Optimal Parametric Conditions Research Articles

Nutrient recovery from manure digestate by using waste magnesite powder and bone meal as sustainable substitutes for struvite precipitation

AbstractBACKGROUNDStruvite (MgNH4PO4.6H2O) precipitation is a sustainable approach that can offer simultaneous removal/recovery of nutrients from biogas plant effluents. However, most biogas plant effluents contain a higher molar concentration of nitrogen (N) than magnesium (Mg) and phosphorus (P). Therefore, the external addition of Mg2+ and phosphate (PO43‐) salts is needed to maximize the recovery. In this study, Mg‐rich waste magnesite powder and P‐rich bone meal were used as sustainable additives. The Box–Behnken design was applied to determine optimum conditions of process parameters (pH, Mg:N and P:N molar ratios) to maximize ammonium‐nitrogen (NH4‐N), PO4‐P and Mg2+recoveries.RESULTSNH4‐N, PO4‐P and Mg2+ recoveries were in the ranges 78.5%–96.9%, 69.2%–96.3% and 75.1%–99.9%, respectively. The actual and predicted values showed significant consistency, indicating that the model is satisfactory. Under optimum conditions (pH = 9.0, Mg:N = 2.2, P:N = 1.8), 97.8 ± 0.1% NH4‐N, 96.6 ± 0.31% PO4‐P and 84.4 ± 0.9% Mg2+ recovery were attained. The X‐ray diffraction results confirmed the sole presence of struvite crystals. Scanning electron microscopy images showed irregular prismatic orthorhombic crystals and amorphous material depositions on precipitates of ~25 μm crystal size. The product was 49% struvite with 15.2% P content. The heavy metal content was lower than regulatory limits.CONCLUSIONEven though waste material and industrial by‐products have been used as additives in this process, high NH4‐N and PO4‐P recoveries were recorded under optimum conditions. These results are promising and illustrate a powerful example of industrial symbiosis, and the precipitate containing struvite can serve as a valuable product. © 2024 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).

An improvement in the mechanical properties of polypropylene/ethylene-propylene-diene monomer/titanium dioxide nanocomposite obtained by fused filament fabrication

In the present research, the PP/EPDM/TiO2 nanocomposite was fabricated using the fused filament fabrication process to improve the mechanical properties of the obtained samples. For this purpose, first the response surface methodology was used to investigate the effect of TiO2 content, nozzle temperature and printing speed on the responses of tensile strength and elongation. Then, the desirability function method was applied to find the optimal condition of the process parameters. The fracture surface of the tensile samples was also studied by scanning electron microscopy, differential scanning calorimetry and thermogravimetric analysis to find a relationship between the microstructure and mechanical properties of the fabricated samples. The results indicated that the highest elongation of samples (144.9%) was attained at a TiO2 content of 4 wt%, while the tensile strength of samples was maximized (24.6 MPa) at a TiO2 content of 2 wt% due to fine dispersion of the nanoparticles. An increase in the nozzle temperature from 200 to 225°C led to an enhancement in the tensile strength (11.2%) and elongation (15.7%) of samples because of the good viscosity of the filament, whereas the tensile strength (6.6%) and elongation (11.1%) of samples were decreased with the increase of nozzle temperature from 225 to 250°C because of the thermal degradation of filament. Moreover, when the printing speed raised from 20 to 40 mm/s, the tensile strength initially improved by 2.7% and then decreased by 1.2%, but the elongation continuously decreased by 6.3%. Nevertheless, the concurrent enhancement of the tensile strength and elongation has been obtained at a TiO2 content of 2.5 wt%, nozzle temperature of 227°C and printing speed of 28 mm/s.

