Response Surface Methodology Experimental Design Research Articles

An alternative peptone preparation using Hermetia illucens (Black soldier fly) hydrolysis: process optimization and performance evaluation.

Hermetia illucens (HI), commonly known as the black soldier fly, has been recognized for its prowess in resource utilization and environmental protection because of its ability to transform organic waste into animal feed for livestock, poultry, and aquaculture. However, the potential of the black soldier fly's high protein content for more than cheap feedstock is still largely unexplored. This study innovatively explores the potential of H. illucens larvae (HIL) protein as a peptone substitute for microbial culture media. Four commercial proteases (alkaline protease, trypsin, trypsase, and papain) were explored to hydrolyze the defatted HIL, and the experimental conditions were optimized via response surface methodology experimental design. The hydrolysate of the defatted HIL was subsequently vacuum freeze-dried and deployed as a growth medium for three bacterial strains (Staphylococcus aureus, Bacillus subtilis, and Escherichia coli) to determine the growth kinetics between the HIL peptone and commercial peptone. The optimal conditions were 1.70% w/w complex enzyme (alkaline protease: trypsin at 1:1 ratio) at pH 7.0 and 54 °C for a duration of 4 h. Under these conditions, the hydrolysis of defatted HIL yielded 19.25% ±0.49%. A growth kinetic analysis showed no significant difference in growth parameters (μmax, Xmax, and λ) between the HIL peptone and commercial peptone, demonstrating that the HIL hydrolysate could serve as an effective, low-cost alternative to commercial peptone. This study introduces an innovative approach to HIL protein resource utilization, broadening its application beyond its current use in animal feed.

Investigation on carbon fiber-reinforced polymer combined with graphene nanoparticles subjected to drilling operation using response surface methodology and non-dominated sorting genetic algorithm-II

In this article, drilling of carbon fiber-reinforced plastics combined with graphene nanoparticles is investigated. These nanocomposites have the potential to be used widely in different industrial applications such as electrical, biomedical and aerospace engineering due to their superior mechanical and thermal specifications. Nonetheless, to be assembled on different sets, drilling nanocomposites is required especially for rivets and joints. In drilling carbon fiber-reinforced polymers (CFRPs), delamination is one of the main challenges that should be minimized in order to enhance the produced hole quality. Besides, machining force is a chief factor to control the drilling-induced damages, especially delamination. This article evaluates the effects of machining parameters on machining force and delamination using response surface methodology experimental design and non-dominated sorting genetic algorithm-II (NSGA-II) multiobjective optimization methodology. Examining delamination is conducted in two parts including peel-up and push-down delamination which are the principal drawbacks in drilling of fiber-reinforced composites. Analysis of variance is also carried out in order to examine the effects of the machining parameters. In addition, predictive quadratic correlations are established by regression analysis. Eventually, multiobjective optimization was implemented by NSGA-II and the optimal values were obtained from pareto-optimal solution set aimed at enhancing the drilling process.

Application of Response Surface Methodology Experimental Design to Optimize Tribological Lubrication Characteristics

Total Knee Replacement (TKR) has become a standard operation for patients with joint disorders. Despite the fact that the number of procedures is increasing all the time, the short service life of implants remains a persistent concern for researchers. Understanding lubrication may aid in explaining tribological processes that lead to replacements that last well into the third decade of service. Likewise, wear and friction in total knee replacement (TKR) components are among the most common causes of implant failure. As a result, this study will evaluate the feasibility of using the polymer Polylactic Acid (PLA) for cartilage replacement in Total Knee Replacement (TKR) using plant-based oils as lubricants. Furthermore, the modifier will be added to plant-based oils as an additive to make them analogous to human bodily fluids. The present paper is applying the Box-Behnken design to optimize the performance and mechanical responses of bio-lubricants toward Polylactic Acid (PLA) as a tibial insert for cartilage replacement in Total Knee Replacement (TKR). The main objective of this paper is to develop an optimized method for the selection of plant-based oil parameters using Response Surface Methodology (RSM). A three-level three-factor Box-Behnken design (BBD) was used to investigate the interactions between the essential factors comprising load (45 kg to 90 kg), speed (60 rpm, 90 rpm and 360 rpm), and concentration (0ml, 5ml and 10ml) of bio-lubricants to accomplish the indicated prospect of using polymer for cartilage replacement. Canola oil, castor oil, and sunflower seed oil are considered vegetable oils, whereas Hyaluronic Acid (HA) is the friction modifier. The parameters are used to create a Box-Behnken design for predicting lubricant anti-wear qualities stated in terms of coefficient of friction, wear rate and frictional force as determined by the pin-on-disk experimental procedure. As a result, the optimization using RSM successfully interpreted the experimental data, according to the analysis of variance, with coefficients of determination of R2 = 0.91 and adjusted R2 = 0.77. The Coefficient of Friction (CoF) and wear rate were investigated following tribological testing. Castor oil had a lower coefficient of friction than canola and sunflower seed oil, according to the findings. In terms of friction reduction, castor oil surpasses canola and sunflower seed oil.

