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A Consequence Finding Approach for Feature Recognition in CAPP

Knut Hinkelmann
DFKI, DFKI Research Reports (RR), Vol. 94-11, 1994.


We present a rewriting approach for a consequence-finding inference of logic programs. Consequence finding restricts the deriva-tions of a logic program to exactly those facts that depend on an explicitly given set of initial facts. The rewriting approach extends the Generalized Magic Sets rewriting, well-known from deductive data-bases, by an up propagation in addition to the usual down propagation. The initial motivation for this inference was to realize the abstraction phase of a knowledge-based CAPP system for lathe turning. The input to the CAPP system is a detailed description of a workpiece. During the abstraction phase characteristic parts, called features, are recognized for which predefined skeletal plans exist. Consequence finding is a method to restrict the computation such that exactly the features of the actual workpiece are derived. The same inference can also be used for checking integrity constraints: given an update of a deductive database or a logic program, consequence finding applies only those rules that are effected by the update operation.