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Grey relational analysis (GRA) has already proved itself as an efficient tool for multi-objective optimization of many of the machining processes. In GRA, the distinguishing coefficient (ξ) plays an important role in identifying the optimal parametric combinations of the machining processes and almost all the past researchers have considered its value as 0.5. In this paper, based on past experimental data, the application of GRA is extended to dynamic GRA (DGRA) to optimize two electrochemical machining (ECM) processes.

Instead of a static distinguishing coefficient, this paper considers dynamic distinguishing coefficient for each of the responses for both the ECM processes under consideration. Based on these coefficients, the application of DGRA leads to determination of the dynamic grey relational grade (DGRG) and grey relational standard deviation (GRSD), helping in initial ranking of the alternative experimental trials. Considering the ranks obtained by DGRG and GRSD, a composite rank in terms of rank product score is obtained, aiding in final rankings of the experimental trials for both the ECM processes.

In the first example, the maximum material removal rate (MRR) would be obtained at an optimal combination of ECM parameters as electrolyte concentration = 2 mol/l, voltage = 16V and current = 4A, while another parametric intermix as electrolyte concentration = 2 mol/l, voltage = 14V and current = 2A would result in minimum radial overcut and delamination. For the second example, an optimal combination of ECM parameters as electrode temperature = 30°C, voltage = 12V, duty cycle = 90% and electrolyte concentration = 15 g/l would simultaneously maximize MRR and minimize surface roughness and conicity.

In this paper, two ECM operations are optimized using a newly developed but yet to be popular multi-objective optimization tool in the form of the DGRA technique. For both the examples, the derived rankings of the ECM experiments exactly match with those obtained by the past researchers. Thus, DGRA can be effectively adopted to solve parametric optimization problems in any of the machining processes.

Utilizing electrical discharge machining (EDM) to process micro-holes in superalloys may lead to the formation of remelting layers and micro-cracks on the machined surface. This work proposes a method of composite processing of EDM and ultrasonic vibration drilling for machining precision micro-holes in complex positions of superalloys.

A six-axis computer numerical control (CNC) machine tool was developed, whose software control system adopted a real-time control architecture that integrates electrical discharge and ultrasonic vibration drilling. Among them, the CNC system software was developed based on Windows + RTX architecture, which could process the real-time processing state received by the hardware terminal and adjust the processing state. Based on the SoC (System on Chip) technology, an architecture for a pulse generator was developed. The circuit of the pulse generator was designed and implemented. Additionally, a composite mechanical system was engineered for both drilling and EDM. Two sets of control boards were designed for the hardware terminal. One set was the EDM discharge control board, which detected the discharge state and provided the pulse waveform for turning on the transistor. The other was a relay control card based on STM32, which could meet the switch between EDM and ultrasonic vibration, and used the Modbus protocol to communicate with the machining control software.

The mechanical structure of the designed composite machine tool can effectively avoid interference between the EDM spindle and the drilling spindle. The removal rate of the remelting layer on 1.5 mm single crystal superalloys after composite processing can reach over 90%. The average processing time per millimeter was 55 s, and the measured inner surface roughness of the hole was less than 1.6 µm, which realized the  micro-hole machining without remelting layer, heat affected zone and micro-cracks in the single crystal superalloy.

The test results proved that the key techniques developed in this paper were suite for micro-hole machining of special materials.

The purpose of this study is to explore the machining characteristics of electrical discharge machining (EDM) when a tool is fabricated using powder metallurgy. Because pure Cu tools obtained using conventional machining pose problems of high tool wear rate, tool oxidation causes loss of characteristics in tool shape.

The research investigation carried out experiments planned through Taguchi’s robust design of experiments and used analysis of variance (ANOVA) to carry out statistical analysis.

It has been found that copper and chromium electrodes give less metal removal rate as compared to the pure Cu tool. Analytical outcomes of ANOVA demonstrated that MRR is notably affected by the variable’s polarity, peak current, pulse on time and electrode type in the machining of EN9 steel with EDM, whereas the variables pulse on time, gap voltage and electrode type have a significant influence on EWR. Furthermore, the process also showed that the use of powder metallurgy tool effectively reduces the value of SR of the machined surface as well as the tool wear rate. The investigation exhibited the possibility of the use of powder metallurgy electrodes to upgrade the machining efficiency of EDM process.

There is no major limitation or implication of this study. However, the composition of the powders used in powder metallurgy for the fabrication of tools needs to be precisely controlled with careful control of process variables during subsequent fabrication of electrodes.

