J. Mou et Cr. Liu, AN INNOVATIVE APPROACH TO INCREASE THE ACCURACY OF MULTIAXIS MACHINESFOR PROCESS-INTERMITTENT INSPECTION, Journal of manufacturing science and engineering, 118(4), 1996, pp. 585-594
A method for enhancing the effectiveness and robustness of process-int
ermittent inspection is presented. The method is developed first using
mathematical models and measurements closely related to the real part
s, thus reducing the uncertainty in both the error estimation and comp
ensation for multi-axis machines. A predictive search algorithm is the
n developed to identify the minimum number of appropriate measuring po
ints (with respect to the designated tolerance)for arbitrarily shaped
manufacturing parts. The identified measuring points are robust in tha
t they least sensitive to uncertainties in measurement and modeling. T
he search algorithm uses computer simulation with information obtained
from previous measurements. Consequently, the measurement effort invo
lved in error modeling has been greatly reduced The error model derive
d from the method can be used to correct the process-intermittent prob
ing data for a more accurate assessment of workpiece dimensions. Altho
ugh the method is designed for general application in multi-axis machi
nes (i.e., machine tools, robots, and coordinate measuring machines),
this paper focuses on the specific application of a machining center E
xperimental results demonstrate the effectiveness of the error modelin
g method for accuracy improvement of the machining center for process-
intermittent inspection.