Parametric Optimization of SPIF Process Using Taguchi Method

Authors(3) :-Ganesh Dasharath Khatal, B. R. Borkar, Ghadmode M. M.

The conventional sheet metal forming process need part dependent tooling, which costs in terms of time and money. Due to these factors along with increasing variants, variety in the sheet metal fabrication, highly flexible forming processes are being developed. The incremental sheet forming is one of the emerging flexible forming technologies in the sheet metal engineering, which rather uses universal tooling that is mostly part dependent .Hence the process offer higher flexibility reducing the product development greatly and making it suitable for low volume production. The present work focused on the optimization of the process parameters of the single point incremental forming (SPIF) process on vertical milling machine using Taguchi approach. The main aim of the optimization is to obtain the appropriate surface roughness values in the forming process. Subsequently the mathematical model developed using regression analysis to predict the values of the surface roughness for different products and different values of the predictors.

Authors and Affiliations

Ganesh Dasharath Khatal
Department of Production Engineering, AVCOE, Sangamner, Maharashtra, India
B. R. Borkar
Department of Production Engineering, AVCOE, Sangamner, Maharashtra, India
Ghadmode M. M.
Department of Production Engineering, AVCOE, Sangamner, Maharashtra, India

SPIF, Taguchi, Milling Machine, Surface Roughness

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2016
Date of Publication : 2016-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 65-68
Manuscript Number : IJSRSET162411
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Ganesh Dasharath Khatal, B. R. Borkar, Ghadmode M. M., " Parametric Optimization of SPIF Process Using Taguchi Method, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.65-68, July-August-2016. Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET162411

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