Spatiotemporal reshaping of femtosecond laser pulses on interaction with gas sheath at ionization saturation intensity regime

Interaction of intense ultrashort laser pulse with gases generates a transient spatiotemporal electron density distribution via field ionization, which may lead to the spatiotemporal reshaping of the pulse, viz., its beam profile, pulse width, etc. Here, we present an experimental study on ultrashort laser pulse interaction with argon gas sheath in an ionization saturation intensity regime (∼1015–1017 W/cm2). The present investigation has been performed using a 6 mJ, 1 kHz, and 55−60 fs Ti:Sapphire laser pulse interaction with a ∼2.5 mm long argon sheath. After the laser gas interaction, the laser spatial profile exhibits a multi-ring structure around a central maximum spot. Laser gas interaction parameters, such as laser intensity, gas pressure, etc., affect the ring pattern significantly. Under optimum parameter conditions, the laser pulse has two rings in spatial profile, and the pulse width of the central spot is self-compressed to ∼35 fs. A theoretical calculation reveals that the laser beam’s spatiotemporal profile evolves as it propagates inside the gas sheath. The calculation also demonstrates that the gas ionization profile plays a crucial role in the spatiotemporal reshaping and self-compression of the laser beam. The calculation also shows that the generation of concentric ring patterns in the spatial profile is mainly due to the ionization of argon atoms into Ar+, Ar2+, and Ar3+ species in the interaction region. Such self-compressed laser pulses with concentric ring beam profiles may be useful for high-harmonic generation and shorter attosecond pulse trains.

MICRO-EDM OF TI–6AL–4V USING VARIOUS TOOL MATERIALS: MULTI-RESPONSE OPTIMIZATION AND SURFACE CHARACTERIZATION

In this paper, experimental analysis was performed during micro-electrical discharge machining (micro-EDM) of titanium alloy Ti–6Al–4V (grade 5) using three types of tools viz. copper (Cu) tool, tungsten carbide (WC) tool, and synthetic graphite (Gr) grade three tool. The main process parameters were taken as (a) pulse on time ([Formula: see text]), (b) pulse off time ([Formula: see text]), (c) voltage (V), and (d) capacitance (C). The output responses were taken as the material removal rate (MRR) and tool wear rate (TWR). Taguchi method coupled with grey relational analysis (GRA) (L[Formula: see text] orthogonal array) technique was applied to optimize the input process parameters for both the responses. Scanning electron microscopy (SEM) analysis of the workpiece and tool was also performed to investigate the morphology of the machined surface and tool surface. Energy-dispersive spectroscopy (EDS) analysis was performed to investigate the elemental composition of the machined surface. The experimental finding reveals that tungsten carbide is the most suitable tool material for machining the chosen workpiece for obtaining optimal MRR and TWR. The optimum condition for the copper tool was found as 180[Formula: see text]V, 1000[Formula: see text]pf, 10[Formula: see text][Formula: see text]s ([Formula: see text]), and 10[Formula: see text][Formula: see text]s ([Formula: see text]). Meanwhile, the optimum parametric condition for tungsten carbide and graphite tools was found to be the same as 240[Formula: see text]V, 100[Formula: see text]pf, 20[Formula: see text][Formula: see text]s ([Formula: see text]), and 5[Formula: see text][Formula: see text]s ([Formula: see text]).

Strategic enzymatic biodegradation of pharmaceutical pollutant carbamazepine by bacteria Rhodococcus zopfii