To the best of the authors’ knowledge, this is the first study that investigates the effectiveness of copper and chromium electrodes/tools fabricated by means of powder metallurgy in EDM of EN9 steel. The effectiveness of the tool is assessed in terms of productivity, as well as accuracy measures of MRR and surface roughness of the components in EDM machining.

The purpose of this paper is to investigate the friction and wear mechanisms in lubricated sliding conditions of additively manufactured SS316L parts. The different viscous oils 5W30, 15W40, 20W50 and SAE140 are used. These investigations provide a theoretical basis for the high performance of printed and postheattreated SS316L.

Tribological tests were carried out on selective laser melting-made SS316L printed specimens and heat-treated specimens. The parameters in 15 min of test duration are 20 N of load, 200 rpm, 8 mm of pin diameter, 25 mm length, 80 mm of track diameter and EN31 counter disc body. This work presented the phenomena of lubrication regimes and their characterization, as identified by the Stribeck curve, and these regimes affect the tribological properties of additively manufactured SS316L under the influence of industrial viscous lubricants. The results are observed using Scanning electron microscope (SEM), X-ray diffraction (XRD) and wear tests.

The observations indicate that additively manufactured SS316L shows a reduced coefficient of friction (COF) and specific wear rate (SWR). This is credited to the utilization of different viscous lubricants.

This exclusive research demonstrates how various viscous lubricants affect the COF and SWR of printed and post-heat-treated SS316L parts. Lambda (λ), lubricant film thickness (h₀), surface roughness and wear mechanisms are studied and reported.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0110/

This paper aims to investigate the corrosion kinetics and corrosion behavior of NdFeB magnets with the addition of heavy rare earth dysprosium (Dy) for its inhibitory activity on poor corrosion resistance of NdFeB magnets.

To study the effect of dysprosium addition on corrosion behavior of NdFeB magnets and investigate its mechanism, potentiodynamic polarization, scanning electron microscopy (SEM), electrochemical impedance, energy dispersion spectrum (EDS) and scanning Kelvin probe force microscopy (SKPFM) were applied in the research. Besides, microstructures were observed by SEM equipped with EDS. Atomic force microscopy was introduced to analyze the morphology, potential image as well as the contact potential difference. The SKPFM mapping scan was applied to obtain the contact potential around Nd-rich phase at 0.1 Hz. The magnets were detected via X-ray diffraction.

Substitution of Nd with Dy led to improvement of corrosion resistance and reduced the potential difference between matrix and Nd-rich phase. Corrosion resistance is Nd-rich phase < the void < metal matrix; maximum potential difference between matrix and Nd-rich phase of Dy = 0, Dy = 3 and Dy = 6 Wt.% is 411.3, 279.4 and 255.8 mV, respectively. The corrosion rate of NdFeB magnet with 6 Wt.% Dy is about 67% of that without Dy at steady corrosion stage. The addition of Dy markedly enhanced the corrosion resistance of NdFeB magnets.

This research innovatively investigates the effect of adding heavy rare earth Dy to NdFeB permanent magnets on magnetic properties, as well as their effects on microstructure, phase structure and most importantly on corrosion resistance. Most scholars are studying the effect of element addition on magnetic properties but not on corrosion resistance. This paper creatively fills this research gap. NdFeB magnets are applied in smart cars, robotics, AI intelligence, etc. The in-depth research on corrosion resistance by adding heavy rare earths has made significant and outstanding contributions to promoting the rapid development of the rare earth industry.

This study aims to investigate the influences of Al₂O₃ mass fraction on the corrosive wear and electrochemical behaviors of FeAl–xAl₂O₃ coatings.

FeAl–xAl₂O₃ coatings were prepared on S355 steel by laser cladding to improve its corrosive wear and electrochemical properties.

The average coefficients of friction and wear rates of FeAl–xAl₂O₃ coatings are decreased with the Al₂O₃ mass fraction, and the Al₂O₃ plays a positive role in the corrosion wear resistance. Moreover, the charge transfer resistance of FeAl–xAl₂O₃ coatings is increased with the Al₂O₃ mass fraction, showing the FeAl–15%Al₂O₃ coating has the best corrosion resistance. The findings show the corrosion resistance of FeAl–15%Al₂O₃ coating is the highest among the three kinds of coatings.

Al₂O₃ was first added into FeAl coatings to further improve its corrosive wear and electrochemical properties by laser cladding.

