LAUSR

Abrasive waterjet machining (AWJM) is one of the versatile unconventional machining processes presently followed in several industries in the machining of variety of engineering materials. Achieving maximum depth of penetration is a prime requirement to achieve higher productivity. As the AWJM involves several process variables, selecting the right combinations of process variables to achieve maximum depth of cut (h) is a cumbersome and time-consuming process. Thus, scientific way of choosing process variables is being attempted by many researchers through suitable modeling techniques. This paper focuses on the development of semi-empirical model using Buckingham’s π theorem to predict the depth of cut (h) during AWJM of unreinforced and reinforced aluminum metal matrix composites (MMCs) and is compared with regression model and experimental data. Experiments were designed according to Box–Behnken method, and cutting trials were performed on unreinforced aluminum and 5%, 10% and 15% volume fraction of boron carbide (B4C)-reinforced 6063 aluminum alloys, MMCs by keeping the process parameters of water pressure (p), mesh size (ms), mass flow rate (ma) and traverse speed (u) each at three levels. The experimental results of depth of cut (h) at different levels of process parameters were analyzed through ANOVA. Based on the experimental results, the combinations such as #80 mesh size, 340 g/min mass flow rate, 200 MPa water pressure and 60 mm/min traverse speed, resulted in higher depth of cut (h). The experimental, semi-empirical and regression models were compared. The models’ predictions are in good agreement with the experimental data under the corresponding conditions.