Carbamazepine is frequently detected in wastewater, impacts human health and the environment. This study evaluates the biodegradation of carbamazepine by Gram-positive bacteria Rhodococcus zopfii, specifically optimum biodegradation conditions and extracellular enzyme roles. The carbamazepine biodegradation optimization and bacteria growth for initial concentrations of carbamazepine, pH and temperatures were investigated. Extracellular enzyme assays were also examined. For the carbamazepine biodegradation, the optimum initial concentration, pH and temperature were at 10 mgL-1, pH 7 and 40 ℃, respectively with the carbamazepine biodegradation percentages ranging from 99.92 ± 0.04 % to 99.98 ± 0.14 %. The optimum parameter conditions for the bacteria growth were 5 mgL-1, pH 7 and 40 ℃ with a range from 9.61 ± 0.01 log CFUmL-1 to 10.35 ± 0.00 log CFUmL-1. The bacteria growth and the carbamazepine biodegradation occurred sequentially, with the bacteria growth preceding the carbamazepine biodegradation. The highest extracellular enzyme secreted by R. zopfii was aldehyde oxidase, followed by oxygen oxidoreductase, catechol 1,2 dioxygenase and catechol 2,3 dioxygenase. At the early of the biodegradation, oxygen oxidoreductase and aldehyde oxidase were secreted, then followed by catechol 1,2 dioxygenase and catechol 2,3 dioxygenase. A linear correlation between oxygen oxidoreductase with the biodegradation of carbamazepine was identified. Such phenomenon revealed R. zopfii metabolised carbon from the phenolic compound, thus reducing carbamazepine toxicity for defence and biodegradation mechanisms compared to growth. This study provides vital information for the biodegradation of carbamazepine using Gram-positive bacteria R. zopfii as a sustainable technology, mimics nature that is beneficial for wastewater treatment management and industry application.

Process parameters optimization and performance analysis of micro-complex geometry machining on Ti6Al4V

AbstractThe aeronautical industry relies on high-performance equipment that demands materials with exceptional engineering attributes, such as the Ti6Al4V alloy. However, the complexity of the parts used in these applications presents challenges related to stack-up tolerances during assembly. Therefore, conventional machining processes are not economically viable due to their two-step nature solution (machining and surface treatment) and their inability to achieve the required accuracy level, particularly given the alloy’s hard-to-cut nature. In this matter, wire electric discharge machining (WEDM) emerges as an attractive alternative for fabricating complex geometries. This research focuses on evaluating the potential of the WEDM process for machining micro-complex profiles. A comprehensive range of process parameters, including servo voltage (Vs), pulse on time (Ton), pulse off time (Toff), and wire speed (Ws), are studied using a Taguchi-based design of experiments. The results are analyzed through parametric significance analysis, parametric control analysis, surface morphological analysis using scanning electron microscopy, and modified layer analysis. Additionally, both mono-objective and multi-objective process optimization techniques are employed to achieve superior accuracy and speed. The findings indicate that Ton and Ws have the most significant influence on both cutting speed and spark gap, whereas Vs and Toff play a crucial role in determining the accuracy index. In addition, adequate flushing, reduced wire speed (economically viable), and stability of the spark are recommended to attain a lower spark gap and higher accuracy. The confirmatory experiments show that the optimal parametric conditions of Vs = 60 V, Toff = 30 μs, Ton = 8 μs, and Ws = 6 mm/s provide the highest speed of 3.4 mm/min, minimum spark gap of 0.344 mm, and accuracy index of 98.72%. The findings will contribute to enhancing manufacturing efficiency, precision, and cost-effectiveness in the aeronautical industry, meeting the demand for high-quality components with tight tolerances.

A feed-regulated water-only cyclone for improving the separation performance of clean coal from coal slime

Due to the challenges of separation and high costs, coal slime is often directly burned without further separation processing, leading to environmental pollution. Therefore, a feed-regulated water-only cyclone has been proposed to improve the coal slime separation efficiency by controlling the suspended bed. This method optimizes particle characteristics by incorporating a pre-desliming hydrocyclone, the characteristics of particles were optimized to regulate the hindered settling in suspension layer. Response surface experiments were conducted to investigate the impact of structural parameters on separation efficiency, Additionally, under optimal parameter conditions, particle size and density were characterized, and a simulation analysis was conducted using CFD–EDEM. The results showed that the maximum separation efficiency achieved in the experiment was 35.31%. Particle characterization analysis also revealed that, after feed regulation, the proportion of particles with a size of 0.045 mm within high density exceeded 75%. Industrial application experiments demonstrated the feasibility of obtaining a high-quality coal product with over screen yield of 9.29% and an ash content of 9.47%. This transformation of coal slurry into a valuable resource has generated significant economic benefits for enterprises and will address the environmental pollution issue caused by direct combustion and improper disposal.

