A review on multi sensor data fusion technique in CNC machining of tailor-made nanocomposites
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A review on multi sensor data fusion technique in CNC machining of tailor‑made nanocomposites K. V. V. N. R. Chandra Mouli1 · Balla Srinivasa Prasad2 · A. V. Sridhar1 · Sandeep Alanka2 Received: 15 October 2019 / Accepted: 10 April 2020 © Springer Nature Switzerland AG 2020
Abstract 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. The sensor signal derives the failure during machining owing to complex cutting tool geometry even in machining of composites. 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. Therefore, it is a challenge to identify the wear features caused during machining of tailor made NMMC’s, reducing wastage and preventing machine malfunction. 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. This can be achieved only with multiple sensor data fusion technique during CNC machining. Keywords Multi-sensor data fusion · Sensors · CNC machining · Nanocomposites · Tool wear
1 Introduction Due 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. Where mandate consistent monitoring of machining is vital in reducing manufacturing cost in less time. 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. The automated machining process in which complex tool path stratagems with intense updated machining techniques such as high-speed milling, drilling turning are in demand. That becomes reasonable for getting complex geometric of the machined product, for instance, precise surface textures. The possession of materials having less finish which are by difficult-to-cut super alloys of titanium, lead to tool failure and wear during machining, forming typical
wear features. Duro et al. [1] intimate from his study that, to prevent the occurrence of wastage in the machining of certain cost allied superalloy components, it is important to intensely find out the workpiece and machine tool malfunctions resulting damage of tool and product machined. The cause of tool damage in any interrupted machining process such as milling operation is mainly, by which tool enter into and exit out of the workpiece several times per second owing to varied chip thickness. This mechanism involves tool disclosed to several thermal and mechanical shocks resulting predominant lopsided tool wear. The rise in the necessity of observing the condition of the cutting tools and workpie
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