Abstract
AbstractThe major difficulty faced in a machining process is predicting the failure of cutting tools and analyzing the stipulated time for tool replacement. The former and latter can be achieved through a monitoring system that surveys the effective condition. This present research work is focused on analyzing tool condition by adopting a vibration signature during the machining of a hybrid aluminum alloy composite using various coolants. The experiments were conducted employing various tools under optimum process parameters utilizing vegetable based cutting oil as a coolant. During the machining process, a vibration signature from the workpiece was acquired using an NI 6221 M series DAQ card allowing for various time domain features to be extracted. The arithmetic mean and skewness significantly increased for dull tools. Based on the extracted features, a decision making algorithm for tool condition monitoring system has been proposed. The result shows that the features extracted increased consecutively with an increase in flank wear.
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