Investigation of process parameters influence in waterjet peening of AZ31B-Mg alloy for bioimplant applications

The main objective of the study is to investigate the effects of parameters standoff-distance, waterjet pressure, traverse speed and number of passes used in the waterjet peening process on AZ31B-Mg alloy to assess surface grain refinement's potential and to improve the alloy's functionality in the biological environment, followed by the study of enhancement in hardening and roughening effect on AZ31B-Mg alloy surface. The optimal parametric condition required for investigating surface texture, X-ray diffraction analysis and electrochemical corrosion analysis with simulated body fluid was obtained through the multi-criteria optimisation, Technique for Order of Preference by Similarity to the Ideal Solution, which employs microhardness and surface roughness as response variables. The obtained results show significant improvement in mechanical and corrosion-inhibiting features of AZ31B-Mg alloy. Further, the biocompatibility of waterjet peened and unpeened surfaces was examined using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-tetrazolium bromide assay and fluorescence analysis with MG63 cell lines.

Green hairy basil seed mucilage biosorbent for dispersive solid phase extraction enrichment of tetracyclines in bovine milk samples followed by HPLC analysis

Unmodified hairy basil seed mucilage (Ocimum basilicum L.), with attractive features as structural functionality and adsorption capacity, was employed as a green biosorbent for dispersive solid phase extraction and enrichment of oxytetracycline, tetracycline, and doxycycline before quantitation by HPLC-UV for the first time. Hairy basil crushed seed increased the contacting surface area and was completely dispersed in the sample solution to extract tetracyclines under acidic condition with the assistance of ultrasonic waves. The analytes in the extraction phase were separated on a C18 column under isocratic condition with a mobile phase consisted of acetonitrile and trifluoroacetic acid. Influence of chemical and physical variables on the extraction efficiency of the developed method was investigated and optimized systematically. Under the optimal condition of all experimental parameters, good linear ranges were obtained at 15.0–500 μg L−1 for tetracyclines with determination coefficients more than 0.9994. Limits of detection (LODs) and limits of quantitation (LOQs) ranged 5.0–7.0 and 15.0 μg L−1, respectively. Relative standard deviations (RSDs) of the proposed method at 100 and 300 μg L−1 for TCs were less than 13 % and 10 %, respectively with percentage TC recoveries from spiked standard ranging 83.1–109.9 %. This simple, reliable, cost-effective, and environmentally friendly method was successfully applied for the analysis of tetracycline residues in milk. The greenness of the proposed method was assessed using the Analytical Eco-Scale and AGREE protocol.

Analytical optimization of open hole effects on the tensile properties of SS400 sheet specimens using an integrated FFD-CRITIC-DFA method

Structural components are generally composed of material discontinuities, including open holes, which are considered stress concentrators in engineering components. In view of this, assessing the influence of open holes on the tensile properties is crucial to determine the sensitivity and tensile strength of a particular material. Nevertheless, investigation of the impact of open holes on the tensile properties of SS400 steel sheets is very limited and yet to be explored. Therefore, this study was performed to optimize the effects of open holes on the tensile properties of SS400 sheet specimens based on a Full Factorial Design (FFD) experiment. Four input parameters that represent various hole configurations, which include the hole diameter, location of the hole, number of holes, and hole shape, were considered in this study to develop the experimental-based prediction models to optimize the output performance, namely yield strength, ultimate tensile strength, and ultimate elongation, commonly denoted as YS, UTS, and UE respectively. A total of 10 additional experimental trials were then utilized to verify the constructed models. In addition, the weight fractions for YS, UTS, and UE were identified using the Criteria Importance Through Inter-Criteria Correlation (CRITIC) method. Subsequently, the Desirability Function Analysis (DFA) is utilized to pinpoint the optimal parameter conditions for maximizing the tensile properties. Based on the results, all four parameters showed significant effects on the response variables, except the number of holes for UTS and hole location for UE. The diameter also recorded the highest contribution toward UTS and UE, followed by the hole shape. Regarding YS, hole diameter takes precedence, with the number of holes as the second most influential factor. Furthermore, the average absolute percent deviation for the prediction responses of 10 experimental cases were 1.06 %, 0.90 %, and 0.85 % for YS, UTS, and UE, respectively, confirming the validity of the constructed models. Meanwhile, the CRITIC method estimated the weight fractions for YS, UTS and UE from the experimental data, which were 0.3825, 0.2559, and 0.3616, respectively. The DFA-derived composite desirability, rated at 0.9820, suggests optimal conditions: a 1 mm hole diameter, centered hole location, three holes, and a hexagonal shape. The minimal deviations between predicted and experimental values affirm the robustness of the models. Overall, this investigation yields important insights for optimizing open holes and elevating the tensile performance of SS400 sheet specimens.

