Influence Of Process Variables Research Articles

Testing the disintegration and texture-related palatability predictions for orodispersible tablets using an instrumental tool coupled with multivariate analysis: Focus on process variables and analysis settings

Orodispersible tablets (ODTs) represent a growing category of dosage forms intended to increase the treatment acceptability for special groups of patients. ODTs are designed to rapidly disintegrate in the oral cavity and to be administered without water. In addition, ODTs are easy to manufacture using standard excipients and pharmaceutical equipment.This study adds to previously published research that developed an instrumental tool to predict oral disintegration and texture-related palatability of ODTs with different formulations. The current study aimed to challenge the predictive capacity of the models under variable process conditions. The studied process parameters with potential impact on the pharmaceutical properties, texture profiles, and palatability were the compression pressure, punch shape and diameter. Subsequently, for all the placebo and drug-loaded ODTs, the in vivo disintegration time and texture-related palatability were determined with healthy volunteers.Previously developed regression models were applied to predict the formulation's disintegration time and texture-related palatability characteristics of ODTs obtained under different experimental conditions. The influence of process variables on the predictive performance of the models was estimated by calculating the residuals as the difference between the predicted and observed values for the investigated response. Increasing the speed of the analyser`s probe from 0.01 mm/s to 0.02 mm/s led to an improved differentiation of the texture profiles. The in vivo disintegration time and texture-related palatability scores were only influenced by the mechanical resistance and the tablet shape. Lower score was observed for the larger diameter tablets (10 mm). Overall, the prediction of the disintegration time at 0.02 mm/s was more accurate, except for stronger tablets. The best prediction of texture-related palatability was achieved for the 10 mm tablets, tested at 0.01 mm/s speed.The same model achieved good predictions of the oral disintegration time for all API-loaded formulations, which confirmed the ability of the texture analysis to capture process-related variability. Drug loading decreased the predictive capacity of the texture-related palatability because of the taste effect.

Optimizing the SPIF parameters for enhancing microhardness and surface quality in Inconel 625 superalloy components

Inconel 625, a high-strength superalloy with excellent corrosion resistance, discovers wide applications in critical sectors such as aerospace, nuclear, marine, and petrochemical. Single-Point Incremental Forming (SPIF) has appeared as an adequate fabricating process for shaping superalloy components. This work used a systematic approach, implementing Response Surface Methodology (RSM) to explore the influence of SPIF process variables, including tool nose diameter, step size, tool spindle speed, and wall angle, on microhardness (MH) and surface roughness (SR). The experimental results have been analyzed to determine the influencing process variables and their optimal settings, which simultaneously enhance MH and reduce SR of Inconel 625 superalloy truncated cones using analysis of variance and the desirability function analysis approach. The most significant parameters that influence MH and SR were TND and SS, respectively. The development of quadratic models for MH and SR has been completed successfully. The maximum MH of 486.8 HV and minimum SR of 0.432 µm have been obtained at the optimal parametric setting of TND = 15 mm, SS = 0.4 mm, TSS = 900 rpm, and WA = 57.5° with the desirability values for MH, SR and combined are 0.832, 0.933, 0.881 respectively. The F-value of the MH model = 109.18 and SR Model = 78.24 implies that both models are significant and both models have excellent prediction strength. The percentage error between predicted and actual values of MH and SR in confirmation run results is less than 5 %.

Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making techniques and regression analysis

Wire electrical discharge machining (WEDM) is one of the most important non-traditional machining methods that is widely used in various industries. The present research work is concerned with the influences of process variables on quality of machined specimen obtained from WEDM process. The process parameters to manufacture mold structure included wire feed speed, wire tension and generator power, and in the current research, the effects of these variables on the aim factors, namely dimensional accuracy, hardness and roughness of product surface have been investigated, simultaneously. In order to obtain the optimal experiment, the multi-objective optimization with discrete solution area has been employed. Method based on the removal effects of criteria (MEREC) and weighted aggregates sum product assessment (WASPAS) techniques have been used with the aim of weighting the objective functions and discovering the best practical experiment. In the following, the regression analysis has been employed to study the effects of variables on response factors. A good correlation between the results gained from two analysis methods was observed. Based on MEREC-WASPAS hybrid technique, the weights of roughness, hardness and dimensional accuracy of machined part were calculated to about 89%, 9% and 2%, respectively. In the selected optimal experiment, the amount of wire feed speed, wire tension and generator power variables were considered to, in turn, 2 cm/s, 2.5 kg, and 10%.

