Experimental Investigation and Optimization of Process Parameters on Abrasive Water Jet Machining of Inconel X-750 Superalloy
DOI:
https://doi.org/10.15282/ijame.22.2.2025.6.0943Keywords:
Inconel X-750, Heat resisting alloy, AWJM, Process parameters, Kerf taper, Surface roughnessAbstract
Inconel X-750 is a nickel chromium-based superalloy with various industrial applications due to its exceptional mechanical properties. It is used in aerospace applications, gas turbine rotor components, nuclear power plant parts, etc. Inconel X-750 has a machinability index ranging from 12 to 16, which makes it hard to cut material using traditional machining processes. Therefore, there is a need to find a modern alternative to machine the Inconel X-750 superalloy. Many industries employ well-established Abrasive Waterjet Machining (AWJM) technology to cut different types of materials. However, the applicability of AWJM of Inconel X750 is not available in the scientific domain. Therefore, the objective finalized for the present study is to conduct thorough experimental research and process parameter optimization in the domain AWJM of Inconel X-750. To accomplish the above objective, the impact of process variables, such as water pressure (WP), standoff distance (SOD), and nozzle traverse speed (TS) on important performance indicators, namely material removal rate (MRR), kerf properties and surface roughness (Ra) of machined components. Central composite design (CCD), a Response Surface Methodology (RSM), was used to design the experimental trials in this study. After conducting the experimental trials, the results obtained were assessed for the statistical relevance of the process factors to response characteristics. For this, the well-known statistical approach, i.e., Analysis of Variance (ANOVA), is employed. The findings of the present work suggested that traverse speed is a highly influential factor on Inconel X-750's MRR as well as Ra. The analysis also reveals that TS and WP are key factors influencing the kerf characteristics of the workpiece. To facilitate precise predictions of material performance under the influence of process variables, a regression model has been developed, allowing the prediction of response within the design space. The developed model serves well for optimizing machining conditions, thereby improving the performance of the process. The values predicted for the responses by the model are in good agreement with experimentally obtained response values with permissible error. Post-optimizing the process performance, the optimized process parameters were found to be WP of 380 MPa, TS of 38.6 mm/min, and SOD of 2 mm, which produced a Ra of 4.1μm, the kerf taper angle of 0.4 degrees, and MRR of 907 mm3/min. The optimized parameters yielded satisfactory results.
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