Abstract

Improving machining performance with reduced power consumption is a big challenge for the manufacturer to reduce production cost. Since the dead metal zone (DMZ) directly affects the cutting forces, the present study aims to optimize the DMZ to reduce the cutting and thrust forces in the micro-milling of hardened AISI D2 steel using teaching–learning-based optimization technique (TLBO). Finite element model for DMZ geometry and mechanistic models for cutting and thrust forces are developed, integrated and estimated the cutting and thrust forces. The estimated forces are compared with experimental results and a good agreement found between them. In the next stage, process parameters (cutting speed and feed per tooth) and tool parameters (nose radius and rake angle) are optimized using TLBO technique to minimize DMZ geometry keeping the surface roughness (≤ 2 µm), tool wear (≤ 30 µm) and amplitude of cutter vibration (≤ 30 µm) as constraints. The optimal working condition is as follows: a spindle speed of 2225 rpm, a feed per tooth of 5.0 µm, and a nose radius of 7.6 µm and rake angle of 3.0°. Under the optimal working condition, side length of DMZ and DMZ angle is found as 13.8 mm and 5.74°, respectively, and the cutting and thrust forces are estimated as 3.27 and 2.37 N, respectively. These cutting and thrust forces are about 21.3–65.7 and 34.8–55.3%, respectively, less than the experimental results.

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