Experimental investigation during nano powder added µ-ED milling on nickel-titanium shape memory alloy

Nickel-titanium (NiTi) shape memory alloy (SMA) is one of the smart materials which has a vast application in the aerospace and biomedical industry due to its shape memory effect (SME), strong corrosion and wear resistance. Thus, the present study investigates the influence of process variables like gap voltage (V), powder concentration (PC) and pulse on time (ton) towards the material removal rate (MRR), surface roughness (SR) and micro-hardness (MH) amid graphene nano powder added micro-electrical discharge milling (µ-ED milling) of NiTi SMA. ANOVA analysis has been carried out to determine the % distribution of individual machining parameters towards all responses. The addition of graphene nano particles to the dielectric oil considerably enhanced the MRR, MH, and decreased the SR of the milled micro-channel. Taguchi’s grey relational analysis (GRA) and grey-desirability approach have been applied for multi-response optimisation to find the maximum MRR, MH, and minimum SR. It is discovered that the grey-desirability method improves all the responses. The Field emission scanning electron microscopy (FESEM) micro-graphs confirm defect-free mirror-like surface finish at the optimal grey-desirability setting. The X-ray diffraction (XRD) analysis discovered the formation of oxides and hardened phases in the machined surface. The application of graphene enhanced the recast layer thickness and reduced the indentation depth at subsurface region. The nano indentation test validates the rise in nano hardness and elastic modulus at the grey desirability optimal setting compared to the initial machining condition.

Parametric Optimization of Selective Laser Melted 13Ni400 Maraging Steel by Taguchi Method

Parametric Optimization of Selective Laser Melted 13Ni400 Maraging Steel by Taguchi Method

Exploring the Effects of Process Parameters during W/O/W Emulsion Preparation and Supercritical Fluid Extraction on the Protein Encapsulation and Release Properties of PLGA Microspheres.

In this study, protein-loaded poly(lactic-co-glycolic acid) (PLGA) microspheres were prepared via supercritical fluid extraction of emulsion (SFEE) technology. To understand the correlation between process parameters and the main quality characteristics of PLGA microspheres, a comprehensive prior study on the influence of process variables on encapsulation efficiency (EE), initial drug burst release (IBR), morphology, surface property, and particle size distribution (PSD) was conducted within a wide process condition range of each unit process step, from the double-emulsion preparation step to the extraction step. Bovine serum albumin (BSA), a high-molecular weight-protein that is difficult to control the IBR and EE of PLGA microspheres with, was used as a model material. As double-emulsion manufacturing process parameters, the primary (W/O) and secondary emulsion (W/O/W) homogenization speed and secondary emulsification time were evaluated. In addition, the effect of the SFEE process parameters, including the pressure (70-160 bar), temperature (35-65 °C), stirring rate (50-1000 rpm), and flow rate of supercritical carbon dioxide, SC-CO2 (1-40 mL/min), on PLGA microsphere quality properties were also evaluated. An increase in the homogenization speed of the primary emulsion resulted in an increase in EE and a decrease in IBR. In contrast, increasing the secondary emulsification speed resulted in a decrease in EE and an increase in IBR along with a decrease in microsphere size. The insufficient secondary emulsification time resulted in excessive increases in particle size, and excessive durations resulted in decreased EE and increased IBR. Increasing the temperature and pressure of SFEE resulted in an overall increase in particle size, a decrease in EE, and an increase in IBR. It was observed that, at low stirring rates or SC-CO2 flow rates, there was an increase in particle size and SPAN value, while the EE decreased. Overall, when the EE of the prepared microspheres is low, a higher proportion of drugs is distributed on the external surface of the microspheres, resulting in a larger IBR. In conclusion, this study contributes to the scientific understanding of the influence of SFEE process variables on PLGA microspheres.

