Optimization using GRA for MS Grade through Fiber Laser Cutting Process

Abstract

Laser beam machining (LBM) is one of the most widely used thermal energy based non-contact
type advance machining process which can be applied for almost whole range of materials. This work studied
the performance of fiber laser cutting of mild steel. The experiment was focused on the cut quality with
surface roughness and kerf width with two assistant gases pressure. After analysis the cutting result, several
conclusions were made. Although the best result got in the experiment is not perfect as predicted, the whole
result of the test can be accepted. This work an application of the grey relational analysis (GRA) to directly
optimize laser cutting of a mild steel sheet using two performance characteristics. From twenty seven
experiments based on the orthogonal array of L27, an O2 pressure of 1 bar, a N2 pressure of 15 bar, and a laser
power of 1100 watt were found to be the best parameters for laser cutting of a mild steel with two assistant
gases pressure. Moreover, the analysis of variance (ANOVA) is also employed to determine the contribution
of each control parameter on the cut quality characteristics. The three largest measured contributions on the
cut quality in decreasing order are the O2 pressure, the N2 pressure, and the laser power. The optimal
combination from both the GRA and the Taguchi methods from 27 experiments is the same. Finally,
confirmation experiments are performed to ensure the robustness of the GRA predicted optimal configuration
for laser cutting of mild steel. Compared with single assist gas laser, a higher cutting speed was achieved by
fiber laser with two assistant gases pressure.