REVIEW AND OPTIMIZATION OF TOOL WEAR IN TURNING OPERATIONS

V diplomski nalogi so predstavljene veličine, ki vplivajo na optimiranje obstojnosti pri struženju. Opisane in prikazane so metode, s katerimi pridemo do realnih rezultatov ob uporabi določene baze podatkov in upoštevanjem medsebojnega vpliva obdelovanec, orodje, vpenjalo, stroj in hladilno mazalno sredstvo. Za prikaz optimiranja so uporabljeni analitični modeli ter prikaz modelov umetne inteligence (nevronske mreže, genetski algoritem). Podani so principi zajemanja signalov pri odrezavanju ter vključitev teh signalov v sistem adaptivnega optimiranja krmilja ter procesa.In this work I have considered all parameters that influence the optimization of tool wear in turning. I have presented the methods that help us come to realistic results when considering specific databases and the correlation of the cutting tool, work piece, clamping, machine and cooling fluid. An analytic and artificial intelligence models (neutral network and genetic algorithm) have been used for the optimization modeling. There is also an overview of data acquisition and the use of this data in an adaptive control optimization model