Influence of process parameters on surface roughness and forming time of Al-1100 sheet in incremental sheet metal forming

Swagatika Mohanty; Srinivasa Prakash Regalla; Yendluri Venkata Daseswara Rao

doi:10.15282/jmes.13.2.2019.11.0408

Authors

Swagatika Mohanty Department of Mechanical Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Jawahar Nagar, Shameerpet Mandal, Hyderabad, Telangana, India, 500078. Phone: +91-9676852171
Srinivasa Prakash Regalla Department of Mechanical Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Jawahar Nagar, Shameerpet Mandal, Hyderabad, Telangana, India, 500078. Phone: +91-9676852171
Yendluri Venkata Daseswara Rao Department of Mechanical Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Jawahar Nagar, Shameerpet Mandal, Hyderabad, Telangana, India, 500078. Phone: +91-9676852171

DOI:

https://doi.org/10.15282/jmes.13.2.2019.11.0408

Keywords:

Incremental sheet metal forming, surface roughness, productivity, forming time, Taguchi, ANOVA

Abstract

Product quality and production time are critical constraints in sheet metal forming. These are normally measured in terms of surface roughness and forming time, respectively. Incremental sheet metal forming is considered as most suitable for small batch production specifically because it is a die-less manufacturing process and needs only a simple generic fixture. The surface roughness and forming time depend on several process parameters, among which the wall angle, step depth, feed rate, sheet thickness, and spindle speed have a greater impact on forming time and surface roughness. In the present work, the effect of step depth, feed rate and wall angle on the surface roughness and forming time have been investigated for constant 1.2 mm thick Al-1100 sheet and at a constant spindle speed of 1300 rpm. Since the variable effects of these parameters necessitate multi-objective optimization, the Taguchi L9 orthogonal array has been used to plan the experiments and the significance of parameters and their interactions have been determined using analysis of variance (ANOVA) technique. The optimum response has been brought out using response surfaces. Finally, the findings of response surface method have been validated by conducting additional experiments at the intermediate values of the parameters and these results were found to be in agreement with the predictions of Taguchi method and response surface method.

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