Fuzzy-nets-based in-process surface roughness adaptive control system in end-milling operations

Abstract

A fuzzy-nets-based in-process adaptive surface roughness control (FN-ASRC) system was developed to be able to adapt cutting parameters in-process and in a real time fashion to improve the surface roughness of machined parts when the surface roughness quality was not meeting customer requirements in the end-milling operations. The FN-ASRC system was comprised of two sub-systems: (1) fuzzy-nets in-process surface roughness recognition (FN-IPSRR); and (2) fuzzy-nets adaptive feed rate control (FN-AFRC) sub-system. To test the system, while the machining process was taking place, the FN-IPSRR system predicted the surface roughness, which was then compared to the desired surface roughness. If the desired surface roughness was not met, then, the FN-AFRC system proposed a new feed rate for the machining process. Once the feed rate was changed, and the cutting continued, the output of the surface roughness of the new feed rate was compared with the desired surface roughness. This proposed FN-ASRC system has been demonstrated to be successful using 25 experimental tests with 100% success rate.