Surface quality of AA7079 sheet through single point incremental forming: experimental investigation and parametric optimization

参数统计 曲面(拓扑) 增量板料成形 点(几何) 材料科学 多点 单点 参数曲面 金属薄板 计算机科学 几何学 复合材料 数学 应用数学 计算机模拟 模拟 统计
作者
Govind Panwar,Dinesh Khanduja,Vikas Upadhyay
出处
期刊:World Journal of Engineering [Emerald Publishing Limited]
标识
DOI:10.1108/wje-07-2024-0396
摘要

Purpose The proposed research primarily focuses on optimizing process parameters to enhance the surface quality of AA7079 material components formed incrementally through the single-point incremental forming process. The study experimentally investigates the influence of selected process inputs on the surface quality of the formed material. Experiments were conducted on AA7079 aluminum alloy sheets under varying conditions of specific process factors, including tool diameter, side-wall angle, rotational speed, feed rate and vertical step size. Design/methodology/approach The experimental investigation has been planned by using the concept of design of experiments (DoE) and is based on trial runs using response surface methodology. The observed data has further been analyzed through analysis of variances analysis and desirability method for highlighting the significant parameters and optimization along with their contribution on surface quality measure, i.e. surface roughness. Findings The side-wall angle, vertical step size, feed rate, rotational speed and forming tool radius have been found to be the major factors that significantly affect the surface roughness. The best value of the SR has been recommended as 0.735 µm under the parametric setting as; tool size (diameter) of 12.291 mm, wall angle of 68.210°, step size of 0.269 mm, speed as 884.672 rpm and a feed rate of 2,791.240 mm/min. Originality/value It has been recommended that greater tool diameter, greater wall angle, smaller steps, higher feed and slower speeds are necessary to improve surface roughness. Out of all the characteristics, tool size is the most important one. In addition, validation trials have been carried out to identify any deviations from the optimal value that was expected.
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