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To explore a hybrid approach in order to attain optimal cutting conditions proficient of generating adequate dimensional accuracy in combination with virtuous surface finish during turning of commercially pure titanium (CP-Ti) grade 2.

In the present paper, an application of the hybrid fuzzy–VIKOR method has been proposed to estimate an optimal combination of process variables during turning of commercially pure titanium (CP-Ti) grade 2. Three distinct input factors, namely, cutting speed, feed rate and depth of cut, were selected, each varied at three levels. Thus, a series of experiments were performed based on Taguchi's 3-factor-3-level (L₂₇) orthogonal array. The major attention was given to acquire minimum cutting force and flank wear along with good surface finish. The adequacy of the proposed methodology was verified with the help of ANOVA test.

The results of the investigation revealed that the suggested hybrid technique is quite effective, easily understandable and time-saving approach, which can be successfully implemented to solve various problems either of similar or of different kinds.

Increasing demand of qualitative as well as low cost products is identified as the main challenging task in the current competitive market. Therefore, estimation and selection of the most suitable machining environment are of paramount importance in a real-time manufacturing system. Machining process involves both qualitative and quantitative factors, may be conflicting in nature, all to be considered together. Consequently, an appropriate combination of the machining variables is evidently desirable to meet the aforesaid challenges effectively.

This paper aims to work exhibits the temperature distribution over the surface of the workpiece during plasma arc cutting process.

The moving heat source is taken into consideration for calculating the heat created by plasma arc. The heat is generated at the plasma – liquid metal boundary. The heat of fusion is also considered for estimation because of molten layer separates the plasma and solid layer. This causes to hamper the heat transfer towards the melting front. Eliminating the heat resistance may calculation error at high cutting speed. Power required to melt the material depends on the speed of the cut.

Higher cutting speed increases the power required. The temperature drop over the layer of molten front increases as the speed of cut increases at higher Peclet number. Different thickness of the molten layer was taken for calculation i.e. zero thickness, 10 and 20 per cent.

The estimated results are shown in non-dimensional form. So, the method can be applied for any other types of material.

The purpose of this study aims to obtain excellent products, consistent investigation and manufacturing process control which are the preconditions that organizations have to consider. Nowadays, manufacturing industry apprise process capability index (C_pi) to evaluate the nature of their things with an expect to enhance quality and also to improve the productivity by cutting down the operating cost. In this paper, process capability analysis was applied during wire electrical discharge machining (WEDM) of titanium grade 6, to study the process performance within specific limits.

Four machine input parameters, namely, pulse ON time, pulse OFF time, wire feed and wire tension, were chosen for process capability study. Experiments were carried out according to Taguchi’s L27 orthogonal array. The value of C_pi was evaluated for two machining attributes, namely, average surface roughness and material removal rate (MRR). For these two machining qualities, single response optimization was executed to explore the input settings, which could optimize WEDM process ability.

Optimum parameter settings for average surface roughness and MRR were found to be TON: 115 µs, TOFF: 55 µs, WF: 4 m/min and WT: 6 kg⁻F and TON: 105 µs, TOFF: 60 µs, WF: 4 m/min and WT: 5 kg⁻F.

Process capability analysis constantly checks the process quality through the capability index keep in mind the end goal to guarantee that the items made are complying with the particulars, providing data for product plan and process quality enhancement for designer and engineers, giving the support to decrease the cost of item failures.

In this research, electro discharge machining (EDM) of Ti-5Al-2.5Sn titanium alloy is performed taking gap voltage, pulse on time, peak current and duty cycle as process parameters. The purpose of this paper is to find out the optimal process parameters setting for getting higher machining efficiency.

For experimental design, a face-centered central composite design (FCCCD)-based response surface methodology (RSM) is used. Multi-objective optimization like grey relational analysis (GRA) is adopted to achieve the higher machining efficiency by means of lower radial overcut (ROC), surface roughness (Ra), tool wear rate (TWR) and higher material removal rate (MRR). For the statistical study, analysis of variance (ANOVA) has been carried out.

The result shows that gap voltage, peak current and pulse on time are the most efficient parameters for the responses. An optimal parameter setting has been obtained for achieving higher machining efficiency. For validation of the study, confirmation experiment has been performed at optimal parameters setting.

Optimum parameter level for higher machining performance of Ti-5Al-2.5Sn Titanium alloy has been achieved machined by copper electrode during EDM operation.

