Manish Dadhich

In the present study, the process parameters of WEDM are selected and experimentally investigated for the selective response. In the present research study four process parameters having each three levels, the process parameters are the following: Ton, Toff, current and wire feed. The experiment tables are generated using Taguchi Method separately for both materials. In this research work, three response parameters cutting time, material removal rate and surface roughness are selected. Signal to noise ratio analysis, analysis of variance and multi-objective optimization are performed using stats software Mini-tab. All experiments are carried out on the WEDM machine. Die steel strength is increased by providing extra heat treatment processes in the college workshop. The composite desirability function method is used to find the multi objective optimization results.

The objective of the present work was to investigate the effects of the various WEDM process parameters on the machining quality and to obtain the optimal sets of process parameters so that the quality of machined parts can be optimized. The working ranges and levels of the WEDM process parameters are found using one factor at a time approach. The Taguchi technique has been used to investigate the effects of the WEDM process parameters and subsequently to predict sets of optimal parameters for optimum quality characteristics. The response surface methodology (RSM) in conjunction with the single block and center point design has been used to develop the empirical models for response characteristics.

Using Taguchi method total experiments are required are L16 which are simulated in ANSYS FEM solver (Version-14.5). Proper FEM simulation techniques are applied for these simulation cases and the modeling steps are also developed for this research study. After proper simulation of these cases two responses are selected to optimize this base design for further study. The two response selected from this study is von-misses stress and body weight. In present study various type of analysis is performed both cases like signal to noise ratio analysis, analysis of variance analysis, model equation generation, optimization of this model equation for stress and body weight of hip joint. Visual analysis is also present in this research study. All these major outcomes are present in this research study. Rank identification of factors are also present in this study. The signal to noise ratio analysis for stress shows that the best factor is ball diameter whereas worst factor is neck length of hip joint.