as a composition of concepts should be transferable to CAD/E systems without the loss of data and the need for extreme user involvement. Transfer of the techniques from template applications to real-life problems has to be made possible too. Some of the techniques that can be easily applied to small scale problems fail to be applicable for cases of high complexity. We have to reconsider using natural communication means to exteriorize concepts. As a matter of fact, even the opportunities offered by the joint use of speaking, gesturing and making in conceptualization of functions and shapes are not explored yet. Also, new system architectures are waited to come. In addition to it, the complex reasoning might be assisted by smart agents in the knowledge-intensive CACD software. It can be foreseen that advances in such fields as knowledge mining based on hypermedia representation will significantly contribute to solving some of the problems of knowledge management in conceptual design. SUMMARY AND CONCLUSIONS This paper tried to investigate conceptual design from inside and outside. Inside the realm of conceptual design significant progress has been achieved, but there are still many unsolved issues originating in the insufficiency of the available knowledge. Having recognized its possible contribution to a successful product development, the academic research is putting more and more emphasis to both the cognitive and engineering aspects of conceptual design. For a more capable conceptualization both aspects have to be explored much deeper. On the one hand, the industry has mystified and therefore somewhat neglected conceptual design so far. On the other hand, it is struggling with the problems caused by the immature and nonintegral tools. It can be predicted that the attitude of the industry will change in the near future for the reason of the ever-increasing competition on the product market. It can also be seen that the academia faces some urgent tasks to keep up with the conceivable progress and tendencies in the industry. Among the tasks of highest priority, the following ones can be mentioned: (a) more natural ways exteriorization of ideas have to be explored, (b) computer systems have to be involved in conceptualization on a higher level of semantics and synergism, (c) smooth transition has to be achieved from mental ideation models to comprehensive initial modeling, (d) the possible ways of application of incomplete, but knowledge-intensive models have to be explored, and (e) artifact and process representations have to be integrated in common models. REFERENCES Albers, L. K.: YMIR: A Sharable Ontology for the Formal Representation of Engineering Design Knowledge, IFIP Transactions: Computer Application in Technology, Vol. B-18, 1994, pp. 3-32. Andersson, K., Makkonen, P., Persson, J. G.: A Proposal to a Product Modeling Language to Support Conceptual Design, Annals of CIRP, Vol. 44, 1995, pp. 129-132.

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