An adaptive sphere-fitting method for sequential tolerance control

The machining of complex parts typically involves a logical and chronological sequence of n operations on m machine tools. Because manufacturing datums cannot always match design constraints, some of the design specifications imposed on the part are usually satisfied by distinct subsets of the n operations prescribed in the process plan. Conventional tolerance control specifies a fixed set point for each operation and a permissible variation about this set point to insure compliance with the specifications, whereas sequential tolerance control (STC) uses real-time measurement information at the completion of one stage to reposition the set point for subsequent operations. However, it has been shown that earlier sphere-fitting methods for STC can lead to inferior solutions when the process distributions are skewed. This paper introduces an extension of STC that uses an adaptive sphere-fitting method that significantly improves the yield in the presence of skewed distributions as well as significantly reducing the computational effort required by earlier probabilistic search methods.

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