Elaeis guineensis leaves for potential renewable sub‐bituminous coal: Optimization of biochar yield by response surface methodology and product characterization

AbstractPyrolysis of oil palm biomass residue can convert the rich organic matter in biomass into sustainable green energy, thereby addressing the challenge of surplus oil palm biomass residue generated during cultivation. Nonetheless, the pyrolysis of oil palm leaves (OPLs) has received limited attention. In this study, design of experiment‐response surface methodology (DoE‐RSM) was employed to identify the optimal combination of reaction temperature, residence duration, and nitrogen (N₂) flow rate for maximum biochar yield. The elemental analysis, high heating value (HHV), functional group, morphology, pore structure, and thermal behavior were assessed. By varying the operational parameters using response surface methodology, the biochar yield increased by 32.6–85.3%. The DoE‐RSM predicted a theoretical yield of 52.1% at 344 °C, 146 min, and 3.2 scfh N₂ flow rate. The experiment confirmed a comparable yield of 53.7% at the stated parameters. The HHV of 24.14 MJ kg−1 was recorded under optimal conditions, and was comparable to sub‐bituminous and bituminous coal. Fourier transform infrared analysis validated the OPL biochar by weakening O‐H, C=O, C‐OH, and C‐H peaks. Scanning electron microscopy images revealed enlarged pores and altered morphology in the OPL biochar. X‐ray diffraction showed lower crystallinity of the OPL biochar than the feedstock. Raman spectroscopy showed higher ID/IG, indicating a more disordered carbon structure in the OPL biochar. Thermogravimetric analysis confirmed higher temperature for main devolatilization of OPL biochar, and the differential thermogravimetric analysis curve pattern resembled that of Mukah Balingan coal. The findings are helpful for an initiative to convert a large amount of leftover OPLs produced during cultivation and to turn them into high value‐added material for a sustainable contribution to a circular carbon economy.

Probiotic Encapsulation: Bead Design Improves Bacterial Performance during In Vitro Digestion.

The stability and release properties of all bioactive capsules are strongly related to the composition of the wall material. This study aimed to evaluate the effect of the wall materials during the encapsulation process by ionotropic gelation on the viability of Lactobacillus fermentum K73, a lactic acid bacterium that has hypocholesterolemia probiotic potential. A response surface methodology experimental design was performed to improve bacterial survival during the synthesis process and under simulated gastrointestinal conditions by tuning the wall material composition (gelatin 25% w/v, sweet whey 8% v/v, and sodium alginate 1.5% w/v). An optimal mixture formulation determined that the optimal mixture must contain a volume ratio of 0.39/0.61 v/v sweet whey and sodium alginate, respectively, without gelatin, with a final bacterial concentration of 9.20 log10 CFU/mL. The mean particle diameter was 1.6 ± 0.2 mm, and the experimental encapsulation yield was 95 ± 3%. The INFOGEST model was used to evaluate the survival of probiotic beads in gastrointestinal tract conditions. Upon exposure to in the vitro conditions of oral, gastric, and intestinal phases, the encapsulated cells of L. fermentum decreased only by 0.32, 0.48, and 1.53 log10 CFU/mL, respectively, by employing the optimized formulation, thereby improving the survival of probiotic bacteria during both the encapsulation process and under gastrointestinal conditions compared to free cells. Beads were characterized using SEM and ATR-FTIR techniques.