Optimization of ohmic parameters in enzyme assisted aqueous extraction for better physico-chemical properties of the black cumin seed oil

This study was carried out to optimize the ohmic heating parameters for enhancing physico-chemical properties of oil from enzymatic hydrolyzed black cumin seed. The effect of electric field strength (EFS) including 550, 650,750,850 and 950 V/m, the end point temperatures (EPT) 50, 60, 70, 80 and 90 ºC, holding time (HT) 0, 5, 10,15 and 20 min and pH levels 2, 3, 4, 5 and 6 were optimized for the extraction process. The response in terms of oil yield, refractive index, specific gravity, color, free fatty acids, saponification, and peroxide values of the extracted oil was studied. Statistical analysis and optimization of process parameters were performed using the response surface methodology. The results revealed that 56.54–64.18% of oil yield was obtained in enzymatic aqueous extraction and in combination with ohmic heating, was increased from 64.18% to 85.71%. From the numerical optimization it is observed that, EFS of 718.22 (V/m), EPT of 66.08 (°C), HT of 14.07 (min) and pH of 3.7 facilitates the oil yield, specific gravity, color, free fatty acid, saponification, and peroxide values were 79.12%, 0.798, 46.68, 0.672%, 181.42 mg KOH/g and 1.128 meq O2/kg, respectively. It is confirmed that there is not statistically significant (P < 0.05) difference was observed between the predicted and actual values. Thus, it could be concluded that the optimum conditions of ohmic heating parameters could be enhanced by oil yield and maintaining the natural of physico-chemical properties of enzymatically hydrolyzed black cumin seed oil.

Application of autochthonous extremophilic Bacillus xiamenensis in remediation of groundwater- A sorption-based metal cleaning approach

Surface water and groundwater used for drinking and agricultural purposes are contaminated due to anthropogenic and geogenic activities. Escalated metal concentrations, xenobiotic pollutants, competitive ions, and reusability issues are main hindrances towards decontamination of water. Moreover, the expensive purification technology brings obstacles to the underdeveloped community from availing clean water. In this context, the present work offers a sustainable cost-effective approach by providing an effective and sustainable sorption-based purification method by novel polyextremophilic bacteria Bacillus xiamenensis ISIGRM16 isolated from metal-rich industrial waste, red mud. Batch adsorption study revealed that the bacterium can remove Cd2+(>99%), Ni2+(>85%), and Cr6+(>40%) from aqueous solution. The optimum parametric conditions for the removal of Cd2+ and Ni2+ were observed at a temperature of 30 °C and a pH of 6, while for Cr6+ removal, the optimal conditions were a temperature of 45 °C and a pH of 2. The adsorption process of Cd2+ was best explained by Freundlich isotherm (R2 ≥ 0.95), revealing multilayer adsorption. Ni2+ and Cr6+ followed the Langmuir isotherm, indicated adsorption onto the monolayer surface. The interaction mechanism was determined to be following 2nd order kinetics, with both exothermic (Cd2+, Ni2+) and endothermic (Cr6+) characteristics. The maximum adsorption capacities were found to be 31.42, 29.30, and 15.21 mg g−1 for Cd2+, Ni2+, and Cr6+ respectively. In the ternary system, the adsorption capacity followed the order Ni2+ > Cd2+ > Cr6+, as confirmed by both their relative adsorption capacity and from analysis visual MINTEQ. Microscopic and spectroscopic analyses revealed, altered cell morphology, metal deposition on the bacterial cell surface, and the involvement of hydroxyl, carboxyl, and amide groups in the elimination of Cd2+, Ni2+, and Cr6+. Further the sequential adsorption-desorption study confirmed a significantly preserved removal efficacy (p < 0.05), indicating the advantageous use of the bacterium as a biosorbent.