Development of Hybrid Optimization Model Using Grey-ANFIS-Jaya Algorithm for CNC Drilling of Aluminium Alloy

Aluminium alloys are gaining popularity in a diversity of engineering applications because of their extraordinary features such as strength, resistance to oxidation, and so on. AA5052 (Al-Mg series) is generally used in antirust uses, particularly in desalination related activities, due to its better resistance to corrosion in marine applications at temperature ranges up to 125°C, lower cost, better heat-carrying capacity, and nontoxicity of its corrosion components. Drilling is one of the most commonly adopted material removal processes that is adopted in numerous engineering uses. Taguchi’s technique is engaged to arrange and examine the tests, by treating the drilling diameter and speed and as independent process factors. The studies were carried out using an L27 orthogonal array. Material removal rate (MRR), surface roughness (SR), and form/orientation error are deemed as output characteristics. Taguchi’s analysis was engaged to discover the best process factors. ANOVA is used to examine the influence of process variables. Suitable application of artificial intelligence tools for making effective decision assists the manufacturer in accomplishing the benefits in numerous engineering domains. To obtain the maximum material removal and minimum roughness, circularity (circ), and perpendicularity errors (perp), the process variables have been optimized with the help of grey-ANFIS-amalgamated with Jaya algorithm. The multiperformance index was developed using grey theory. Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best-suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.

Dominating influence of cutting-edge lead angles on arc-trajectory machining of Nomex® honeycomb composites by using a straight blade cutter

Nomex® honeycomb composites (NHCs) with circular arc features are a challenging issue in the machining of aviation curved structural components. Compared to linear feature machining, arc feature machining involves six-axis coordinated motion, introducing additional variables. Directly referencing the linear feature machining process will lead to the deterioration of contour accuracy and surface quality in arc-trajectory machining (ATM). To further explore the influence of process variables on ATM, this study developed an error model for straight blade tool (SBT) ATM and investigated the influence of cutting-edge lead angles (γ) on contour accuracy and surface quality. A vertical cutting process was proposed, and experiments proved it provided the optimal machining quality (the defect rate of core cells was only 3.93 %) compared to forward and backward inclination cutting (7.23 %∼34.3 % and 9.71 %∼17.36 %, respectively). Additionally, it was revealed that the main reason for the deterioration of surface quality on ATM was the excessive angle between the cutting edge direction and the feed direction. Based on the results above, the influence and optimization of cutting-edge lead angles were revealed, and the advantage of vertical cutting process for machining NHCs with arc-trajectory was demonstrated. This research provides a feasible method for the machining of NHCs with arc-trajectory using SBT.

Adsorptive removal of oxytetracycline using MnO2-engineered pine-cone biochar: thermodynamic and kinetic investigation and process optimization.

