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The Influence of New 3-D CAD Systems on Knowledge Creation
in Product Development
KENTARO NOBEOKA YASUNORI BABA
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The management of knowledge creation is considered one of the key factors in the management of new product development. In the past, differences in knowledge creation capabilities at the organizational level were primarily attributed to the quantity and quality of human interactions that were facilitated by the appropri- ate organizational management (Nonaka, 1994; Kogut and Zander, 1992). Al- though organizational interactions continue to be important, the use of informa- tion technologies (ITs), including design, engineering, and manufacturing (CAD/
CAE/CAM), is becoming a much more critical factor for organizational knowledge creation in product development.
Traditionally, ITs have been considered tools that support product development processes with organizational management positioned in the center. However, it appears that in the future IT will play a much more critical role and in some cases it will actually lead the changes in new product development processes. The purpose of this essay is to outline how the newest generation of information technologies will play this key role in terms of their effect on the knowledge-creation process.
New CAD technologies coupled with new organizational structures and processes that are designed to complement the new ITs have only just begun the fundamen- tal change that they will make in the core concept of traditional product develop- ment activities. Most of the firms we have studied are currently implementing these initial changes. We will lay out the key issues these firms both have been struggling with and will have to consider in the immediate future.
The effective utilization of ITs in the product development process is part of a larger trend in which Japanese human-oriented approaches are being integrated with Westernsystematic-rationality-oriented practices. Japanese manufacturing and prod- uct development processes in the assembly industries have been recently recognized worldwide as best practices. The core of their competitiveness has been attributed to continuous improvements made by multiskilled workers who have utilized their extensive experiences in the factory and to extensive interactions among different groups of engineers and workers. In the Japanese best practices model, an impor- tance has been attached to both the workplace and to the actual product in which knowledge at the manufacturing site is highly regarded. Knowledge and skills im-
prove as the result of an accumulation of experiences gained through direct con- tacts with artifacts (we define artifacts as humanmade objects) and through active interpersonal exchanges. It is thought that both tacit and articulated knowledge are created mainly through these experiences and exchanges (Nonaka, 1994).
This human-oriented approach, in which manufacturing and product knowledge is created by sharing a common “field,” has enabled Japanese firms to interpret and apply technology flexibly to varying environments. A common field has been nur- tured by the cooperation between engineers and workers, and the implementation of concurrent engineering has been based on the smooth exchange of information between design engineers and manufacturing engineers. With this human-oriented approach, computers were introduced only as a supportive role.
However, changes are taking place in both the IT and the economic environ- ment that are affecting the competitiveness of the Japanese workplace and human- oriented manufacturing model. The first notable change is the rise in the absolute standard of computer capabilities. From the economic standpoint, there is the en- try into the world market of newly industrializing countries such as the eastern European countries, China, and other Asian countries where labor costs are much lower than in Japan. In addition, because of the increasingly intensifying competi- tion, standards of competition with respect to the speed and efficiency of product development have been raised to unprecedented levels.
In the Western systematic-rationality-oriented model, development and produc- tion processes are integrated primarily through the use of IT. These processes re- flect the Western model of knowledge creation and problem-solving, which is based on pragmatism and an intellectual tradition of analytic rationality. In this model, possible options are analyzed using clearly defined objectives, and the decision- making is a rational process that follows the comparison and review of these op- tions. The ideal state of this systematic-rationality-based model is the systematic management of processes in a decentralized computer environment that utilizes digital information. For example, this approach could enable the establishment of a global production system in which real-time integration of a firm’s worldwide development and production activities can be achieved.
Although for a number of technical and organizational reasons the potential capabilities of IT have not yet been fully realized in the creation of such a world- wide decentralized development and production system, it appears that technical and managerial changes are taking place that will enable the creation of such a system. The limitations in IT that prevented their effective support of the Western systematic-rationality-oriented model are being solved through new generations of IT such as three-dimensional (3-D) CAD. The introduction of new organizational systems, involving, for example, the simplification of organizations and the down- ward transfer of managerial authority, is also being driven by the need for faster and more rational decision-making processes.
