IN-PROCESS EVALUATION OF THE OVERALL MACHINING PERFORMANCE IN FINISH-TURNING VIA SINGLE DATA SOURCE

Sensor fusion often uses multiple sensors to evaluate a single quantit y. The work presented in this paper attempts to use information from a single sensor to estimate overall machining performance (characterize d by cutting forces, chip breakability, surface roughness, and dimensi onal deviation due to tool wear). In particular, the performance is ai med at reflecting the in-process changes of the above-named quantities with respect to tool wear progression (major flank, crater and minor flank wear). 3-D cutting force measured by a tool dynamometer is fully utilized by aggregating multivariate time series models and neural ne twork techniques. Dispersion analysis is used to extract signal featur es which correlate well with progressive tool wear. The results have s hown the effectiveness of the proposed method which also has the obvio us merit of simplicity.