Hexavalent chromium has been a benchmark corrosion inhibitor before it was phased out because of its carcinogenic properties. However, because it was phased out, many alternative corrosion inhibitors have been introduced but failed to meet the performance of this benchmark inhibitor. Consequently, benzotriazole (BTA) was reported to exhibit chromate-like inhibition performance. Subsequently, Intelli-ion was reported by researchers to exhibit chromate-like performance also with claims of being a unique alternative. This paper aims to review the inhibition performance of these two alternatives. Above all, promotes the unique inhibition performance of Intelli-ion that makes it suitable for application in many sectors.

In this paper, the corrosion inhibition performances of BTA and Intelli-ion were compared systematically by reviewing some related literatures based on the opinion of the authors.

Different methodologies for measuring the inhibition performance of BTA showed that it’s an inhibitor of choice. However, the cut edge corrosion performance of Intelli-ion and BTA corrosion inhibitors on galvanized steel of 55% Wt.% Al, 44% Wt.% Zn and 1% Wt.% Si in 5 Wt.% NaCl solution was compared when subjected to scanning vibrating electrode technique (SVET) for 24 h. The results showed faint blue-colored region depicting negative cathodic current density for the Intelli-ion while there was a high-intensity of red-colored region depicting a positive anodic current density for BTA. In other words, the Intelli-ion inhibitor had a better overall cut-edge corrosion inhibition performance than the BTA inhibitor.

This paper compares and further, summarizes the corrosion inhibition performance of Intelli-ion and BTA by evaluating SVET results from the literature. In addition, it serves as an overview and reference for the unique inhibition performance of Intelli-ion when applied in field applications.

This paper aims to examine dissimilar joints for various applications in chemical, petrochemical, oil, gas, shipbuilding, defense, rail and nuclear industry.

This study examined the effects of cold metal transfer welding on stainless steel welds for 316L austenitic and 430 ferritic dissimilar welds with ER316L, ER309L and without (autogenous) fillers. The microstructural observation was done with an optical microscope. The mechanical test was done to reveal the strength, hardness and toughness of the joint. The electrochemical polarization tests were done to reveal intergranular and pitting corrosion in the dissimilar joints.

This microstructural study shows the presence of austenitic and ferritic phases with vermicular ferrite for ER309L filler weld, and for ER316L filler weld specimen shows predominately martensitic phase in the weld region, whereas the autogenous weld shows lathy ferrite mixed with martensitic phase. Mechanical test results indicated that filler welded specimen (ER316L and ER309L) has relatively higher strength and hardness than the autogenous weld, whereas ER316L filler weld exhibited the highest impact toughness than ER309L filler weld and lowest in autogenous weld. The electrochemical corrosion results displayed the highest degree of sensitization (DOS) in without filler welded specimen (45.62%) and lower in case of filler welded specimen ER309L (4.95%) and least in case of ER316L filler welded specimen (3.51%). The high DOS in non-filler welded specimen is correlated with the chromium carbide formation. The non-filler welded specimen shows the highest pitting corrosion attack as compared to the ER316L filler weld specimen and relatively better in ER309L filler welded specimen. The highest pitting corrosion resistance is related with the high chromium content in ER309L composition.

This experimental study is original and conducted with 316L and 430 stainless steel with ER316L, ER309 and without fillers, which will help the oil, shipbuilding and chemical industries.

This study aims to assess support vector machine (SVM) models' predictive ability to estimate half-cell potential (HCP) values from input parameters by using Bayesian optimization, grid search and random search.

A data set with 1,134 rows and 6 columns is used for principal component analysis (PCA) to minimize dimensionality and preserve 95% of explained variance. HCP is output from temperature, age, relative humidity, X and Y lengths. Root mean square error (RMSE), R-squared, mean squared error (MSE), mean absolute error, prediction speed and training time are used to measure model effectiveness. SHAPLEY analysis is also executed.

The study reveals variations in predictive performance across different optimization methods, with RMSE values ranging from 18.365 to 30.205 and R-squared values spanning from 0.88 to 0.96. Additionally, differences in training times, prediction speeds and model complexities are observed, highlighting the trade-offs between model accuracy and computational efficiency.

This study contributes to the understanding of SVM model efficacy in HCP prediction, emphasizing the importance of optimization techniques, model complexity and dimensionality reduction methods such as PCA.

This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard.

A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes.

Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup.

The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries.

A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.