Abstract
Titanium alloys find increased applications in many engineering fields such as bio-medical, aerospace, electronics and automobile industries due to their superior physical properties such as high specific strength, weight to strength ratio, corrosive resistant and toughness. Low thermal conductivity of titanium alloys makes it difficult to machine since high cutting temperature is generated at tool work piece interface. As it is highly chemically reactive at high temperature, work piece is adhered to the tool surface. The present work aims at investigating the effect of drilling process parameters viz. spindle speed, drill bit diameter and feed rate on machining performance measures such as burr height at entry and exit, surface roughness and circularity at entry and exit. In order to optimize all the performance measures simultaneously, the present investigation utilizes a hybrid approach known as superiority and inferiority ranking method combined with technique for order preference by similarity to ideal solution (SIR-TOPSIS) to convert these characteristics into single equivalent characteristic ([Formula: see text]-flow). A statistically valid empirical relationship is developed for r-flow in terms of machining parameters using nonlinear regression technique. The study aims at attaining optimal parametric setting that maximizes [Formula: see text]-flow. To optimize [Formula: see text]-flow, an improved version of meta-heuristic evolutionary algorithm known as harmony search (HS) algorithm is implemented. The confirmatory experiment suggests the robustness of the methodology in optimizing the drilling operation.
Published Version
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