Flank wear modeling of a tungsten carbide tip using the GMDH method in turning operation

Abstract

In machining area, the use of conventional ap-proach to develop a reliable method predicting tool wear with a mathematical model based on the plastic defor-mation of the work material cannot always deal to satisfac-tory results. Sometimes the conventional model gives ra-ther large prediction errors by the disturbance into the cut-ting process. This paper deals with the prediction of the tool flank wear in a turning operation using the powerful technique called Group Method of data Handling (GMDH). As a process modeling tool, the GMDH algo-rithm determines a mathematical representation between tool flank wear and the measured variables involved. The GMDH method is said useful for forming a statistical model of a complex multi-variable system using a few pro-cess data. The tool wear model obtained by applying GMDH has considerably high prediction accuracy and indicates the influence of input variables on the cutting tool life. Special care was taken to avoid the influence of the dynamic phenomenon of turning process on the obtained experimental data. The derived model reveals that tool wear and consequently tool life is a complex function ac-cording to cutting parameters: speed, feed and depth of cut.