Cutting Tool Condition Monitoring and Validation Using ANN- A Comprehensive Research
Tool life determines the rate of production in machine shop. The acceptance of part depends on how close the specifications of the work part are met. The specification of a part normally comprises of dimensional accuracy in terms of tolerance and surface finish. The performance of tool is also measured in terms of metal removal rate. It is thus becomes imperative to measure the Tool Life. The aim of the present paper is to develop a methodology for collection of real time data and diagnosis of the conditions of tool failure. The method shall include a setup for collection of data under defined cutting conditions and developing appropriate computer software for acquisition and analysis of the relevant data. This Expert system shall contribute towards determination of Tool life in the Real World Usage. The worn out tool affects the accuracy of the work part and also produces machine chatter which further aggravates the problem. The problems due to these are cumulative and difficult to trace in time. The proposed work aims at developing a system to measure the accuracy and surface finish of the work part along with the vibrations generated due to variations in cutting parameters which affects the Tool Life using the intelligent systems. The system shall determine the condition of the tool at any given point. .The intelligent system thus develop shall exhibit the tool performance and predict its failure and determine the Tool Life. Tool life and tool quality are decisive criteria for the successful application of bulk metal forming in industrial production. They directly affect production costs and therefore competitiveness of the process and may as well have a considerable impact on tool supply, stability of production and last but not least delivery performance. Since tool failure is unavoidable, tool life must be properly taken into account for the calculation of tooling cost and planning of tool supply for production.