Experimental estimation and numerical optimization of \u2018cylindricity\u2019 error in flow forming of H30 aluminium alloy tubes

Abstract

The present article analyses the influence of flow forming input parameters on the development of “cylindricity error” in H30 aluminum alloy seamless tubes fabricated by a single pass reverse flow forming process. Measurement and control of geometrical precision in terms of cylindricity encompassing straightness and roundness are critical for the success of component manufacturing by flow forming. The experimental trials with a predefined range of input parameters conforming to the full factorial design of experiments approach have been performed, and corresponding cylindricity data have been recorded as the outcome. An empirical relation has been established between the input parameters and the cylindricity. It has been established that cylindricity value increases sharply with an increase in axial stagger contributing 39% to the outcome, whereas the percentage contributions of in-feed and feed-speed ratio are found to be less than 1%. The adequacy of the proposed model has further been analyzed and validated through the confirmation tests. In order to obtain better control over the overall process towards achieving higher productivity and accuracy, 2 meta-heuristic optimization algorithms namely, teaching and learning-based algorithm and genetic algorithm have been utilized for optimization of input process parameters to minimize cylindricity error. Both the algorithms predict that a combination of higher feed rate and lower value of axial stagger and in-feed parameters is essential to achieve the lowest cylindricity error in H30 Al alloy. Confirmatory experimental trials have been carried out to validate both the regression model and optimization, and have been found to agree well with the model predictions described herein.