Optimization of voltammetric parameters for sensitive and simultaneous determination of ferulic acid and vanillin using a glassy carbon electrode based on 2-aminonicotinic acid in the presence of surfactant media

The electrochemical sensor for simultaneous determination of ferulic acid (FA) and vanillin (VA) was prepared by electrochemical deposition of 2-aminonicotinic acid (2-ANA) on the glassy carbon (GC) electrode. The voltammetric determination of FA and VA was performed in the BR buffer solution in the presence of sodium dodecyl sulfate as a surfactant with SWV. The parameters of the SWV technique were optimized by response surface methodology experimental design. Under optimized conditions, the 2-ANA/GC modified electrode presented a linear working range of 2.8 × 10−8 M to 7.50 × 10−6 M and 7.50 × 10−6 M to 2.45 × 10−5 M for FA, 3.06 × 10−8 M to 1.27 × 10−5M for VA. The detection limit (LOD) values for FA and VA were 6.87 nM and 9.23 nM, respectively. Using the 2-ANA/GC sensor, concentrations of FA and VA in instant coffee and milk samples were determined with %recovery values between 103.40 and 97.07 and %RSD values between 0.76 and 4.40.

Catalytic steam gasification of soy hull pellets in a fluidized bed gasifier

The catalytic effects of inherent alkali-based metal catalysts present in biomass residues on biomass pellets were explored in this work. Gasification experiments were carried out in a pilot scale fluidized bed gasifier in the presence of alkali metal catalysts. By using a response surface methodology experimental design technique, soy hull biomass pellets were subjected to steam gasification within a temperature range of 750–950 °C. Additionally, the effects of steam-to-biomass (S/B) ratio and the catalyst loading on the gas and tar yields, and gaseous compositions were investigated. It was found that lower temperature resulted in the formation of more tar residue since the temperature was insufficient to crack the tar formed. Lower S/B ratio led to increased tar yield. Addition of catalyst significantly reduced the tar residue produced during the gasification experiments. An increase in the catalyst loading led to a steady decrease in the tar yield with up to 52% reduction at 950 °C. Further increasing catalyst loading beyond 5% had no significant effect on tar reduction. Gas yield increased slightly with catalytic gasification of the biomass pellets compared to the non-catalyzed reactions earlier studied. The reaction mechanism of the catalyzed reactions and effect on tar decomposition were discussed. Catalytic effects on tar composition were also investigated. The results from these experiments provide further insight into considering co-pelletization of catalysts during production of pellets for better gasification performance in terms of increased yields of the major gaseous components.

Optimization of uranium alkaline leaching from the solid waste sample containing high fluoride and nitrate by response surface methodology experimental design

به منظور فروشویی قلیایی اورانیم از پسماند جامد، از محلول حاوی کربنات استفاده می‌­شود. زمان، دما و سرعت هم­‌زدن (پارامترهای مستقل) و غلظت کل کربنات، نسبت کربنات به بی­کربنات و نسبت حجم شوینده مایع به وزن پسماند جامد (L/S) (پارامترهای وابسته) از جمله پارامترهای مؤثر در فرایند فروشویی هستند. بهینه‌­سازی پارامترهای مستقل به شیوه یک متغیر در زمان (OVAT) انجام گرفت و پارامترهای وابسته نیز با کمک نرم‌­افزار MINITAB و با استفاده از روش طراحی آزمایش مختلط مرکزی در وجه (FCCD) به صورت هم­‌زمان بررسی شدند. پودر پسماند جامد توسط EDAX، SEM و XRD آنالیز گردید و آنالیز عنصری نمونه­‌ها نیز پس از انحلال کامل توسط ICP-OES صورت پذیرفت. مدت زمان 5/0 ساعت، سرعت چرخش هم‌زن 150 دور بر دقیقه، دمای اتاق، غلظت‌­های 09/0، 01/0 و 1/0 مولار (به ترتیب) برای کربنات و بی­کربنات سدیم و کل کربنات، همراه با نسبت‌­های 9/1 و 20 (به ترتیب) برای نسبت کربنات سدیم به بی‌کربنات سدیم و L/S شرایط بهینه بودند. تکرارپذیری فروشویی پسماند جامد با انجام 4 آزمایش بررسی و مقادیر 2±2/94 و 6/1±15/4 به ترتیب برای متوسط درصد لیچ و جامد باقی‌مانده به­‌دست آمدند. متوسط عیار اورانیم نیز 02/0±09/2 بود.