The purpose of this paper is to explore a multi-criteria decision-making (MCDM) methodology to determine an optimal combination of process parameters that is capable of generating favorable dimensional accuracy and product quality during turning of commercially pure titanium (CP-Ti) grade 2.

The present paper recommends an optimal combination of cutting parameters with an aim to minimize the cutting force (F_c), surface roughness (R_a), machining temperature (T_m) and to maximize the material removal rate (MRR) after turning of CP-Ti grade 2. This was achieved by the simultaneous optimization of the aforesaid output characteristics (i.e. F_c, R_a, T_m, and MRR) using the MCDM-based TOPSIS method. Taguchi’s L₉ orthogonal array was used for conducting the experiments. The output responses (cutting force: F_c, surface roughness: R_a, machining temperature: T_m and MRR) were integrated together and presented in terms of a single signal-to-noise ratio using the Taguchi method.

The results of the proposed methodology depict that the higher MRR with desirable surface quality and the lower cutting force and machining temperature were observed at a combination of cutting variables as follows: cutting speed of 105 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm. The analysis of variance test was conducted to evaluate the significance level of process parameters. It is evident from the aforesaid test that the depth of cut was the most significant process parameter followed by cutting speed.

The selection of an optimal parametric combination during the machining operation is becoming more challenging as the decision maker has to consider a set of distinct quality characteristics simultaneously. This situation necessitates an efficient decision-making technique to be used during the machining operation. From the past literature, it is noticed that only a few works were reported on the multi-objective optimization of turning parameters using the TOPSIS method so far. Thus, the proposed methodology can help the decision maker and researchers to optimize the multi-objective turning problems effectively in combination with a desirable accuracy.

In this study, powder mixed electro discharge machining (PMEDM) has been performed for the machining of AISI 304 stainless steel by using the tungsten carbide electrode when silicon carbide (SiC) powder is mixed with kerosene. The purpose of this study is to find the optimal value and ascertain the effect of significant machining parameters on surface crack density (SCD) of a machined surface of AISI 304.

A face-centered central composite design-based response surface methodology has been adopted for designing this experiment.

An increase in peak current and powder concentration decreases SCD, which is the main goal of this investigation.

From this investigation, an optimal value has been achieved to minimize the SCD and prevent fatigue and corrosion resistance of the workpiece.

Plasma arc cutting (PAC) is extensively applicable for cutting the materials in faster speed with better accuracy in different manufacturing industries. The cutting of sailhard steel plate plays a great challenge in plasma arc cutting process.

In this investigation, a special abrasion-resistant steel known as sailhard of 20 mm thickness plate has been cut by PAC machine. Cutting current, stand-off distance, cutting speed and gas pressure were selected as cutting parameters. The corresponding responses focused for this study are material removal rate, kerf and chamfer. L30 orthogonal array based on a central composite design (CCD) of response surface methodology (RSM) was used to design the run of the experiment. For predicting and modeling of optimal cutting conditions, a hybrid approach of desirability function-based response surface methodology (DRSM) was acquainted.

The result of this study determines that desirability index (DI) was affected significantly with the machining parameter as well as their interaction. A confirmation test was carried out to analyze the degree of effectiveness of DRSM technique.

In PAC, the selection of process parameters and effect of that parameter on the output responses is of greater value because of the selection of best cutting condition.

Micro-electro discharge machining (EDM) plays an important role in the fabrication of micro holes in an electrically conductive high-strength material. The flushing of debris poses a great challenge in the micro-EDM operation. The vibration of workpiece plays a significant role in the flushing of debris of the workpiece.

This study aims that the finite element analysis is performed using ANSYS software to find out the maximum displacement of the workpiece at a different location at different frequencies. For the convergence of this analysis, the natural frequency obtained from ANSYS is validated with some available literature.

The continuous up and down vibration of the workpiece results in the formation of vapor bubbles in a low-pressure region that contributes to material removal due to the fracture of bubbles. The vibration-assisted workpiece in the micro-EDM process causes the pressure variation of dielectric between the electrode and workpiece that enhances material removal rate because of cavitation.

In workpiece vibration-assisted micro-EDM, the selection of correct vibration frequency and displacement is of greater importance because improper frequency selection can cause bending of the wire electrode, affecting machining stability and short circuiting.