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In the present study, wire electro-discharge machining (WEDM) of Inconel 625 (In-625) is performed with the machining parameter such as spark-on time, spark-off time, wire-speed, wire tension and servo voltage. The purpose of this study is to find the most favorable machining parameter setting with respect to WEDM performance such as material removal rate (MRR) and surface roughness (RA).

Taguchi’s L27 orthogonal array has been used to design the experiments with varying machining parameters into three-level four factors. A hybrid multi-optimization technique has been purposed with grey relation analysis and fuzzy inference system integrated with teaching learning-based optimization to achieve optimum machinability (MRR and RA in present case). The obtained result has been compared with two evolutionary optimization tools via a genetic algorithm and simulated annealing.

It has been found that proposed hybrid technique taking minimum computational time, provide better solution and avoid priority weightage calculation by decision-makers. A confirmation test has been performed at single and multi-optimal parameter settings. The decision-makers have been chosen to select any single or multi-parameter setting as per the industry’s demand.

The proposed optimization technique provides better machinability of In-625 using zinc-coated brass wire electrode during WEDM operation.

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

Ti_49.4Ni_50.6 (at. %) shape memory alloy (SMA) is a unique class of smart materials because of unbeatable property which given a wide variety of their applications across a broad range of fields including an orthopedic implant. It plays a very important role in the constructions of novel orthopedic implants application (like dynamic compression plate) because of lower Young’s modulus compared to other biomedical implant materials, high mechanical strength, excellent corrosion resistance and unique property like shape memory effect. Conventional machining of Ti-Ni yields poor surface finish and low dimensional accuracy of the machined components. Hence, wire electro-discharge machining (WDEM) of Ti-Ni has been performed. The purpose of this paper is to investigate the effect of variation of five process parameters, namely, a pulse-on time, pulse-off time, spark gap set voltage (SV), wire feed and wire tension on the material removal rate, surface roughness (SR), kerf width (KW) and dimensional deviation (DD), in the WDEM of Ti_49.5Ni_50.6 SMA.

The effect of machining parameters on Ti_49.4Ni_50.6 has been fully explored using WEDM with zinc coated brass wire as an electrode. In this work, L18 orthogonal array based on Taguchi method has been used to conduct a series of experiments and statically evaluate the experimental data by the use of the method of analysis of variance. Scanning electron microscope images of the machined surface, at the highest and lowest pulse-on time, have been taken to evaluate the quality of surface in terms of their SR values.

For the highest pulse-on time, it is observed that blow holes, cracks, melted droplets and craters have been formed on the machined surface with an SR of 2.744 µm, while for the lowest pulse-on time, these are not formed with an SR of 0.862 µm. It is seen that the pulse-on time is the most significant process parameter for MRR, SR and KW, while the DD is significantly affected by spark gap SV. The optimal values of the process parameters have been obtained by the method of analysis of mean and the confirmatory experiments have been carried out to validate results of optimization. Energy dispersive spectroscopy analysis of the machined surface of Ti_49.4Ni_50.6 has shown a certain amount of deposition of material on the machined surface.

This is an original paper.

Manufacturing industry worldwide is at a turning point in seeking greater competitiveness. High precision manufacturing offers better quality and reliability for conventional products, but also makes possible entirely new products, especially where mechatronics, miniaturization and high performance are important. Describes the main ultra precision machining processes and illustrates how cutting and grinding have been stretched into the nanotechnology regime, especially for advanced ceramics, glasses and opto‐electronic materials.

The decision-making for additive manufacturing (AM) process selection is typically applied in the end of the product design stages based upon an already finished design. However, due to unique characteristics of AM processes, the part needs to be designed for the specific AM process. This requires potentially feasible AM techniques to be identified in early design stages. This paper aims to develop such a decision-making methodology that can seamlessly be integrated in the product design stages to facilitate AM process selection and assist product/part design.

The decision-making methodology consists of four elements, namely, initial screening, technical evaluation and selection of feasible AM processes, re-evaluation of the feasible process and production machine selection. Prior to the design phase, the methodology determines whether AM production is suitable based on the given design requirements. As the design progresses, a more accurate process selection in terms of technical and economic viability is performed using the analytic hierarchy process technique. Features that would cause potential manufacturability issues and increased production costs will be identified and modified. Finally, a production machine that is best suited for the finished product design is identified.

The methodology was found to be able to facilitate the design process by enabling designers to identify appropriate AM technique and production machine, which was demonstrated in the case study.

