> Modeling, in general, is an important technique in Know-How Engineering (KHE), to collect, represent, consolidate, extend, and to apply know-how in any given application area. CAEBM, like some other modeling methods in KHE, employes a very capable method of modeling, ie Parametric Modeling.
> Experience-Based (EBM), Science-Based (SBM), and Rule-Based Modeling (RBM) point to three different KH-representation methods in modeling. While sciences are developed extraordinarily during history, examples are the most common natural form of men's experiences, and examples are able to represent any kind of KH in any area and from any source, even from dynamic processes. Rules whereas can be arbitrary and often represent given boundaries.
> Today, there is a tremendous over- developement of SBM, compared to EBM and RBM, because of the extraordinary career of sciences in history, and the extensive use of computers especially for SBM (>90%), and on the other hand because of the rather poor natural EBM capabilities of humans, being not able to deal with more than 2-5 parameters in a given problem. As a result, there is a rather big chance to catch up for EBM, if we can extend the human EBM capabilities to more than 2-5 parameters, and even small EBM projects then can make a big difference in today's KHE campaigns. RBM plays a rather marginal role nowerdays, since the expectations in "Expert Systems" had to be reduced drastically over the last decades.
> CAEBM can bring some re-balancing of the use of EBM and SBM, ie the use of experience and science in today's KHE, by extending the restricted human EBM capabilities with the aid of computers, opening the chances to gain new insights in many problem domains.
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