Multi-objective optimisation of single point incremental sheet forming using Taguchi-based grey relational analysis

Incremental forming is a potential process for sheet metal prototyping and low volume production applications. This paper presents the application of Taguchi-based grey relational analysis for optimisation of multiple performance characteristics in single point incremental forming (SPIF) process. In this study, tool diameter, feed rate, shape of the geometry and step depth have been considered as the process parameters with the objective of optimising the maximum wall angle (φmax) and arithmetic mean surface roughness (Ra) simultaneously. The incremental forming experiments have been performed on computer numerical control (CNC) milling machine as per Taguchi L9(34) orthogonal array. The analysis of variance (ANOVA) has been used to understand the effect of process parameters on individual response variables. Further, the grey relational grade has been calculated using the grey relational approach for simultaneous optimisation maximum wall angle and surface roughness. The ANOVA analysis indicated that the step depth is most influential factor on grey relational grade followed by feed rate, tool diameter and shape of the geometry.