Artificial Neural Network Based Tool Condition Monitoring in Machining Applications-An Overview

Tool Condition Monitoring (TCM) is a very important aspect to maintain quality of products manufactured in any machining process. Tool wear is a complex phenomenon occurring in different and varied ways in metal cutting processes. There is a need to identify the tool condition well in advance and take necessary action like replacement, to prevent damaged tools from negatively affecting production in terms of excessive power takeoff, inaccurate tolerances and uneven workpiece surface finish and some times damage to the machine tools and also injury to the operator. There is a need to reliably detect the condition of the tool and take necessary steps. Artificial Neural Networks (ANN) has been widely used for sensor fusion in TCM. This paper presents a brief overview of ANN and followed by it presents an overview of the application of ANN for tool condition monitoring and briefly to other manufacturing processes. Conclusions at the end of the paper contain a brief summary of some of the observations relevant to the application of ANN to TCM.