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The purpose of this paper is to investigate the process parameters and optimise the machining input parameter of powder mixed electric discharge machining for high carbon high chromium alloy steel (D2 steel) for the industrial application. Grey relational analysis approach has been used to obtain the multiple performance output response.

In this experimental work, input parameters, namely, pulse on-time, discharge current, tool material and grit size, are selected. The design of the experiment has been constructed with the help of MINITAB 7 Software, in which L16 orthogonal array has been preferred for the experimentation. The effect of input parameters, namely, material removal rate, tool wear rate and surface roughness, is investigated. Grey relational analysis and analysis of variance are performed to optimise the input parameters and better output results.

In this experimentation, there is an increment of tool wear rate by 64.49 per cent, material removal rate by 47.14 per cent and surface roughness by 35.82 per cent.

A lot of practical applications have been found in many different material processing industries like metallurgy, machinery, electronics, transportation, military science, agricultural machinery, etc. These practical applications have brought forward definite and noticeable economic benefits.

The reader is given a general overview on the machining investigation and optimisation of processes parameters through the grey theory approach. It gives a new framework to investigate the problems where multiple input machining variable and various output responses are obtained in single optimised parameters.

WEAR is one of the major ways by which a material part ceases to be useful, others are corrosion, obsolescence and breakage. It is the consequence of relative motion and in industrial plant and equipment it has always been accepted as inevitable that it should lead to heavy expenditure for maintenance and replacement. Historically, wear is a well established fact, yet our knowledge of the technology is extremely limited. It has become a way of life that we compensate for wear when it no longer can be tolerated, yet need this be so? This article examines the problem, and primarily from the unlubricated point of view, describes the various types of wear and the way material selection or modification can be used to limit wear.

The purpose of this paper is to examine the performance parameters of WEDM to improve the productivity and material removal rate (MRR) with a high surface finish of high chromium-high carbon dies steel.

The experiments were performed on AGIE CUT 220 CNC WEDM. High chromium-high carbon dies steel (D3) was used in the form of a rectangular plate. The workpiece and the brass wire having diameter ɸ 0.25 mm had linked up with +ve and –ve polarity in the DC power source, respectively. De-ionized water having a conductivity level of 0.6 µs/cm was used as the dielectric medium. The dielectric fluid was flushed from the top and bottom nozzles and material was submerged in the dielectric.

The WEDM process parameters for D3 die steel had optimized by using Grey relational analysis method couples with Taguchi method. The optimum solution has been calculated for MRR, cutting speed (Cs), machining time and surface roughness (SR) (Ra value). A fuzzy logic model using Matlab was developed for the prediction of performance parameters, namely MRR, cutting speed (Cs), machining time (M/c time) and SR with respect to changes in input parameters.

The fuzzy model shows the 96.19 percent accuracy between the experimental values and the predicted values.

The optimized parameters by multi-parametric optimization method showed considerable improvement in the process and will facilitate the WEDM, tool and die industries, defense and aerospace industries to improve the productivity with the higher surface finish.

This manuscript represents valid work and the authors have no conflict of interests. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.

This paper aims to clarify the relationship between the slurry erosion and one of the case hardening treatments, i.e. boronizing in this study, for AISI-5117 steel alloy. AISI-5117 steel alloy was used because of its variety applications in the field of submarine equipment. Most of the slurry erosion factors such as velocity, impact angle and mechanism of erosion were studied at different impact angles.

At first, the samples were prepared and subjected to the boronizing treatment in controlled atmosphere. By using a slurry erosion test-rig, all experiments for studying the slurry erosion factors were carried out. Moreover, the studied specimens were investigated via scanning electron microscope, optical microscope and X-ray diffraction to study the erosion mechanism in the different conditions.

It was expected that the boronization of the AISI-5117 steel would increase its slurry erosion resistance due to its positive impact on the surface hardness. However, the results observed show the opposite, where the boronization of AISI-5117 steel decreased its slurry erosion resistance as implied by the increase of the mass loss percentage at all impact angles.

This research, for the first time, exhibits the effect of boronizing treatment on the slurry erosion in different impact factors accompanied by the erosion mechanism at each impact angle.

The problem The resistance to intercrystalline corrosion has been the subject of very thorough investigations. On reading through published research results it is, however, surprising that all the large scale investigations were done on rolled material, whilst information on weld metal is very sparse.

The purpose of this study to identify and optimize the machining of polyvinyl butyral (PVB) material for industrial uses. The research is based on input machining parameters of rotary ultrasonic machining for better understand the output response surface roughness (SR) property of polyvinyl butyral (PVB) by using the Taguchi approach. The grey relational grade analysis (GRG) is also implemented to resolve the complex interrelationship of SR data for optimization and predicting and validate the results.

In experimental work, the input parameters, namely, concentration, abrasives, power rate, grit size, tool material and hydrofluoric (HF) acid has been selected. The experiment’s design was created using MINITAB Software; the L27 orthogonal array was selected for the experimentation. SR was examined with the GRG technique for process optimization. On the other hand, for single parameter optimization analysis of variance (ANOVA) has been used.

ANOVA optimization technique gives the best result on concentration (40%) of abrasive (Al2O3+SiC+B4C), power rate (40%), grit size (600), HF acid (1.5%) and tool material (D2 alloy) are the optimal parameters to provide the slightest degree of SR. GRG optimization of multi-response parameter setting: 40% concentration, SiC+B4C mixed abrasive slurry, 40% of power rating, 280 grit size, 0.5% HF acid and high-speed tool steel tool material gives better results. The SR of PVB glass material improved by 20% after grey relational analysis.

