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Analysis and optimization of process parameter intervals for surface quality in polishing Ti-6Al-4V blisk blade

Zhen Chen, Yaoyao Shi, Xiaojun Lin and 5 more

Results in Physics · 2019

doi:10.1016/j.rinp.2018.12.056 (opens in a new tab)

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Abstract

As the predominant factor influencing the service performance and life cycle of finished parts, surface quality is always improved by polishing technology in the machining process of aero-engine blade. The reasonable selection of polishing process parameter intervals have significant impact on surface quality, which is critically bound up with the performances of finished blade. In this paper, two different characteristic values of surface quality, including morphology feature (surface roughness) and stress property (residual stress), were analyzed respectively. To obtain the global optimal parameter intervals for surface quality improvement in Ti-6Al-4V blade polishing process, the comprehensive analysis methods were presented in this paper. In order to develop the prediction models of surface roughness and residual stress, regression analysis was conducted based on the results of Central-Composite designed polishing experiments. The significance and adequacy of the developed model was verified by using the analysis of variance (ANOVA). The sensitivity analysis was carried out to evaluate the influence of polishing process parameters on surface quality. Subsequently, stability interval and instability interval were divided according to sensitivity curves. Finally, the optimization method of process parameter intervals was proposed and the comprehensive optimal intervals were obtained. The experiments were carried out to verify the developed prediction models and the obtained global optimal parameter intervals. The results of polishing confirmation experiments indicated that the surface-quality-oriented optimal intervals of polishing process parameters were dependable. Keywords: Ti-6Al-4V blade, Surface quality, Polishing parameters, Surface roughness, Residual stress, Sensitivity analysis

Abstract licence: CC BY-NC

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