This study addresses the gap between the isolated product design and process selection stages by developing the decision-making methodology that can be integrated in product design stages.

This experimental study aims to deal with the improvement of process performance of electric discharge drilling (EDD) for fabricating true blind holes in titanium alloy Ti6Al4V. Micro EDD was performed on Ti6Al4V and blind holes were drilled into the workpiece.

The effects of input parameters (i.e. voltage, capacitance and spindle speed) on responses (i.e. material removal rate, tool wear rate and surface roughness [SR]) were evaluated through response surface methodology. The data was analyzed using analysis of variance and multi-optimization was performed for the optimized set of parameters. The optimized process parameters were then used to drill deeper blind holes.

Blind holes have few characteristics such as SR, taper angle and corner radius. The value of corner radius reflects the quality of the hole produced as well as the amount of tool roundness. The optimized process parameters suggested by the current experimental study lower down the response values (i.e. SR, taper angle and corner radius). The process is found very effective in producing finished blind holes.

This experimental study establishes EDD as a feasible process for the fabrication of truly blind holes in Ti6Al4V.

Titanium has certain properties that make it an ideal material to prevent wear; titanium alloys lend themselves to a versatility of mechanical properties by heat treatment. This should provide a sound tribological combination but, unfortunately, these materials can cause serious galling and fretting. The authors describe the properties of titanium and its alloys, methods of forming and lubricating them and possible methods of combatting wear. In the second part, in our next issue, they will deal with diffusion, electrodeposition, electroless deposition of metallic coatings, and other ways of preventing fretting. In both parts an extensive review of published literature is made and all bibliographical references will be included in our next issue.

The purpose of this study is to investigate the effect of dimple size on the tribological performances of laser surface-textured palm kernel-activated carbon-epoxy (PKAC-E) composite.

A PKAC-E disc 74 mm in diameter was fabricated using the hot compression moulding technique. Five different types of surface contacts were prepared using a CO2 laser surface-texturing machine: a non-textured surface, and surfaces with dimples between 500 and 1,200 μm in diameter. The area density, contact ratio and depth were kept constant. A sliding test was carried out using a ball-on-disc tribometer under boundary lubricated conditions with constant sliding speed, sliding distance and applied load.

In general, the results showed that the friction coefficient decreased with an increasing dimple diameter of surface-textured PKAC-E composite. However, the appropriate dimple diameter for maintaining low friction coefficient is proposed in the range of 800 to 1,000 μm.

This is the first study, to the authors’ knowledge, to investigate the effects of dimple size, which is larger than 500 μm, on the tribological performances of laser surface-textured PKAC-E composite.

The purpose of this study is to investigate the characteristic and function of oxide film formed on grinding wheel in electrolytic in-process dressing (ELID) precision grinding and improve the quality of ELID grinding.

Dynamic film forming experiments were carried out with a simulation device close to the actual processing conditions. Then, the ELID grinding experiments of bearing rings were performed using grinding wheels with good film forming effect. The experiment was designed by quadratic regression general rotation combination method. The influence of grinding depth, electrolytic voltage, duty cycle and grinding wheel linear speed on grinding effect is analyzed.

A mathematical model for the formation rate of oxide film was established. The experiments show that the composition of grinding wheel and grinding fluid, as well as the electrical parameters, influence the film forming effect. Thus, the oxide film plays an important role in ELID grinding.

This study provides a reference for the design and selection of grinding wheel and grinding fluid and the setting of process parameters in ELID grinding.

The purpose of this paper is to optimize the laser-assisted jet electrochemical machining parameters, namely, supply voltage, inter-electrode gap, duty cycle and electrolyte concentration during machining of WC-Co composite using grey relational analysis and fuzzy logic.

In this work, experiments were carried out as per the Taguchi methodology and an L16 orthogonal array was used to study the influence of various combinations of process parameters on material removal rate, hole taper angle and surface roughness height. As a dynamic approach, the multiple response optimization was carried out using grey relational analysis and fuzzy logic.

The process parameters were optimized using grey relational analysis and fuzzy logic for different machining conditions such as balanced manufacturing, high-speed manufacturing and high-quality manufacturing. The research documented in this paper can be scaled up for case studies regarding industrial applications to compare optimization methods for manufacturing processes that are already being carried out.

An attempt to optimize material removal rate, hole taper angle and surface roughness height together by a combined approach of grey relational analysis and fuzzy logic has not been previously done.