Response Surface Optimization of Culture Conditions of Microcystis sp. to Enhance its Biomass Production and Explore its Potential as Antimicrobials

The menace of drug-resistant bacteria is an issue of global concern. The growth mechanism of the algae Microcystis sp. encompasses the capacity to upset bacterial pathogens, and this approach is explored in the study. Microcystis sp. biomass harnessing was optimized via DoE-RSM (Design of Experiment-Response Surface Methodology), and further, the in vitro antimicrobial abilities to counter the drug-tolerant microbes were considered. This investigation aimed to increase the biomass output via optimization of essential components of the media parameter like NaNO3, K2HPO4, and MgSO4 as the variables. A maximal biomass yield of 262 mg.L-1 was accomplished within the optimized conditions and the Microcystis sp. displayed notable antimicrobial action against Staphylococcus aureus and Pseudomonas aeruginosa. Hence the Microcystis sp. could be an ideal biocontrol agent to mitigate the drug-tolerant microbes. A partial sequencing was performed, and gene sequences were subject to BLAST at NCBI, and the microbial isolate was identified as Microcystis aeruginosa, and the accession number was also procured for this sequence submission as MT792731.1.

Optimization of square wave voltammetry parameters by response surface methodology for the determination of Sunset yellow using an electrochemical sensor based on Purpald®

A modified electrode (Purpald®/GC) was prepared by electrochemical deposition of 4-Amino-5-hydrazino-1,2,4-triazole-3-thiol (Purpald®) on the glassy carbon electrode surface to determine sunset yellow (SY). The sensor was characterized by Fourier transform infrared spectroscopy, scanning electron microscope with energy dispersive X-ray spectrometer attached, and electrochemical techniques. Optimum experimental conditions were determined for the determination of SY. To obtain better analytical performance on the Purpald®/GC sensor, the response surface methodology experimental design was used. The square wave voltammetry technique’s parameters were optimized to obtain the highest anodic peak current of SY. The working range was obtained as three linear concentration ranges were 4.97 nM-1.18 µM, 1.18 µM-15.16 µM, and 15.16 µM-0.153 mM. The LOD value was found as 1.15 nM with the optimum parameters combination. Using the proposed sensor, SY concentration was determined with satisfactory results in instant powder drink and orange-flavored carbonated drink samples.

Analysis of Multiclass Pesticide Residues in Tobacco by Gas Chromatography Quadrupole Time-of-Flight Mass Spectrometry Combined with Mini Solid-Phase Extraction

A screening method using gas chromatography quadrupole time-of-flight mass spectrometry (GC-QTOF/MS) combined with mini solid-phase extraction (mini-SPE) was established for the quantification and validation of multiclass pesticide residues in tobacco. The method was quicker and easier, with sample purity higher than that obtained by traditional SPE and dispersed-SPE. Box-Behnken design, an experimental design for response-surface methodology, was used to optimize the variables affecting the target pesticide recovery. Under the optimized conditions, 92% of the pesticides showed satisfactory recoveries of 70%–120% with precision <20% at spiking levels of 50, 250, and 500 ng/g. The limits of detection and quantification for all the analyses were 0.05–29.9 ng/g and 0.20–98.8 ng/g, respectively. In addition, a screening method based on the retention time and a homebuilt high-resolution mass spectrometry database were established. Under the proposed screening parameters and at spiking levels of 50, 100, and 500 ng/g, 76.6%, 94.7%, and 99.0% multiclass pesticide residues were detected, respectively, using the workflow software. The validated method was successfully applied to the analysis of real tobacco samples. Thus, the combination of mini-SPE and GC-QTOF/MS serves as a suitable method for the quantitative analysis and rapid screening of multiclass pesticide residues in tobacco.