Indiscriminate use of oxytetracycline is linked to the development of antibiotic-resistant genes, posing a serious threat to human health and ecosystem balance. This article reports the adsorptive elimination of oxytetracycline (OTC) from aqueous solution using a newly developed MnO2-modified pine-cone biochar (MnO2/PCBC). The MnO2/PCBC was characterized using X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, CHNS analyzer, inductively coupled plasma-optical emission spectroscopy, and Brunauer-Emmett-Teller N2 adsorption analyzer. Batch adsorption experiments, designed using the central composite design framework of response surface methodology, were conducted to investigate the influence of process variables on the adsorption of OTC onto MnO2/PCBC. The optimized conditions for achieving maximum removal (88.1%) were found to be at pH 8, MnO2/PCBC dose 0.44 g/L, initial OTC concentration 200 mg/L, and temperature 303 K. The adsorption process follows Langmuir (R2=0.95) and Freundlich (R2=0.95) isotherms and pseudo-second-order (R2=0.99) adsorption kinetics. The adsorption process was found to be endothermic (ΔH0 = 33.04 kJ/mol) and spontaneous in nature (ΔG0 from -1.33 kJ/mol at 283 K to -5.65 kJ/mol at 313 K). The synthesized MnO2/PCBC could be recycled and reused for OTC removal with a percentage removal of around 80% after fifth cycle. The results indicate an effective removal of oxytetracycline with only 0.44 g/L MnO2/PCBC with maximum adsorption capacity of 357.14 mg/g which demonstrates improved performance in comparison to many adsorbents reported in literature. This implies that MnO2/PCBC offers potential to be developed into a cost-effective technique for antibiotic removal from water.

Kinetic evaluation of Pachira aquatica Aubl biomass slow pyrolysis towards to biochar production

The abrupt climate change, caused by the anthropogenic activities in the environment, intensified the search for sustainable sources of energy aiming reduce the dependence on fossil fuels. In this study, a multivariate study design was applied within a batch reactor system to determine the influence of process variables and kinetic parameters of slow pyrolysis of Pachira aquatica Aubl fruit peel towards biochar generation. The statistical evaluation of Box Behnken planning model was applied and showed good adjustment to the model establishing the model that describes the significant effect of variables behavior. The maximum biochar yield (41.22%) was observed were temperature (T) = 406 °C, heating rate β = 2 °C min−1, and residence time t R = 60 min, under nitrogen atmosphere. It is also observed that temperature was the most substantial influence on the process, followed by heating rate and the remaining process variables did not exhibit significant individual effects. The empirical model obtained was applied into mass change equation aiming calculate the activation energy (Ea)=77.10 kJ mol−1 and frequency factor (A 0)= 6.28 × 1010 s−1. The low activation energy in maximum biochar yield region showed a great potential of Pachira aquatica Aubl fruit peel thermoconversion towards to biochar.

Valorization of lignocellulosic waste (coconut coir) for bio-vanillin production having antioxidant and anticancer activity against human breast cancer cells (MCF-7)

The usage of agro-waste for producing natural flavor has gained research interest. Vanillin is a vital flavoring compound widely used in food industries. In the present study, Bacillus aryabhattai NCIM 5503 efficiently utilizes the temple waste coconut coir as the sole carbon source for bio-vanillin production. The most influential process variables, i.e., temperature, pH, and trace metal solution, were identified based on central composite rotary design. Response surface methodology was employed to optimize these process variables, and an enhanced bio-vanillin yield (14.78 %) was obtained. The result demonstrated that a yield of 0.528 ± 0.04 g/100 g bio-vanillin was obtained under optimum conditions (temperature 30 ℃; pH 9; trace metal solution 1.27 mL) after 72 h of fermentation. The predicted response was experimentally validated, resulting in a maximum bio-vanillin of 0.533 ± 0.03 g/100 g. High-performance thin-layer chromatography (HPTLC) of extracted bio-flavor showed a distinct fingerprinting profile similar to bio-vanillin. The bio-flavor produced by B. aryabhattai was characterized as bio-vanillin by FTIR and GC-MS. The antioxidant and anticancer potential of bio-vanillin were also studied. The result revealed that the extracted bio-vanillin has anticancer activity against human breast cancer cells (MCF-7). The experimental results showed the feasibility of SSF as an alternative for producing bio-vanillin through agro-waste valorization.

