Process monitoring and effects of process parameters on responses in turn-milling operations based on SN ratio and ANOVA

Process monitoring in machining constitutes machine performance and machine condition for performing the desired objective. The optimality and effect of machining parameters on machine performance monitoring in tangential and orthogonal turn-milling processes is been studied. Surface Roughness (Ra) and Surface Hardness (H) has been taken as machine performance responses and Tool Vibrations (VIB) as machine condition monitoring response. Laser Doppler Vibrometer (LDV) is used for online capturing of tool vibrations and is analyzed using VibSoft analyzer for processing Acousto-optic emissions (AOE). Single cut machining on A-axis of CNC Vertical Milling center using HSS end mill cutters is adopted. Process parameters like cutter (tool) speed, feed rate and depth of cut with constant rotation of workpiece on A-axis are chosen while machining Brass material under dry condition. Statistical design of experiments (DOE) based on Taguchi’s Orthogonal Array (OA) is adopted for experimentation and Signal-to-Noise ratio (SN ratio) of the responses is used for finding optimality of process parameters. The influence and contribution of the process parameters on the responses is been studied with help of Analysis of Variance (ANOVA).

[1]  Vedat Savas,et al.  The Optimization of Cutting Parameters for Surface Roughness in Tangential Turn- milling using Taguchi Method , 2012 .

[2]  Sounak Kumar Choudhury,et al.  Investigation in orthogonal turn-milling towards better surface finish , 2005 .

[3]  Vedat Savas,et al.  Analysis of the surface roughness of tangential turn-milling for machining with end milling cutter , 2007 .

[4]  K Venkata Rao,et al.  Experimental study on surface roughness and vibration of workpiece in boring of AISI 1040 steels , 2015 .

[5]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[6]  S. R. S. Kalpakjian.  Manufacturing Processes for Engineering Materials , 1984 .

[7]  Herbert Schulz,et al.  Turn-milling of hardened steel: an alternative to turning , 1994 .

[8]  Tarek Mabrouki,et al.  Finite-element-based hybrid dynamic cutting model for aluminium alloy milling , 2010 .

[9]  Noureddine Zerhouni,et al.  The ISO 13381-1 standard's failure prognostics process through an example , 2010, 2010 Prognostics and System Health Management Conference.

[10]  Sounak Kumar Choudhury,et al.  Investigation of orthogonal turn-milling for the machining of rotationally symmetrical work pieces , 2000 .

[11]  Vedat Savas,et al.  The optimization of the surface roughness in the process of tangential turn-milling using genetic algorithm , 2008 .

[12]  Clarence W. de Silva.  Vibration Signal Analysis , 2006 .

[13]  B.S.N. Murthy,et al.  Cutting tool condition monitoring by analyzing surface roughness, work piece vibration and volume of metal removed for AISI 1040 steel in boring , 2013 .

[14]  Yuji Sugiyama,et al.  Experimental Analysis of Chatter Vibration in End-Milling Using Laser Doppler Vibrometers , 2008, Int. J. Autom. Technol..