Optimization of surface roughness in laser-assisted machining of metal matrix composites using Taguchi method

Abstract

Usually, the surface quality of components produced under turning of particle reinforced metal matrix composites (PRMMCs) is one of the most important factors influencing their practical performance. Keeping good surface quality needs additional manufacturing cost or loss of productivity. In this study, semi-finish turning tests were conducted using high-power diode laser and cemented carbide tools to evaluate the superiority of the laser-assisted machining of PRMMCs and better understand its governing mechanism. The Taguchi method is used to optimize the cutting parameters in laser-assisted machining (LAM) by seeking the smallest surface roughness and the best signal-to-noise ratio. The results of orthogonal experiment revealed that the most significant turning parameter for surface roughness was feed rate, followed by the rotational speed, the cutting temperature, and the depth of cut. LAM provides a larger material removal rates under the same surface roughness compared with conventional machining. The tool wear mechanism for coated and uncoated cemented carbide tools was evaluated, and the LAM provides a maximum 2.31 times improvement in cemented carbide tools over conventional machining. Additionally, an economic analysis reveals significant benefits of diode laser-assisted machining of PRMMCs over conventional machining with conventional carbide tools.