Prediction of nitrous oxide emission of a municipal wastewater treatment plant using LSTM-based deep learning models.

Accurate assessment of greenhouse gas emissions from wastewater treatment plants is crucial for mitigating climate change. N2O is a potent greenhouse gas that is emitted from wastewater treatment plants during the biological denitrification process. In this study, we developed and evaluated deep learning models for predicting N2O emissions from a WWTP in Switzerland. Six key parameters were selected to obtain the optimal LSTM model by adjusting experimental parameter conditions. The optimal parameter condition was achieved with 150 neurons, the tanh activation function, the RMSprop optimization algorithm, a learning rate of 0.001, no dropout regularization, and a batch size of 128. Under the same conditions, we compared the performance of recurrent neural networks (RNNs) and Long Short-Term Memory (LSTM) networks. We found that LSTM models outperformed RNN models in predicting N2O emissions. The optimal LSTM model achieved a 36% improvement in mean absolute error (MAE), a 19% improvement in root mean squared error (RMSE), and a 6.92% improvement in R2 score compared to the RNN model. Additionally, LSTM models demonstrated better resilience to sudden changes in the target sequence, exhibiting a 9.54% higher percentage of explained variance compared to RNNs. These results highlight the potential of LSTM models for accurate and robust prediction of N2O emissions from wastewater treatment plants, contributing to effective greenhouse gas mitigation strategies.

Investigating the influence of induced charge and surface charge heterogeneity on electrokinetic micromixing: A comparative analysis

This paper investigates the performance of a micromixer by considering the combined effects of surface charge heterogeneity and the induced charge electrokinetic (ICEK) phenomenon. With the applied electric field, surface charge heterogeneity generates a recirculation zone within the microchannel, while conductive links induce micro-vortices. The main objective is to explore the influence of various control parameters on the mixing efficiency, including zeta potential, the number and orientation of conductive links, and applied electrical potential. The generated recirculation zone and induced micro vortices introduce chaotic perturbations within the microchannel, improving mixing performance. The results demonstrate that increasing the zeta potential on heterogeneously charged patches enhances the mixing performance, albeit at the expense of a reduced average outlet velocity. Additionally, a higher number of conductive links leads to increased mixing efficiency. The combination of mounting a conductive link inside the channel and applying a heterogeneous zeta potential patch on the wall substantially increased mixing efficiency. The influence of fluid rheology on mixing performance is also investigated, revealing that pseudoplastic fluids exhibit better mixing than dilatant fluids. Finally, the combined effects of all parameters are evaluated using the Taguchi method, resulting in an optimized mixing performance for the proposed micromixer. Micromixing efficiency exceeding 98% is achieved for all types of non-Newtonian fluids under optimal parametric conditions.

