By G. Menges, N. Hövelmanns, E. Baur (auth.), Georg Menges, Norbert Hövelmanns, Erwin Baur (eds.)
The current quantity comprises edited models of the communications offered at a global Workshop on "Expert structures in construction Engineering", held in Spa, Belgium, in 1986. Introductory papers on synthetic Intelligence and professional structures are complemented by way of case experiences of professional structures in perform, essentially, within the zone of Mechanical Engineering and discussions of the probabilities and the restrictions of specialist Systems.
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Additional info for Expert Systems in Production Engineering: Proceedings of the International Workshop, Spa, Belgium, August 18–22, 1986
Sample text
In addition to this, all (real) objects and concepts being important for the "inspection plan generation" are defined as (formal) objects with a list of attributes belonging to them, respectively. Attributes stand either for a proberty of an object or a relation between two objects. Beside these static structures LESP dynamically generates descriptions within different abstraction levels for finding out the best suggestion. The basic reasoning structures used by LESP are abstraction and windowing.
M; or b) Pli>=P2i for all i element of l .. m, n>m. If more than one common, direct predecessor-node for a pair of processing states exists, mutual larger depths must be taken into consideration, additionally. For doing this in a concise manner such a similarity measure can only be defined in a special, product spectrum dependent way. Fig. 6 illustrates the functioning of the defined similarity measure. The considered screw is round-top-screw(RTS)-8/80. LESP tries to find out the most similar screws.
P2m, such that either a) n=m, Plj>P2j for a j element of l .. n, Pli>=P2i for all i<>j, i element of l .. m; or b) Pli>=P2i for all i element of l .. m, n>m. If more than one common, direct predecessor-node for a pair of processing states exists, mutual larger depths must be taken into consideration, additionally. For doing this in a concise manner such a similarity measure can only be defined in a special, product spectrum dependent way. Fig. 6 illustrates the functioning of the defined similarity measure.