The necessity of less dependency on the operator is essential in order to eradicate error and cost with less lead time, which will lead towards the automated machining till today. Where mandate consistent monitoring of machining is vital in reducing manufacturing cost in less time. This can be achieved only with multiple sensor data fusion technique during CNC machining.ĭue to the intense prerequisite of varied products and fall in the life of products, there is a crucial demand to increase the quality and quantity of manufacturing products. This paper presents a comprehensive review on the machining strategies in extreme output conditions which rely on input parameters of speed, feed and depth of cut influencing tool life during CNC machining. Therefore, it is a challenge to identify the wear features caused during machining of tailor made NMMC’s, reducing wastage and preventing machine malfunction. Nano metal matrix composites (NMMC) being extremely upright in mechanical characteristics, consequently machining of these hybrid nano metal matrix composites reinforced with difficult-to-cut nano particles leads to reduced tool life thereby causing rapid flank wear. The sensor signal derives the failure during machining owing to complex cutting tool geometry even in machining of composites.

In this study, a multiple sensor data fusion system is anticipated as essential for monitoring of cutting operations, by identifying suitable sensor locations to obtain feedback signals periodically.

Fusion cnc