Investigating the wear performance of AZ91D magnesium composites with ZnO, MnO, and TiO2 nanoparticles

In recent decades, there has been a notable advancement in the field of bioactive, biodegradable, and biocompatible metallic materials, particularly for applications in general surgery. Among these materials, magnesium alloy-based composites have gained popularity due to their excellent biological properties and adequate strength. However, their resistance to wear is still an area that requires further investigation. Therefore, this study examines the wear properties of stir-ultrasonic-squeeze-casted magnesium (AZ91D) composites, incorporating distinct nanoparticles such as ZnO, MnO, and TiO2. The Evaluation-based Distance from Average Solution (EDAS) approach is used to determine the optimal parameters. Additionally, an Analysis of Variance (ANOVA) is conducted to identify the crucial factors influencing the responses. The effect of process factors on the wear rate and Coefficient of Friction (COF) is then investigated using response surface plots. The confirmation assessments reveal that the optimal parameter conditions for the tribo process comprise a 50.0018 N applied load, a 1.4998 m/s sliding velocity, and the AZ91D + 1% TiO2 (ATO) composite utilization. The ANOVA findings demonstrate that the applied load significantly contributes to 67.3% of the wear performance. Subsequently, after determining the optimal condition, it is observed that the ATO composite, when exposed to temperatures above 150 °C, exhibits an abrupt increase in wear rate and COF due to the degradation of grain strength and the dissolution of the β-phase within the composite.

Expert opinion based optimziation of CNC machining parameters for Al-CNT composites using fuzzy TOPSIS method

Machinability of Al-CNT composites at optimum conditions of machining parameters saves a lot of time, improves quality of machined components at minimum possible cost of machining. In conventional methods, controlled experimentation is performed. In order to obtain best machining parameters, optimization methods are applied but they are inadequate in many situations. Hence, an attempt was made in this work to collect subjective data for response parameters such as, quality, cost, and time, from selected experts in this field for various combinations of input process parameters of CNC milling machine for the case of Al-CNT composites with high-speed steel as tool material. 27 sets of experiments were devised for various combinations of machining parameters systematically by taking cutting speed (in rpm), feed, step over ratio, and depth of cut each at 3 levels. Two experts were invited for collection of data for the response parameters and three experts were involved for giving weightages for the response parameters. Fuzzy trapezoidal membership functions were made use of, for representing fuzzy set and fuzzy Technique and TOPSIS method was applied for finding the best solution. Results revealed that best solution was obtained for a spindle speed of 3000 rpm, feed of 150 mm rev−1, step-over ratio of 0.5, and depth of cut of 0.2 mm.

Investigation of Heat Annealing and Parametric Optimization for Drilling of Monel-400 Alloy

A nickel-based copper alloy known as Monel-400 is extensively applied in many industries including aerospace, marine engineering, and nuclear power generation, owing to its exceptional characteristics such as extreme tensile strength and toughness, excellent corrosion resistance, and the ability to retain shape even at extremely high temperatures. Traditional methods of drilling Monel-400 alloy are difficult due to quick tool wear and poor surface polishing, resulting in expensive machining costs. In this study, a technique called heat annealing was implemented to externally heat-treat the Monel-400 alloy material before the drilling process. Cutting force, surface roughness, and tool wear were used as the responses to investigate the effect of heat annealing and the drilling parameters on the machinability of Monel-400. The results revealed that the cutting force (Fz) and surface roughness (Ra and Rt) could be reduced by 33%, 31%, and 25%, respectively, after annealing at 700 °C compared to the results of the drilled Monel-400 at room temperature. It can be observed that the maximum improvement can reach 42% of Fz, 35% of Ra, and 59% of Rt while annealing Monel-400 at 1000 °C. A significant reduction was observed in the tool wear for machining the annealed material, which minimized the tooling and overall machining cost. Regarding the effects of the drilling process on the considered responses, the results revealed that the spindle speed has a greater effect on the cutting force, whereas the feed rate has the most significant effect on Ra. The significance of the drilling input parameters on the outputs is determined by analysis of the main effect plots and surface plots. Subsequently, the multi-objective genetic algorithm (MOGA) is used to identify the optimal parametric conditions for minimizing the cutting force and surface roughness of the drilled holes. The optimized values achieved via multi-objective optimization are the cutting force, Fz = 388–466 N, and the surface roughness, Ra = 0.17–0.19 μm and Rt = 3–3.5 μm, respectively.

