Analysis of control factors and surface integrity during wire-EDM of Inconel 718 alloy using T-GRA approach

Abstract

In today’s competitive modern manufacturing sectors, there is a vital need of utter precision and rigorous processing using various manufacturing approaches that directly influences the cost and processing duration of mechanized materials in addition to the consistency of the finished products. Therefore, it’s essential to figure out the required output by adjusting the control factors of any machining techniques which resulted in optimal values of the desired outcome. In this study, machining evaluation and process optimization is carried out on volumetric extraction of material namely material removal rate (MRR), kerf obtained during the machining (KW) and surface roughness (SR) of Inconel 718 superalloy during CNC controlled wire- electrical discharge machining. Four controllable factors- pulse interval, wire speed, pulse duration and peak current are considered to investigate the influence on performance measures. Taguchi's L16 has been used to construct the set of experiments before physical experimental runs and most influencing factors have been evaluated using ANOVA. SEM images and EDXS analysis have been resorted to examine the morphology of Inconel 718. These findings assist in identifying the topography of the machined surface. Further, the optimum integration has been obtained for the best yield and recorded using grey relational analysis integrated with Taguchi’s technique (T-GRA). The unfamiliarity of the work is based on consideration of zinc coated thin wire electrode and Taguchi-Grey combined approach of modelling with four levels of experimental design.

Experimental Investigation into the Influence of the Process Parameters of Wire Electric Discharge Machining Using Nimonic-263 Superalloy

“…Because of the greater temperature developed, the workpiece was heated more, and the whole surface of the workpiece became harder due to quenching during the subsequent spark-off. This may be why a significant quantity of heat energy created between the wire material and the test sample due to the greater amount of sparking contributed to rapid erosion and hence an increased material extraction rate [7].…”

“…A greater MRR number suggests a quicker production rate, which is significantly required in the current sectors. A greater MRR is preferable for the WEDM process [7]. The MRR is determined using Equation ( 1) [6]:…”

“…In the modern and technical world, manufacturing is changing dramatically due to customers' increased needs for high-quality, dependable, and better components and products. To address these expectations, companies worldwide have begun to focus on lower-cost solutions in machined components and producing items to maintain their profitability [7,8]. Materials with a high hardness, toughness, impact resistance, strengthto-weight ratio, light weight, outstanding resistance against corrosion, and many other attributes are required in today's mechanical engineering environment.…”

A Review on Role of Ai in Damage Assessment Inlaminated Composite Structures

“…By analyzing data on material properties, design parameters, and performance criteria, machine learning algorithms can generate optimized designs that meet specific requirements and constraints. Overall, implementation of machine learning in damage/failure detection and structural health monitoring has tremendous potential to improve safe operable range, reliability, and performance of laminated composites [17][18][19]70,71] . The article discusses various aspects of damage associated with integrated structures and the smart algorithms related to them.…”