Abstract
The conventional process of machining of nitinol alloy which possesses excess strain hardening and low thermal conductivity makes a complex process that leads to extensive wear on the tool and inadequate surface quality. Wire-electro-discharge machining (WEDM) is widely accepted for machining this alloy involving various input factors, namely, P (pulse-on-duration), Q (pulse-off-duration), C, (maximum-current), and V (voltage). Using the PSO (particle swarm optimization) method, the effect of WEDM process factors on multiresponses such as MRR (metal removal rate) and SR (surface roughness) has been investigated. ANOVA was used to create a relationship model between input factors and response characteristics, which was then optimized using response surface methods (RSM). ANOVA revealed that variables A and C are the most significant. When investigated individually, the influence of WEDM process parameters on SR and MRR is contradictory, as no response provides the best process quality. To find the optimal ideal condition for decreasing SR and maximizing MRR, the MOOPSO approach was used. P = 25.47051 μs, Q = 10.84998 μs, C = 2.026317 A, and V = 49.50757 volts were used to calculate the optimal universal solution for machining characteristics (MRRmax = 3.536791 mm3/min and SRmin = 1.822372 μm). PSO enhanced MRR and SR for every optimal combination of variables, according to the findings. Based on the findings, a wide range of optimal settings for achieving maximum MRR and minimum SR are given, depending on the product requirements.
Highlights
A meta-analysis showed that there have been no systematic investigations of the input parameters influencing the surface finish and MRR of nitinol alloy using the Wire-electro-discharge machining (WEDM) method
WEDM was used to prepare workpieces composed of nitinol alloy, a commercially accessible material. e construction of numerical models is crucial in the manufacturing process if parts are to be developed quickly and at a lowest machining cost
Where Z is the output characteristic to be optimized, and h is the objective function, which includes both dependent and independent factors a1, a2, a3, . . ., an, as well as error correction. e Taguchi design approach was used to optimize WEDM factors involved in the machining of an aluminum alloy 5754 produced by friction-stir-welding for experimentation planning in an orthogonal array format to take all conceivable various combinations of variables and their levels [27]
Summary
WEDM was used to prepare workpieces composed of nitinol alloy (nickel-titanium alloy), a commercially accessible material. e construction of numerical models is crucial in the manufacturing process if parts are to be developed quickly and at a lowest machining cost. All of the trials on nitinol parts using CNC wire cut EDM employed 0.2 mm diameter molybdenum (Mo) wire as the electrode material. When it comes to making complex geometries parts for aerospace and missiles, Mo wire has a number of benefits, including a high melting temperature and ultimate strength. Converging to the Pareto front for ideal global-optimized solutions group and supporting variation and scattering in solutions are two goals of the MOOPSO. Nondominated (ND) solutions are solutions that can improve any response by worsening one or more individual responses. e goal of running a MOO is to get a collection of ND solutions that stabilize the transaction amid completely different responses, which is known as a Pareto set. e proposed effort entails maximizing MRR while lowering SR
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