Multi-Objective Optimization of Abrasive Water Jet Cutting Using MOGA

Abstract

Abrasive water jet (AWJ) cutting is an unconventional machining process used to cut different types and thicknesses of materials. Cutting process is based on material removal by erosion. Cutting tool is an ultra-fast thin jet of water mixed with abrasive particles. High-speed water jet accelerates the abrasive particles and these particles erode the material. AWJ cutting is a complex process with many factors that determine performances. The most important factors are: water pressure, water flow rate, orifice diameter, nozzle diameter, abrasive mass flow rate, traverse speed and standoff distance. The most important performances are performances related to economy, productivity and quality. Optimizing the AWJ cutting performances is essential in order to obtain better product quality, higher productivity and higher economic efficiency. In process optimization it is logical to take economy and productivity performances as objectives and quality performances as constraints. For the realization of production goal single-objective optimization is a good way, but multi-objective optimization is the right way. In this paper, multi-objective optimization of abrasive water jet cutting carbon steel S235 is studied. Optimization was performed to simultaneously optimize two objectives (productivity and operating cost) with three factors (traverse speed, abrasive mass flow rate and standoff distance) and three constraints (perpendicularity tolerance, surface roughness limit and traverse speed for separation cut). The optimization problem was solved using multi-objective genetic algorithm (MOGA).