There are several practical applications in a variety of material processing sectors, including metallurgy, machinery, electronics and transportation. These real-world applications have produced substantial and discernible economic benefits.

The analytical and optimization results will be used in the various material processing sectors, including metallurgy, machinery, electronics and transportation.

The ANOVA and grey theory approaches offer the reader a primary picture of the machining research and process parameter optimization. Combined abrasive slurry of Al₂O3+SiC+B₄C with a high power-rating exhibits lower SR. Similarly, grit size is vital; larger grits produce better SR. Ra – 0. 611 m is the lowest SR value at the hole found in trial 25 after the experimentation.

The purpose of this study was to investigate the frictional characteristics of the mechanical seals by using an efficient pairing by providing a suitable lubricant. Among all techniques and lubrication, deposition of solid lubricants on the sliding surface of the mechanical seal was found to be the most effective method to reduce frictional coefficient, frictional force and seal face temperature, thereby increasing the life time of mechanical seal.

In this study, two coatings, diamond-like carbon (DLC) and tungsten carbide/carbon (WC/C), was deposited over the stationary high-carbon high-chromium steel ring paired with resin-impregnated carbon. Their frictional characteristics were studied under various classes of liquid lubricants such as organic liquids, synthetic oil, mineral oil and vegetable oils using an experimental approach. Further, among all classes of liquid lubricants, the one which showed better frictional characteristics was mixed with 0.5, 1 and 2 wt% of potential environmental friendly solid lubricant – boric acid powder.

The high hardness and low surface roughness of DLC- and WC/C-coated seal with the lubricant of palm olein oil containing 1 wt% of boric acid powder contributed a hybrid tribofilm and resulted in low and stable friction coefficient in the range of 0.04-0.05 without any measurable wear.

A pair involving stationary DLC- and WC/C-coated seal ring and resin-impregnated carbon seal rotating ring for the application of mechanical seal was suggested and its frictional characteristics were studied under various classes of lubricants.

The purpose of this paper is to develop an unsupervised classification algorithm including feature selection for industrial product classification with the basic philosophy of a supervised Mahalanobis‐Taguchi System (MTS).

Two novel unsupervised classification algorithms called Unsupervised Mahalanobis Distance Classifier (UNMDC) are developed based on Mahalanobis' distance for identifying “abnormals” as individuals (or, groups) including feature selection. The identification of “abnormals” is based on the concept of threshold value in MTS and the distribution property of Mahalanobis‐D².

The performance of this algorithm, in terms of its efficiency and effectiveness, has been studied thoroughly for three different types of steel product on the basis of its composition and processing parameters. Performance in future diagnosis on the basis of useful features by the new scheme is found quite satisfactory.

This new algorithm is able to identify the set of significant features, which appears to be always a larger class than that of MTS. In industrial environment, this algorithm can be implemented for continuous monitoring of “abnormal” situations along with the general concept of screening “abnormals” either as individuals or as groups during sampling.

The concept of determining threshold for diagnostic purpose is algorithm dependent and independent of the domain knowledge, hence much more flexible in large domain. Multi‐class separation and feature selection in case of detection of abnormals are the special merits of this algorithm.

Tool steel (AISI D3) is a preferred material for industrial usage. Some of the typical applications of D3 tool steel are blanking and forming dies, forming rolls, press tools and punches bushes. It is used under conditions where high resistance to wear or to abrasion is required and also for resistance to heavy pressure rather than to sudden shock is desirable. It is a high carbon and high chromium steel. Therefore, wire electric discharge machining (WEDM) is used to machine this tool steel. The paper aims to discuss these issues.

The present experimental investigation evaluates the influence of cryogenically treated wires on material removal rate (MRR) and surface roughness (SR) for machining of AISI D3 steel using the WEDM process. Two important process responses MRR and SR have been studied as a function of four different control parameters, namely pulse width, time between two pulses, wire mechanical tension and wire feed rate.

It was found that pulse width was the most significant parameter which affects the MRR and SR. Better surface finish was obtained with cryogenically treated zinc coated wire than brass wire.

The review of the literature indicates that there is limited published work on the effect of machining parameters in WEDM in cryogenic treated wires. Therefore, in this research work, it was decided to evaluate the effect of cryogenically treated wires on WEDM.

This study aims to focus on experimenting the performance of aluminum (Al) powder mixed electric discharge machining (PMEDM) of two different materials viz plastic mould die steel (AISI P20) and nickel-based super alloy (Nimonic 75). This experimental study also focuses on using three different tool materials such as copper, brass and tungsten to analyze their influence on the process output. These materials find many uses in industrial as well as aerospace applications. The performance measures considered in this work are material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR).

The experimental design used in this work is based on Taguchi’s L18 orthogonal array. Besides considering work and tool material as one of the process variables, other process variables are peak current (I_p), pulse on time (T_on) and concentration of powder (C_p). The analysis of variance (ANOVA) is performed on the experimental data to determine the significant variables that influence the output.

It is found that copper produced maximum MRR and brass tool exhibited higher TWR. However, the surface finish of the machined work piece was very much improved by using the brass tool. Though the performance of tungsten tool lies between the above two tool materials, it showed very little wear during EDM with or without the addition of Al powder.

The experimental investigation of PMEDM of nickel-based super alloy (Nimonic 75) has not been attempted before. Besides that, the study on the influence of tungsten tool on the performance of EDM is also very limited.