Prediction of angular error in wire-EDM taper cutting of AISI D2 tool steel by RSM approach

KLU Kiran, P Sarath, K Saraswathamma… - Materials Today …, 2018 - Elsevier
Materials Today: Proceedings, 2018Elsevier
Taper-cutting is one of the most important application of wire electrical discharge machining
(WEDM) process used for producing precise complex geometries with inclined surfaces in
hard material parts that are extremely difficult to machine by conventional machining
process. The wire is subjected to deformation during taper cutting operation leading to
deviations in the angular dimensions and loss of tolerances in machined parts. For the
correction of error time consuming experimental trial-and-error methods are currently …
Abstract
Taper-cutting is one of the most important application of wire electrical discharge machining (WEDM) process used for producing precise complex geometries with inclined surfaces in hard material parts that are extremely difficult to machine by conventional machining process. The wire is subjected to deformation during taper cutting operation leading to deviations in the angular dimensions and loss of tolerances in machined parts. For the correction of error time consuming experimental trial-and-error methods are currently adopted by WEDM machine manufacturers. So, to reduce the experimental load experiments were carried out to find the effect of process parameters such as taper angle, geometrical thickness and servo voltage on response variables such as angular error and cutting speed on AISI D2 tool steel using statistical design of experiments. The experiments were designed using Response Surface Methodology (RSM) – Central Composite design (CCD) involving three variables with five levels. An attempt has been made to develop regression model for relating the responses to the process parameters. Separate analysis of variance (ANOVA) is used to analyze the effect of parameters and contribution of each parameter affecting the responses is calculated. Results show that part thickness and servo voltage are the most influencing variables in the study.
Elsevier
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