Production of nesquehonite, a magnesia precursor, by carbonation of synthetic mine waste water

Nesquehonite (MgCO3.3H2O) is the preferred precursor to the high value product magnesia (MgO). Magnesia is used extensively in the mining industry for the hydrometallurgical recovery of metals and is usually obtained from processing naturally occurring minerals, brines or sea water. The mining industry produces large volumes of mine-impacted water in the form of brines and other wastes that could be used as a low-cost resource for producing the magnesia precursor. This work aimed to optimise the first phase of a potentially low-cost MgO production process, by carbonation of a synthetic solution simulating a Mg-rich liquid mine-waste. A three-factor, two-response, Box-Behnken response surface methodology experimental design (RSM) was used to determine the optima for the process on a synthetic sample. The optimal factor settings were identified and the tests established that the target product, nesquehonite, was preferentially formed in the majority of the experiments.

Flow pattern analysis and multi-objective optimization of helically corrugated tubes used in the intermediate heat exchanger for nuclear hydrogen production

Using the heat of the very-high-temperature gas-cooled reactor (VHTR) for large-scale and carbon-free hydrogen production provide an excellent option for a new sustainable energy economy. The intermediate heat exchanger (IHX) is a crucial component to realize this new hydrogen production mode. To supply sufficient heat for hydrogen production, the heat transfer of IHX needs to be enhanced. In this study, helically corrugated tubes (HCTs) were used to enhance the heat transfer of IHX. The flow pattern of HCTs was analyzed and a multi-objective optimization was then performed. First, the numerical experiment design with two objectives and three factors was conducted by Box-Behnken design in the response surface methodology (RSM). Second, the significant regression models for Nusselt number, friction factor, and performance evaluation criteria were obtained by the analysis of variance. Combining the analysis of turbulence kinetic energy and flow dead zone, a more comprehensive mechanism for the effect of corrugation parameters on flow and heat transfer was proposed. Finally, the fast-elitist non-dominated sorting genetic algorithm (NSGA Ⅱ) was adopted to conduct the multi-objective optimization of HCTs. The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted for multi-objective decision-making. The CFD validation and comparison with RSM experimental design confirmed that the obtained Pareto optimal set and Pareto front can provide a comprehensive and effective design strategy for the IHX used for nuclear hydrogen production.

Optimization of Mechanical Oil Expression from Sandbox (Hura crepitans Linn.) Seeds

Optimization of process variables has become very vital in oil extraction processes to obtain maximum oil yield from oilseeds and nuts. This work focussed on the optimization of process oil extraction process from sandbox seed by mechanical expression. Effects of moisture content, roasting temperature, roasting time, expression pressure and expression time on oil yield from sandbox seed was studied using a 5×5 Central Composite Rotatable Design of Response Surface Methodology experimental design. Results obtained were subjected to Analysis of Variance (ANOVA) and SPSS statistical tool at (p = 0.05). Optimum conditions predicted were validated by experiments. All the processing factors were significant at (p = 0.05) for the sandbox oil yield except roasting temperature. The experimental results and predicted values showed low deviation (0.01-0.62). Oil yields obtained from the sandbox seed at varying process conditions varied from 16.38-38.68%. The maximum oil yield of 38.68% was obtained when the sandbox seed was subjected to process conditions of 6% moisture content, 85°C roasting temperature, 15 min roasting time, expression pressure of 20 MPa and 8 min pressing time. Mathematical equations to predict sandbox seed oil yield at varying process conditions were developed with an R2 (0.8908). The optimum extractable oil yield of 38.95% was predicted for sandbox seed at processing conditions of 7.03% moisture content, 97.72°C roasting temperature, 11.32 min roasting time, 15.11 MPa expression pressure and 8.57 min expression time. The study results provide data for designs of process and equipment for oil extraction from sandbox and other oilseeds.