A Systematic Investigation of Lead-Free Electroless Ni-B-W Coating Properties Using Taguchi’s Methodology

Electroless Ni-B (ENB) coatings have industrial importance due to their excellent mechanical properties. The inclusion of W (ENB-W) to the coatings further enhances their mechanical properties and thermal stability. Nevertheless, the ENB or ENB-W coatings are deposited from a heavy metal-stabilized bath, and the very commonly used stabilizer is lead nitrate. The present work is an attempt to obtain an ENB-W coating with enhanced mechanical properties and elimination of the stabilizer from the bath. To achieve this, the coating bath temperature, the heat treatment temperature and the heat treatment duration were varied systematically following a strategy adopted from Taguchi’s experimental design. The mechanical properties targeted include surface microhardness and scratch hardness. Multi-objective optimization was performed using gray relational methodology. The predicted bath temperature was 85 °C, while the predicted heat treatment temperature was 450 °C and there was 3 h of heat treatment time. The optimized lead-free ENB-W coatings had a microhardness of 1096.2 HV100 and scratch hardness of 13.86 GPa. In fact, single-objective optimization for surface microhardness and scratch hardness by Taguchi’s methodology also predicted the same optimal parametric condition for both scratch hardness and surface microhardness. This was comparable to that of a lead-stabilized ENB-W coating and higher than the as-plated stabilizer free ENB-W coatings. The coating failure of the optimized ENB-W alloy was tested using a progressive scratch test, which showed that there was no chevron or transverse cracks within the load range considered. Analysis of corrosion resistance revealed that the corrosion potential of the optimized coatings was −407 mV, and this was comparable to that of a lead-based ENB-W coating.

Dry machining of alloy steels – A review

Dry machining has been used as an alternative method in place of the conventional machining process as the usage of cutting fluid has many side effects and adds more cost to the manufacturing process. Handling and recycling of chips is the main feature of the dry machining process. The heat generated and the tool life are the major concerns in dry machining. There is an alternative method called the minimum quantity lubrication technique where the cutting fluid is sprayed in the form of a mist. Alloy steels are extensively used for the manufacturing of various components in automobile, aircraft, military, and medical industries. It’s crucial to study the dry machining of alloy steels to achieve high-quality finished products at economical costs. In turning operation cutting speed, feed rate, depth of cut and cutting environment are the controllable machining parameters which affect the outputs like surface roughness, tool wear, tool life, MRR, power consumption, etc. In practice when machining is done there are some desired characteristics for the output parameters, that can’t be achieved with some random input parameters combination, the combination of input parameters where desired characteristic of output parameters is achieved is called optimal parameter condition. Optimal conditions for the machining process can be found using the Taguchi technique based on means method or S/N ratio method and ANOVA is used to find the significance of input dimension on outputs. This optimal condition can be found for each individual output parameter or else for all output parameters at once which is called multi-objective optimization. Machine learning model can be developed using experimental data for prediction. The model will be trained based on the training data that has been provided to it. Machine learning models can avoid the waste of time of manual experimentation and directly predict the values.

Optimization of Reducing Sugar Production from Sida cordifolia Biomass Using Response Surface Methodology

This study is aimed at evaluating the potential of Sida cordifolia, for the production of reducing sugars via acid hydrolysis. Effect of temperature (60oC-100oC), acid concentration (1%-6%) and time(30min-60min) was investigated using response surface methodology (RSM) experimental design. Reducing sugars yield from acid hydrolysis was optimized using RSM. The interaction of (acid concentration)2 and (temperature)2 were found to be the most significant quadratic terms affecting reducing sugars yield. The optimum parameter conditions were found to be temperature (80oC), reaction time (60 min) and acid concentration (3.50%) with a reducing sugar yield of 4.931%. The findings suggest that the biomass can be harnessed as a potential feedstock for the production of bioethanol and other bio-based chemicals.