Extraction of Phosphorus from Sewage Sludge Ash—Influence of Process Variables on the Electrodialytic Process

Phosphorus is a critical, irreplaceable raw material, and developing methods to recover P from secondary sources such as sewage sludge ash (SSA) is crucial. Two-compartment electrodialytic extraction (2C-ED) is one method where an electric DC field is applied to extract P and separate heavy metals simultaneously. Several process parameters influence 2C-ED, and they influence each other mutually. This paper explores chemometrics modeling to give insight into the 2C-ED process and, specifically, optimization of the experimental parameters towards 80% P extraction. A projections-to-latent-structures model was constructed based on new 2C-ED experiments conducted with one SSA type. The model was stable (high correlation factor and predictive power). Variable importance in the projection (VIP) plots showed that the influence of the variables was in the order: current > duration > L:S ratio > stirring velocity > dispersion solution (weak acid or distilled water). Contour plots were used for exploring different P extraction strategies. For example, more P mass per unit current was extracted at an L:S ratio of 7 compared to L:S 14. This shows that treating a thicker SSA suspension is preferable to optimize the current efficiency. The chemometric model proved valuable for optimizing the 2C-ED process and future scale-up.

Sustainable remediation of toxic congo red dye pollution using bio based carbon nanocomposite: Modelling and performance evaluation

Remediation of synthetic dyes found in aqueous environment poses a serious challenge for treatment due to their resistance to chemical and biological degradation. This research study investigated the application of Chitosan-ZnO-Seaweed bio nanocomposite in the remediation of congo red. The novel bionanocomposite was characterised by FTIR, SEM, TEM, EDS and XRD studies. The FTIR spectra and SEM images indicated the adsorption of congo red onto the synthesized bionanocomposite. The batch wise experimental studies were done to explore the influence of process variables on removal of congo red from synthetic wastewater and to determine optimized conditions. Under optimized conditions of pH 3, temperature 40 °C, initial congo red concentration 50 mg/L, bionanocomposite quantity 0.03 g/L and interaction period 30 min, the bionanocomposite removed 95.64% of congo red. Thermodynamic studies were carried out and the parameters, ΔH° and ΔS° were found to be 38.386 kJ/mol and 0.1451 kJ/mol. K, respectively. The isotherm and kinetic study showed that monolayer Langmuir model was obeyed (R2 = 0.968) and the experimental value of congo red adsorption correlated well with pseudo second order model (R2 = 0.9938) respectively. The maximum adsorption capacity was found to be 303.03 mg/g. Protonated amino group of chitosan, hydroxyl group of seaweed accounts for congo red adsorption along with zinc oxide.

Fluidized Bed Co-Melt Granulation: New Insights in the Influence of Process Variables and Validation of Regime Map Theory

Fluidized Bed Co-Melt Granulation: New Insights in the Influence of Process Variables and Validation of Regime Map Theory

PLA stereocomplex-chitosan nanoparticles loaded with tenofovir alafenamide as a long-acting antiretrovirals

Antiretroviral therapy (ART) is a major method of HIV and AIDS treatment; however, it has several limitations, such as poor drug availability, cytotoxicity or renal clearance of the drug molecules. The drugs can be encapsulated in biocompatible polymeric nanocarriers to overcome these limitations. Therefore, the NPs composed of different ratios of poly(l-lactide) PLLA, poly(d-lactide) PDLA, and chitosan (CHI) were prepared by spray-drying technique. Subsequently, the NPs were loaded with the antiretroviral drug - tenofovir alafenamide (TAF). The influence of process variables and nanoparticles (NPs) composition on particle size, drug encapsulation and release was investigated. Finally, it was proved that obtained formulations are non-toxic, and their antiviral efficiency was quantified by JurkatE6 cells infected with HIV. Our findings ascertain that PLLA/PDLA/CHI nanocarriers have great potential for delivering anti-HIV therapeutics.

