Multi-objective optimization of surface roughness, thrust force, and torque produced by novel drill geometries using Taguchi-based GRA

A significant part of today’s chip removal processes are drilling holes. Many parameters such as cutting parameters, material, machine tool, and cutting tool, etc., in the hole-drilling process affect performance indicators such as surface roughness, tool wear, force, torque, energy consumption, and costs etc. While cutting parameters are easily planned by the operator during drilling, the selection and planning of the drill geometry are more difficult. In order to design and produce the new drill geometry, a wide time and engineering research are needed. In this study, the design and fabrication of new drill geometry were performed to improve the hole-drilling performance. The performance of the fabricated drills was judged with regard to surface roughness, thrust force, and drilling torque. In the performance tests, four different drill geometries, four different cutting speed levels, and four different feed rate levels were selected. Holes were drilled on AISI 4140 material. In addition, the optimization was performed in two phases. Firstly, the mono-optimization was carried by using Taguchi’s S/N analysis in which each performance output was optimized separately. Secondly, the multi-objective optimization was employed by using Taguchi-based gray relational analysis (GRA). For the purpose of the study, two different drill geometries were designed and fabricated. Experimental results showed that the designed Geometry 4 is superior to other geometries (geometry 1, geometry 2, and geometry 3) in terms of thrust force and surface roughness. However, in terms of drilling torque, geometry 2 gives better results than other drill geometries. It was found that for all geometries, obtained surface roughness values are lower than the surface roughness values expected from a drilling operation and therefore surface qualities (between 1.2 and 2.4 μm) were satisfactory.