This essay suggests implications for both U.S. and Japanese manufacturers. United States firms appear to be the leaders in integrating the U.S. and Japanese approaches.
Leading U.S. manufacturing firms have already begun to learn and adopt aspects of the Japanese model, according to recent studies (Ellison, et al., 1995; MacDuffie and Pil, 1996). Japanese manufacturers, on the other hand, appear to be lagging
significantly behind U.S. firms in the effective implementation of IT. However, al- though both sets of firms are approaching the problem from different directions, it appears that they have the same goal in mind. This essay argues that in both the U.S. and Japanese approaches, the new generation of 3-D CAD systems is the key to successfully introducing the new paradigm of product development.
The next section reviews the evolution of CAD technologies and it defines the key aspects of the new generation of 3-D CAD systems. We then describe two types of conceptual models for knowledge creation in product development, one supported by traditional 2-D CAD systems and the other led by the new 3-D CAD systems. Next, we discuss potential contributions and benefits that the new 3-D CAD system may provide in the product development process. We provide a brief description of the Boeing 777 project as a leading example of how the new generation of 3-D CAD systems can be effectively utilized. Next, we briefly explain usage of CAD systems in the Japanese automobile and shipbuilding industries. Finally, we discuss the nec- essary managerial changes for successfully introducing and fully realizing the bene- fits of the new CAD systems in the product development process.
This study is primarily based on a 1995 and 1996 field study done in Japan.
We interviewed about fourteen managers and engineers in three shipbuilding firms, twenty-two in four automobile firms, eleven in two aircraft firms, and seven in a chip manufacturer. It is very appropriate to study the implementation of CAD in these industries, since they have been the leading users of advanced CAD ap- plications for mechanical products (Kaplinsky, 1982). It is also important to rec- ognize that the influences of CAD tools on design and organizational processes varies greatly depending on the products that are developed (Liker et al., 1992).
Our detailed case studies regarding the automobile, shipbuilding, and chip manu- facturers, available elsewhere, also include detailed descriptions of the firms (Baba and Nobeoka, 1996).
The Evolution of CAD Tools for Product Development
In order to consider the influence of CAD on the product development process, it is necessary both to describe the evolution of CAD tools and to define the specific characteristics of the newest generation of them that will enable the realization of a more effective knowledge-creation process within the product development process. Using an example from the Japanese automobile industry, table 4.1 sum- marizes the three stages in the evolution and the application of CAD systems to product development.
In the beginning of the first stage, called the introduction stage, design engineers began to use CAD tools; almost simultaneously, manufacturing engineers began to use (NC) machines and CAM tools. In this stage, design engineers used CAD tools primarily as an electronic drafting board. The use of CAD significantly improved the efficiency and preciseness of drawing, particularly when engineers were able to develop drawings based on existing ones.
Manufacturing engineers were also able to reduce the number of engineering hours in the design of dies by using digital design data that was received from de-
sign engineers. However, even when components were designed using early ver- sions of 3-D CAD, manufacturing engineers needed to transform the data rather extensively before an effective die design was realized.
In the second stage, called the learning and diffusion stage, design engineers learned to use CAD tools more efficiently, and the tools continued to be adopted in greater numbers. Figure 4.1 shows the diffusion pattern of CAD terminals at a major Japanese automobile firm in which the diffusion pattern follows the classic S-curve.
It took several years for this firm to increase the number of CAD terminals to a suf- ficient level whereby the diffusion speed slowed down. There are about three thou- sand design engineers in total at this firm. On the basis of our interviews with three other Japanese automobile firms, although there are minor differences in terms of time, we have concluded that this pattern is not unique to one firm.
Understandably, CAD usage has gradually increased as the benefits of CAD tools to designers and engineers have continued to increase—from four perspectives.