Optimasi Sudut Baji, Kecepatan Pemakanan & Rpm Terhadap Kekasaran Permukaan Material SCM 440 Dengan Metode Respon Surface (RSM)

The development of manufacturing technology has developed so rapidly. In this study, SCM 440 steel material was used, which is an alloy steel of chromium molybdenum. This steel has the advantages of stable composition,low harmful elements,high steel purity. Surface roughness is important, surface roughness is defined as the irregularity of surface configuration in an object resulting from a finishing process. This study aims to determine the influence of process variables on the surface roughness rate of SCM 440 material by varying the total cutting angles of 700,750 and 800 then variations in feeding speed of 0.08mm, 0.09mm, and 0.10mm and spindle speed or RPM, namely 160,220, and 280 puts / min in the RSM method. The Rspon Surface method is a set of mathematical and statistical techniques that are useful for analyzing problems where several independent variables affect the response variable and determine the optimal value of the process variable. From the results of the study, the value of the Second order yˆ = + 0.092224 X1² + 0.208515 X2² - 0.03661 X3² was obtained. With stationary point value X0 = ( total Cut angle ) = - 0.382409, X0 = (feeding) = 0.161715, X0 = (RPM) = 0.578250. and found the optimal values of Wedge Angle (78.212), Feeding Speed (0.095 mm) and RPM (278.29 put/min). Then it can be analyzed the optimal value that is different from the value of the RSM method framework and if the values are the same then the research fails.

Adsorption of methylene blue dye onto modified activated carbon produced from groundnut shells

In this research work, groundnut shells agricultural byproducts were utilized for the production of modified groundnut shell based activated carbon (MGSAC) through the use of phosphoric acid and ethylene-diamine tetraacetic acid disodium salt (Na2EDTA) as an activating agent and a modifier, respectively. A three factor, two-level full factorial design (FFD) was employed for the exploratory design of experiments (DoE). The independent process variables are temperature, activation time, and activating agent concentration for the production of MGSAC in a muffle furnace. The product yield and methylene blue (MB) dye adsorption were considered as the performance indicators for the process. Regression analysis was conducted to examine the influence of process variables on the responses of the process parameters. From the analysis, it was found that the activation temperature has the most significant effects on the MGSAC product yield and the activation time for the adsorption of MB dye. The results obtained showed that the best operating conditions for production of MGSAC were carbonization temperature of 450°C, activation time of 30 min and activating agent concentration of (35 mmol Na2EDTA; 50% H3PO4) which resulted in the product yield of 55.5% MGSAC, and 99.6% MB dye adsorption. It was also observed that experimental values obtained were in good agreement with the values predicted by the model. Hence, the two-level FFD DoE technique demonstrated worthwhile features in disclosing the dominant factors that affect the production of modified groundnut shell based activated carbon. The products appear to be promising adsorbents for the adsorption of cationic MB dye from wastewaters.

Pressurized Liquid Extraction (PLE) in an Intermittent Process as an Alternative for Obtaining Passion Fruit (Passiflora edulis) Leaf Hydroalcoholic Extract (Tincture)

Tinctures are medicinal plant extracts obtained by extraction with a hydroalcoholic solution (70%) by percolation (PER). This process takes about 26 h to prepare, in addition to using a large amount of solvent. In our research, passion fruit leaf tinctures were obtained using extract with the same pressurized hydroalcoholic solution as in an intermittent process. The objective was to demonstrate that this emerging technology can be economical and profitable. An optimization using Central Composite Rotatable Design (CCRD) was performed to evaluate the influence of process variables on the yields and compositions of the extracts. The temperature (T) was the factor that most influenced the responses. Extraction with pressurized liquid (PLE) provided total yields and total phenolic and flavonoid contents in greater amounts than PER. The optimized conditions of the process variables studied in the CCRD for the highest content of total phenolics (43.2 mg GAE/g) and flavonoids (58.8 mg QE/g) were at 100 °C with a rinse volume of 120% of the divided extractor volume in four cycles of the intermittent process. When adjusting the PLE in an intermittent process, and according to the one-dimensional mass transfer by the continuous diffusion of the Fick model, the effective diffusion coefficient (1.28 × 10−12 m2/s) was not affected by T. The kinetic curve of PLE extraction indicates that the adjusted intermittent process occurred in the period of the constant extraction rate when compared to the kinetics of the semi-continuous process. The yielded extracts were rich in isovitexin, and the highest levels were identified in the extracts obtained via PLE, indicating that this intermittent process can bring a product to market with the same quality but with a much shorter production time and the use of fewer solvents. Antioxidant activity, determined by DPPH, FRAP and ORAC, was also higher in extracts obtained via PLE.

