Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

Abstract

Reaming is one of the finishing processes that has been widely applied in automotive industry. Reaming parameters were evaluated and optimized based on multiple performance characteristics including tool wear and hole quality. Taguchi’s L16, 4-level, 2-factor orthogonal array (OA) was conducted for this test. It was shown that crater wear and flank wear were seen on the tool surface. Furthermore, the crater wear was also of major significance. Hole quality was discovered to be mostly dependent upon cutting speed and feed rate. TiAlN coated carbide reamer shows the best performance with respect to the tool wear as well as hole quality. Grey relational analysis used as a multiple-response optimization technique found that feed rate was the more influential parameter than cutting speed. The goal of the experimental results was to obtain both minimum diametral error and the value of surface roughness by adopting the optimal combination of the reaming parameters.