Table 4.1. An Evolution of CAD Usage in New Product Development
Stage 1. Introduction 2. Diffusion 3. Integration
CAD System 2-D/3-D mixture 2-D/3-D mixture 3-D
Primary purpose Efficiency in drawing Diffusion and learning Real concurrent data transfer to more efficiency and engineering NC machines smoother data transfer
Relationship with Support for efficiency Support for efficiency Fundamental traditional product in drawing and data in drawing and data change in process development process usage for NC machines usage for NC machines
Period (in the case 1970–1985 1985–1995 1995–
of automobile)
Figure 4.1. Number of CAD Terminals at a Japanese Automobile Firm
First, engineers gradually learned to use CAD tools more effectively and efficiently.
Salzman (1989) has reported that it usually takes a relatively long period of time for engineers to learn how to make the most of CAD tools. Second, the CAD tech- nologies continued to improve, in terms of user interface, speed, and stability of the system. Both the learning by designers and the technological improvements gradu- ally improved the benefits of CAD tools over manual drawing boards and helped diffuse CAD systems.
Third, there was also a continuous improvement in data transferability from one application to others. For example, it became much easier to transfer design data into NC data. It also became less time-consuming to create a CAE simulation model using design data. Fourth, because the benefits from CAD tools are greatest when designers can reuse existing drawings, the potential for realizing benefits from CAD increased as more designs were accumulated. Therefore, the benefit of the CAD tools for designers improved as a function of time and experience, and CAD tools contin- ued to diffuse during the second stage.
However, in spite of these improvements, CAD tools were not considered a truly integrated product development tool during this stage in most firms. One of the major reasons for the lack of integration was attributed to the mixture of 2-D and 3-D CAD applications. Different applications are used depending on the different component characteristics even within the development of a single product. For example, among automobile components, exterior body panels began to be designed using 3-D CAD very early, primarily because they had complex curves and needed 3-D representation. However, most other functional components, such as the sus- pension, engine, and transmission, continued to be designed in 2-D CAD, although 3-D models were sometimes used for simulation in CAE.
When only the efficiency of drawing designs is considered, there are many types of components that do not benefit much from 3-D drawings. It takes many more hours to design components using 3-D CAD, at least until the engineers become fully accustomed to 3-D tools. Although the use of 3-D CAD can provide potential bene- fits to other functional groups, such as manufacturing and suppliers, each func- tional group has pursued the improvement of its own efficiency as opposed to im- provements in the system-level performance for the entire product development process.
In the third stage of the evolution of CAD technology, called the integration stage (see table 4.1), all components are designed using 3-D CAD tools, which usually feature 3-D solid modeling features. The same 3-D CAD data are shared by all the engineering functions, including styling and component designers, analytical en- gineers, and manufacturing engineers. For example, the 3-D data that are created by design engineers can be shared and used by manufacturing engineers. In addi- tion, all the components are digitally assembled as a finished product in an early stage of the development project before a real prototype can be available. Digitally assembled data have information regarding topological relationships among the different components as well as manufacturing requirements. Finally, the integrated CAD systems also include the capability for sharing the latest digital data between different computer terminals. Therefore, all the engineers involved in a development project can see the latest design that is being worked on by other engineers.
This essay focuses on the influence of this third stage on knowledge creation in product development. Whenever we use terms like the new 3-D CAD system, or 3-D CAD model, we are referring to this third stage. Although 3-D CAD is not techno- logically new to this stage, digital preassembly and the sharing of digital data among all engineers is new at this point.
Knowledge-Creation Models: 2-D and 3-D CAD Models
In the process of knowledge creation, specific processes of identifying and solving problems play an important role. In order to properly consider the influence of CAD systems on knowledge creation in the product development process, we will first summarize different types of problem-solving processes.
In solving problems, people use several types of logic and reasoning. We classify the logical ones into the following three forms: deduction, induction, and abduction.
The first two are widely used in categorizations of human logic; the third, abduction, was originally advocated by Charles S. Peirce, a nineteenth-century pragmatic phi- losopher, and has been discussed in some studies (Hartshorne and Weiss, 1978).
We argue that because the 3-D CAD system supports the abductive reasoning process of engineers, as well as the deductive and inductive reasoning processes, it will have a fundamentally different impact on knowledge creation in product de- velopment from that of the earlier CAD systems. The earlier versions basically only supported deductive and inductive reasoning processes through their analytical and data-processing capabilities.
