No abstract

The current study aims at investigating the influence of different machining parameters such as cutting speed (V c ), feed (f) and depth of cut (t) on different performance measures during dry turning of AISI 304 austenitic stainless steel. ISO P30 grade uncoated cemented carbide inserts was used a cutting tool for the current purpose. L27 orthogonal array design of experiments was adopted with the following machining parameters: V c = 25, 35, 45 m/min., f= 0.1, 0.15, 0.2 mm/rev. and t= 1, 1.25, 1.5 mm. Three important characteristics of machinability such as material removal rate (MRR), cutting force (F c ) and surface roughness (R a ) were measured. Attempt was further made to simultaneously optimize the machining parameters using grey relational analysis. The recommended parametric combination based on the studied performance criteria (i.e. MRR, F c and R a ) was found to be V c =45m/min, f=0.1mm/rev, t=1.25mm. A confirmatory test was also carried out to support the analysis and an improvement of 88.78% in grey relational grade (GRG) was observed.

Keywords:AISI P20 tool steel Grey-fuzzy logic Multi-response optimization Surface integrity Electric discharge machining a b s t r a c t Surface integrity remains one of the major areas of concern in electric discharge machining (EDM). During the current study, grey-fuzzy logic-based hybrid optimization technique is utilized to determine the optimal settings of EDM process parameters with an aim to improve surface integrity aspects after EDM of AISI P20 tool steel. The experiment is designed using response surface methodology (RSM) considering discharge current (Ip), pulse-on time (T on ), tool-work time (T w ) and tool-lift time (T up ) as process parameters. Various surface integrity characteristics such as white layer thickness (WLT), surface crack density (SCD) and surface roughness (SR) are considered during the current research work. Grey relational analysis (GRA) combined with fuzzy-logic is used to determine grey fuzzy reasoning grade (GFRG). The optimal solution based on this analysis is found to be Ip ¼ 1 A, T on ¼ 10 ms, T w ¼ 0.2 s, and T up ¼ 0.0 s. Analysis of variance (ANOVA) results clearly indicate that T on is the most contributing parameter followed by Ip, for multiple performance characteristics of surface integrity.

No abstract

No abstract