Evaluation and Optimization of Bioethanol Production from Pomegranate Peel by Zymomonas mobilis

Introduction: The large amount of production and use of pomegranate in Iran has made the waste of this important product a suitable source for the production of bioethanol. This research examined the ability of Zymomonas mobilis for producing bioethanol from Pomegranate peel.Materials and Methods: The hydrothermal treatment method and enzymatic hydrolysis were used to release the fermentable sugars from PP particles. Cellulase loading of 30 U/g solid was used for enzymatic hydrolysis. Zymomonas mobilis PTCC 1718 was used as the ethanol-producing strain. The Response Surface Methodology experimental design was performed to optimize the fermentation process conditions for maximum ethanol production and minimum fermentation time.Results: The amount of sugar released after hydrolysis was about 18.37% of the fresh PP weight. The amount of meat peptone and yeast extract (as nitrogen sources added to the medium), bacterial dry weight (as inoculum) and fermentation time were considered as the effective factors in the RSM experimental design. The maximum amount of 0.218 g ethanol was produced at 0.37 g meat peptone, 0.28 g yeast extract, 0.021 g bacterial dry weight and 30 h fermentation time (in 50 ml of culture medium). The maximum ethanol production yield of 45.5% (which is 89.2% of the theoretical yield) was achieved in this process.Conclusions: Z. mobilis has good ability for producing bioethanol from PP. However, more research should be conducted in order to industrialize the process.

Prediction of cutting force based on machining parameters on AL7075‐T6 aluminum alloy by response surface methodology in end milling

AbstractCutting forces modeling is the basic to understand the cutting process, which should be kept in minimum to reduce tool deflection, vibration, tool wear and optimize the process parameters in order to obtain a high quality product within minimum machining time. In this paper a statistical model has been developed to predict cutting force in terms of geometrical parameters such as rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Response surface methodology experimental design was employed for conducting experiments. The work piece material is Aluminum (Al 7075‐T6) and the tool used is high speed steel end mill cutter with different tool geometry. The cutting forces are measured using three axis milling tool dynamometer. The second order mathematical model in terms of machining parameters is developed for predicting cutting forces. The adequacy of the model is checked by employing ANOVA. The direct effect of the process parameter with cutting forces are analyzed, which helps to select process parameter in order to keep cutting forces minimum, which ensures the stability of end milling process. The study observed that feed rate has the highest statistical and physical influence on cutting force.

Optimization and wear characteristics of TiAlN coated carbide when machining hardened high thermal conductivity (HTCS-150) die steel.

High Thermal Conductivity Steel-150 (HTC-150) is a specific steel designed for use in the hot stamping process as a stamping die. HTCS-150 die steel was difficult to machine due to its high strength, hardened state, and high thermal conductivity characteristics, which necessitated parameter control for a fine surface finish and maximum tool life. The characteristics of tool wear when machining HTCS-150 hardened steel (52 HRC) with a ball nose end mill TiAlN coated carbide insert is presented in this study. Cutting speed, feed rate, and axial depth of cut have all been varied in machining trials. Response surface methodology experimental design was used to create a parametric optimisation model. The results indicate that the model develops an accurate prediction, with comparisons between measured and expected results suggesting that the model operates within the 90% prediction interval with an error of less than 10%. The lowest tool wear was achieved at 130 m min−1 cutting speed, 0.4 mm/tooth feed rate, and 0.1 mm axial depth of cut, according to the optimisation results. The most influenced cutting parameters were found to be feed rate and depth of cut, followed by cutting speed. The wear surface texture analysis revealed coating delamination, adhesion, built-up edge formation, and tool edge chipping. The findings of this experimental study can be used to machine the HTCS-150 for the longest possible tool life while maintaining a fine surface finish.

Comparison and optimization of conventional and ultrasound-assisted solvent extraction for synthetization of lemongrass (Cymbopogon)-infused cooking oil.