In the abductive reasoning process, a person forms a hypothesis that he or she believes provides a unified explanation for the various observed data. Nakajima (1995) argues that the synthesis of knowledge or knowledge creation in designing new products, the diagnosis of design problems, and the product maintenance pro- cesses can all be categorized as abductive reasoning processes.
Yoshikawa (1993) uses an example of house design to explain the abductive rea- soning process. Selecting a design from an unstructured set of alternatives can be considered a major part of the abductive reasoning process. A client expresses his or her desires for the structure, budget, and so on. There may also be conditions related to the circumstances of the land and regulations that should be satisfied in the design of the new house. An architect designs the house on the basis of the client’s needs and conditions, as well as his or her knowledge of architectural tech- nology. The architect first develops a domain where all the needs and conditions are satisfied. He or she then considers design alternatives within the domain. A client’s desires and conditions must be clearly converted to the architecture-related forms so that the architect can judge whether particular design alternatives fall within the domain. Another way to state this is that a major part of the process of designing a house are the attempts to create hypotheses and to verify whether a particular hypothesis consistently fulfills all the requirements. These actions can be classified as an abductive form of reasoning.
Once the domain has been defined (i.e., the design objective and demands have been fully defined), the designer forms a mental picture of a completed design. In
this stage of the design process, engineering or architectural theories, although they provide intellectual support, do not bring about a solution. For example, in the case of developing a photocopying machine, although theories in electrostatic engineer- ing, photoconducting material science, and control engineering all provide a de- sign engineer with knowledge for carrying out deductive reasoning, this knowledge by itself does not bring about a concrete design solution. It is also necessary for the designer to search for a design solution by considering hypothetical design alter- natives. Although these search activities partially utilize deductive reasoning, they are actually abductive reasoning processes (Nakajima, 1995).
A series of recent studies in economics and business administration have revealed that abductive reasoning is acquired through learning by doing or by accumulat- ing aesthetic perceptions nurtured by professional experiences (von Hippel, 1994;
Dosi, Marengo and Fagiolo, 1996; Tyre and von Hippel, 1997). These studies have emphasized that although abduction may accompany a jump in logic and may occasionally lead to wrong hypotheses, human beings can learn from abduction processes and mistakes. When they make mistakes, they find differences between their perceptions and realities. Based on the differences, they modify their mental and intellectual models. They continue this process until the hypothesis is deduc- tively corroborated and objectively recognized as correct.
These abductive reasoning processes can be considered a major part of the learn- ing process. Social scientists may be interested in the roles of abduction in learning and knowledge-creation processes; from engineering and computer scientists may be more interested in the mechanism of the abductive reasoning process.
Although this discussion has focused on unstructured problems whose solution may require abductive reasoning, there are also many structured problems to be solved in product development, problems that can be successively solved mainly through deductive reasoning and sometimes through induction. Computer support is obviously effective and useful for this type of problem-solving. When a designer verifies the viability of a deduced design plan, he or she can analyze a series of de- sign parameters with the support of a database in which designing and drafting rules are encoded.
As seen in such an expert system, it is possible to support deductive reasoning through the systematization of information found in the operation manuals of ex- perts. The knowledge base of an expert system comprises a congregation of if-then rules. If problems fit within these rules, a solution can be found through reasoning that traces a tree structure of rules. When manufacturing knowledge is built into the database, even in metal mold processing where a craftsman’s technique was traditionally required for the delicate finishing process, it is possible for NC data fed into CAM equipment to replace skills embodied in a craftsman. In addition to ex- pert systems, automatic fuzzy control is also effective for deductive reasoning, and as for support for inductive reasoning, a neuron system that promotes modeling by a built-in self-organizing function is known to be effective.
In the 2-D CAD model of knowledge creation, there must be a preexisting prob- lem structure that has been developed using an abductive reasoning process. Solu- tions are then obtained through a series of deductive and inductive reasoning pro- cesses that can be supported by a 2-D CAD model. Information created in this process