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Comparative evaluation of performances of TiAlN, AlCrN, TiAlN/AlCrN coated carbide cutting tools and uncoated carbide cutting tools on turning Inconel 825 alloy using Grey Relational Analysis
, , , Tamiloli N, Sharma N, Srivastava S, Patel A.
Published in Elsevier BV
2018
Volume: 279
   
Pages: 331 - 342
Abstract
This study evaluates the machining performance of nanostructured Titanium Aluminium Nitride (TiAlN), Aluminium Chromium Nitride (AlCrN) and TiAlN/AlCrN bilayer coated and uncoated carbide tools used for machining Inconel 825 alloy. Taguchi's L9 orthogonal experimental design was used in the turning operation by fixing machining parameters namely, cutting speed (v), feed rate (f) and depth of cut (d) at different levels. Taguchi's Response Graph (TRG), Analysis of Variance (ANOVA) and Grey Relational Analysis (GRA) were used for examining the effects of machining parameters and their contributions to the cutting force, tool wear and surface roughness. The optimal cutting parameters were evaluated for “Smaller-the-Better” (STB) quality characteristic of all the three output responses. The GRA results, show AlCrN and TiAlN/AlCrN coated tool having obtained high Grey Relational Grade (GRG) at L1 trial when v = 50 m/min, f = 0.14 mm/rev and d = 0.15 mm. The TiAlN coated tool and uncoated tool obtained high GRG at v = 100 m/min, f = 0.25 mm/rev and d = 0.15 mm for L8 trial. The feed rate showed a high percentage contribution, followed by the depth of cut and cutting speed for TiAlN and AlCrN coated cutting tools based on the ANOVA obtained for GRG values. But, the TiAlN/AlCrN coated and uncoated tool have shown the depth of cut obtaining a high percentage contribution followed by feed rate and cutting speed based on ANOVA obtained for GRG results. Machining studies show a better performance of the TiAlN/AlCrN bi-layer coated tool when compared to TiAlN, AlCrN coated and uncoated carbide tool for machining Inconel 825 alloy. © 2018 Elsevier B.V.
About the journal
JournalData powered by TypesetSensors and Actuators A: Physical
PublisherData powered by TypesetElsevier BV
ISSN0924-4247
Open Access0