The application of a knowledge-based clustering algorithm as an aid to probe selection and inspection process planning

Abstract

This paper outlines the development of a clustering algorithm used for inspection planning which allows each inspection feature to be inspected at a designated cell. This is achieved by grouping (a) inspection features into feature families and (b) probe orientations into probe cells. This would result in minimal probe calibration errors and part installation errors for the relative tolerance features. This procedure would reduce the time for probe exchange and reinstallation of parts. An incidence matrix representation has been developed to represent the relationship between inspection features and their relative probe orientations. The incidence matrix which is used for grouping feature families and probe cells are similar in function to the concept of group technology (GT) as used in machine cell formation. The knowledge-based clustering algorithm possesses the flexibility for consideration of multiple constraints for grouping probe cells and feature families. The application of the developed clustering algorithm satisfies the requirement of the inspection feature grouping and provides efficiency and effectiveness in probe selection and inspection process planning for coordinate measuring machines (CMMs).

Modelling integration of CAD and inspection planning of simple element features

“…CAIP is a major activity within CAPP (Legge, 1996;Marefat et al, 1993;Yau and Meno, 1993;Ziemian and Medeiros, 1997). Therefore, integrating CAD with automated inspection greatly enhances the improvement of products and processes, especially if CAPP, CAIP and NC programming were known to be developed independently (Eversheim et al, 1991;Reimann and Sarkis, 1993;Rogers et al, 1994;Ben-Arieh and Chopra, 1998;Ajmal and Zhang, 1998). Effort for integration faces the problems of different CAD data structures (Gu et al, 1994), redundant data storage, inconsistent database, insufficient representation of technology, and different understanding of CAPP and NCprogramming.…”