A Numerical Study to Analyze the Effect of Process Parameters on Ring Rolling of Ti-6Al-4V Alloy by Response Surface Methodology

Abstract

Hot ring rolling is a production method to manufacture seamless rings. It is a complex incremental metal-forming process where reduction of cross-section leads to increase in diameter of the ring via circumferential extrusion. High degree of non-linearity and asymmetry is associated with the process. The process results in non-uniform distribution of temperature and plastic strain in the ring cross-section, and this in turn significantly affects the deformation behavior, microstructure, and mechanical properties. Form defect like fishtail defect is also a major concern and incurs loss in terms of labor and machining cost. In this study, rolling of Ti-6Al-4V rings is studied with the help of three-dimensional coupled thermo-mechanical finite element model established using ABAQUS/Explicit environment-based dynamic explicit code. The major parameters taken into consideration for the study are main roll speed (rpm), main roll feed (mm/s), and coefficient of friction. Each parameter was studied at two levels. Twenty simulations with different combinations of major parameters were developed via Central Composite Design (CCD). Coefficient of Variation (CoV) was used as a heterogeneity index to ascertain heterogeneity in equivalent plastic strain (PEEQ) and temperature distribution in the ring. Fishtail defect was quantified using fishtail coefficient as an index. Analysis of variance (ANOVA) was used to ascertain the impact of significant factors and interactions between different parameters affecting the ring rolling process. ANOVA technique requires unrestricted range of (−∞, ∞) for analysis. Hence, logit transformation is used to transform fishtail coefficient present in the range 0–1 to an unrestricted real number range (−∞, ∞). Main roll feed rate was found to be the most significant factor affecting CoV (PEEQ), CoV (temperature) and logit transformation of fishtail coefficient and has an inverse correlation and quadratic relationship with all the responses. Other sources of variation like main roll speed (rpm) and coefficient of friction (CoF) have minimal impact. Increase in feed rate was found to reduce CoV (PEEQ), CoV (temperature), and logit transformation of fishtail coefficient.