SAMPLING STRATEGY DESIGN FOR DIMENSIONAL MEASUREMENT OF GEOMETRIC FEATURES USING COORDINATE MEASURING MACHINE

Dimensional measurement using a coordinate measuring machine (CMM) has been commonly adapted in advanced manufacturing environments to ensur e that manufacturing products have high quality and reliability. To co nduct dimensional inspection effectively in a computer-integrated manu facturing (CIM) environment there is an urgent need to derive a sampli ng strategy which can be used to specify a set of measuring points tha t lead to accurate sampling while minimizing the sampling time and cos t. Owing to the variations in characteristics of geometric features an d manufacturing processes, different feature surfaces on a workpiece u sually have different variations in their dimensional accuracy and sur face finish. The variations may differ considerably from one surface t o another, even though those surfaces may share the same feature. Ther efore, the variation in dimensional accuracy and surface finish should be considered in determining the proper sampling size for each geomet ric feature generated by various processes with different production p arameters. In this paper, a feature-based methodology which integrates the Hammersley sequence and a stratified sampling method are develope d to derive the sampling strategy far various geometric features which have specified measuring points. Case studies are used to compare the effectiveness of Hammersley sequence sampling, uniform (systematic) s ampling and random sampling. The results show that the derived samplin g strategy based on the Hammersley sequence leads to a nearly quadrati c reduction in the number of samples compared with the uniform samplin g method, and hence units of time and cost, while maintaining the same level of accuracy. The derived sampling strategy also shows a better performance when compared with the random sampling method. (C) 1997 El sevier Science Ltd.