Several software projects are underway, primarily in Germany, to simulate the capabilities of various SFF machines for the purpose of giving users a means of determining which particular rapid prototyping machine (or process) is preferable for a given set of requirements. On the one hand, such projects seem premature, because SFF processes are not well understood, existing process models are incomplete, and new processes and machines continue to be announced. On the other hand, this project can serve as a mechanism for codifying existing RP knowledge and may identify areas for additional research. More importantly, it may also help new users be productive sooner, thereby making SFF more accessible to a broader community. A VR simulation package is being developed at the University of Stuttgart that will provide feedback to the user on the impact of modifications by showing the effect of changing geometry, processes, and so forth. Results will include material buildup and associated stresses, dimensional errors, and material strengths. This is a very ambitious project.
The simulation software under development at the IKP in Stuttgart accepts input data such as part material, surface finish, and desired strength, among other specifications, and selects the RP process required to fabricate the tools, as well as the processing sequence needed to produce the part. These projects recall an interesting Japanese perspective on codification of information, which the panel gleaned during its visit to the IMS Promotion Center in Tokyo (see also Sites, 1996, 60-68), namely, Yoshikawa's categorization of the evolution of technical knowledge.
The categorization, shown in Fig. 8.8, starts with the creation of fundamental knowledge through the basic and applied research stages, which is public domain knowledge. The innovation or new technology stage uses this fundamental knowledge to generate proprietary knowledge for commercial purposes -- including development and manufacture. When islands of this developed technological knowledge achieve widespread use and are thoroughly understood and public, then the knowledge is codified or systematized to reveal missing elements that, in turn, can lead to new basic research. Codification also ensures that this knowledge is not ultimately lost, especially when it lies at interfaces between disciplines.
One modification to this view may be offered: knowledge is not generally created in one large batch process, but perhaps in a more fractal manner, traversing the cycle in many small chunks.