The analysis of high-pressure water jet cutting of thick aluminium alloy 6061-T651 from a statistical perspective

Abstract

The main context in which abrasive water cutting is used is the reduction of thermal deformation induced by thermal (plasma arc PAC, oxyfuel OFC, laser) of electrothermal (electroerosion EDM) cutting methods. Although it is not the cheapest or time-efficient technique it can be used on a wide variety of metallic and non-metallic materials. Among other benefits are the lack of burrs, high precision and improved surface finish, low setup time and stress-free cutting. This leads to no secondary processing required in many other applications. Depending on the material hardness the cutting thickness can reach up to 300 [mm]. The present study proposes an analysis of high-pressure abrasive water jet cutting of a 19 [mm] thick plate. The aluminium alloy used in this study was Al-6061-T651. This alloy is being used especially in the aeronautics industry due to is excellent welding properties. The experiments were conducted using multiple input and output factors. The design of experiments (DOE) takes into account input factors and offers models for responses. The study was organised according to response surface methodology, with an I-optimal design type and a quadratic design model. The input factors were: cutting pressure, standoff distance, programmed quality of the cut. The responses analysed were: entrance (Iw) and exit (Ow) width of cut, and taper angle (α). An ANOVA analysis was performed for each response. This interpretation implies the significance (p-value) that the input factors have on the variation of the responses. For Iw and Ow a reduced 2FI model was proposed, while for θ a linear model was suggested. The p-value obtained for each response is smaller than 0.0001, which classifies the models as significant. The ANOVA fit statistics determine the R-squared error between 0.964 and 0.995, meaning that the responses are well defined by the input value variations. This high confidence in the results leads to accurate mathematical models.