The lemongrass plant, which is widely cultivated in Asia, Australia, and Africa, has been reported to have many significant health benefits such as antimicrobial, insecticide, anticancer, fight fever, and disinfection. Therefore, it is an added benefit to have lemongrass compounds in cooking oil. This study was aimed to compare the conventional (CSE), and ultrasound‐assisted solvent extraction (UASE) for citral compounds from lemongrass (Cymbopogon) leaves and to optimize the best extraction method using the response surface methodology (RSM) and ANOVA. RSM design of experiments using three types of cooking oils; palm oil, sunflower oil, and corn oil. The effect of three independent variables, which are temperature (48.2–81.8°C), extraction time (4.8–55.2 min), and solvent to leaves ratio (5.3–18.7), was investigated. The characterization of lemongrass‐infused cooking oil was evaluated by Fourier transform infrared spectroscopy (FT‐IR), Gas Chromatography‐Mass Spectrometry (GC‐MS) and Scanning Electron Microscopy (SEM) analysis for confirmation of the citral compound extraction. This extraction process is optimized using Response Surface Methodology (RSM) for producing the lemongrass‐infused cooking oil. After optimization, the UASE process gives 1.009 × 106 maximum citral area for palm oil and 1.767 × 106 maximum citral area for sunflower oil. CSE process only can give 2.025 × 105 and 2.179 × 105 citral area in the GC‐MS spectrum for palm oil and sunflower oil respectively. For both the UASE and the CSE, the optimum operating conditions are 81.8°C of extraction temperature and 55.2 min of extraction time except for lemongrass‐infused palm oil in the CSE process with 45 min extraction time. The optimum solvent to leaves ratio varies from 5.3:1 to 12.9:1. This study found that corn oil cannot be used as a solvent to extract lemongrass‐infused cooking oil due to the insignificant changes and no citral peak. The lemongrass (Cymbopogon)‐infused palm oil and sunflower oil extracted using the UASE have a higher maximum citral area than the CSE process.

Analysis of the failure modes and design improvement of an eccentrically loaded connecting rod for a double front axle steering linkage prototype

Failure analysis and optimal redesign study of the connecting rod prototype to be used in the multi-axle steering linkage of an 8x8 Aircraft Rescue and Fire Fighting (ARFF) vehicle is reported. At the prototyping stage, the field tests showed that the connecting rod experiences a plastic deformation during a zero-speed steering manoeuvre. In order to predict the possible causes of the failure, Finite Element (FE) analyses were applied to the complete steering linkage which contains the failed rod design. Primary FE analyses showed that there are critical stress concentration regions on the rod. It was also seen that the maximum stress values at these regions are influenced by the tyre steering angle and the slope of the road surface. Subsequently, critical structural parameters having an influence on the mechanical behaviour of the part were chosen, and a parametric base model was built. Then, using DOE-RSM (Design of Experiments – Response Surface Methodology) based optimisation study, optimal values were selected within the applicable variation range. Nonetheless, by considering the form of the structure together with the loading type, it was decided that the elastic stability should also be taken into account. Although a sufficient improvement was obtained against the overload failure, the elastic stability limit remained exceeded according to the American Institute of Steel Structures (AISC) criteria. Thus, the eccentricity of the connecting rod was also decreased by employing a particular kinematic arrangement in order not to disturb the Ackermann’s rule-based synchronisation ratio of the linkage. Compared to the failed design, it was seen that von-Mises stress can be reduced by up to 66%. The results of this study showed that, factors such as wheel steering angle and road inclination-related axle load variation greatly influence the design load of the steering linkage. Field tests also indicated that, suggested design improvements such as increase in thickness and eccentricity reduction meet the strength requirements of the system.

Multi response optimization for micro-EDM machining of AISI D2 die steel using RSM and neural network

Abstract Micro parts play an important role in the growing micro- industry such as in electronics field and MEMS applications. In precision industry, micro-hole machining is very much required, such as fuel injection nozzles. Micro Electrical Discharge Machining (Micro-EDM) is defined as an un-conventional manufacturing process for the materials having electrical conductivity. It is widely used in die and tool making. In this paper, the effect of various machining parameters used like pulse on time, pulse off time, peak current, spark gap voltage, pulse peak voltage and current output on machining hardened AISI D2 die steel using copper electrodes of 600 µm diameter have been analysed. Metal Removal Rate (MRR) and Tool Wear Rate (TWR) are the responses to be measured. The experiments are conducted by Central Composite Design (CCD) of Response Surface Methodology (RSM) and using three level RSM Design of Experiment (DOE) approach. Models for the output responses have been developed. Desirability function approach is used for optimization of multi response by fitting regression model using the experimental values, after that the parameters of optimal machining are verified experimentally. The optimum predicted response values of MRR, and TWR are 1663.4564 µg/min and 166.7949 µg/min respectively and it is found that experimental values are close to optimized responses.