Dirk Pons

Context—Rapidly solidified aluminium alloy (RSA 443) is increasingly used in the manufacturing of optical mold inserts because of its fine nanostructure, relatively low cost, excellent thermal properties, and high hardness. However, RSA 443 is challenging for single-point diamond machining because the high silicon content mitigates against good surface finishes. Objectives—The objectives were to investigate multiple different ways to optimize the process parameters for optimal surface roughness on diamond-turned aluminium alloy RSA 443. The response surface equation was used as input to three different artificial intelligence tools, namely genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE), which were then compared. Results—The surface roughness machinability of RSA443 in single-point diamond turning was primarily determined by cutting speed, and secondly, cutting feed rate, with cutting depth being less important. The optimal conditions for the best surface finish Ra = 14.02 nm were found to be at the maximum rotational speed of 3000 rpm, cutting feed rate of 4.84 mm/min, and depth of cut of 14.52 µm with optimizing error of 3.2%. Regarding optimization techniques, the genetic algorithm performed best, then differential evolution, and finally particle swarm optimization. Originality—The study determines optimal diamond machining parameters for RSA 443, and identifies the superiority of GA above PSO and DE as optimization methods. The principles have the potential to be applied to other materials (e.g., in the RSA family) and machining processes (e.g., turning, milling).