Optimization of stir casting and drilling process parameters of hybrid composites

AA2219 alloy is widely used in aerospace and automobile applications, wherein the properties can be enhanced with 15% wt. of B4C reinforcement particles. Assembly task in aerospace application requires drilling millions of holes, and it is often challenging to obtain good-quality drilled holes due to the presence of hard B4C particle reinforcements. The self-lubricating capability of molybdenum disulfide (MoS2) and Graphene (Gr) materials was used as secondary reinforcements to improve the drilled hole quality characteristics. The stir-casting route fabricates the hybrid composites (AA2219 alloy/B4C/Gr/MoS2). The hardness and wear resistance properties of hybrid composites are affected by the influencing process variables such as percent reinforcement of Gr and MoS2, stirring speed, and pouring temperature. Taguchi L9 matrix is used for experimentation and performs statistical analysis. All stir-casting variables are found to make significant contributions toward hardness and wear resistance. The limitation of the Taguchi method to solve multiple objective optimizations is solved by applying Data Envelopment Analysis Ranking (DEAR) method. A DEAR method determined optimal conditions (Gr and MoS2: 1.5 wt%, stir speed: 400 rpm, and pouring temperature: 760 °C) resulted in a reduced wear rate of 1.65 × 10−3 mm3/min and 128 HV hardness in hybrid composites. The hybrid composites were prepared for the determined optimal stir casting conditions. Drilling experiments were carried out to analyze the variables such as feed rate (FR), drilling speed (DS), and drill tool material (DM): high-speed steel: HSS, carbide: C, and coated carbide: CC that affect the hybrid composite hole quality characteristics such as burr height: BH, material removal rate: MRR, and thrust force: TF. A DEAR method determined optimal drilling conditions (FR: 0.25 mm/rev; DS: 20 m/min; DM: coated carbide drill tool) resulted in 645 mm3/min of MRR, 2.95 kN for TF, and 0.16 mm for BH, respectively. The self-lubricating capability of Gr and MoS2 reinforcement particles in hybrid composites ensures excellent composite properties and drilled-hole quality characteristics. Taguchi and DEAR methods employ simple mathematical steps which can be used by novice industry personnel to perform optimization for other output characteristics.

Strategy for tailoring thermoplastic forming process incorporating the influence of process variables in bulk metallic glasses

The technical interest in bulk metallic glasses (BMGs) has grown over the past few decades due to their potential for new areas of applications based on thermoplastic forming (TPF), which was previously unattainable in conventional crystalline alloys. However, the difficulty in controlling the TPF process due to the metastability of the amorphous phase has posed a barrier to widespread commercial use. This study provides practical guidelines for tailoring the TPF process incorporating the influence of process variables in BMGs. Specifically, we constructed a continuous heating transformation (CHT) diagram with iso-viscosity contours for LM1b (Zr44Ti11Cu10Ni10Be25) using Flash-DSC measurement. As an example of a TPF process utilizing the obtained CHT diagram, we demonstrated three TPF procedures from bulk to nano scales, namely BMG pressing, BMG joining, and hologram nanopatterning. Interestingly, with increasing heating rate, the TPFA is enhanced, although the incubation time for crystallization decreases. Furthermore, we proposed a new TPFA parameter, P, which considers both the supercooled liquid viscosity and crystallization kinetics to compare the TPFA of various BMGs. Especially, we constructed a plot depicting the correlation between P and calculated maximum elongation, and heating rate to investigate quantitatively the relationship between TPFA and heating rate. These results will enable us to select the most suitable BMG for the targeted applications and precisely optimize the TPF processes, which could lead to further improvements in their performance and expanded applications in various industries.