L9 Orthogonal Array Research Articles

Investigation on Water Erosion Behavior of Ti-based Metal Matrix Composite: Experimental Approach

Wet steam flow produces big water droplets in the low-pressure zone of a steam turbine blade. These droplets clash with subsequent blades, resulting in a strong impact that is evident as erosion. Titanium and its alloys are valuable for technical applications such as turbine blades because of their low density, high strength, and exceptional corrosion resistance. The boron carbide(B4C) has a high hardness but a low strength; therefore, it's exciting to investigate water erosion of Ti/ B4C and SiC combination. The effect of 1 wt% B4C and 1, 3, 5, and 7 wt% SiC particles on water droplet erosion of Ti composite was studied using the SPS method for 5 minutes at 1200 oC temperature and 50 MPa pressure. The L9 orthogonal array with four levels of parameters of the Taguchi method is used to conduct the experiments. By measuring the weight of the specimen at interval time, the erosion behavior with time is obtained with different nozzle diameters. The effect of material and experimental parameters on erosion resistance is studied, and an empirical relation is developed.

Development of PCM tile for residential buildings in hot and dry climate: design and optimization

In recent years, the building sector has become more conscious of sustainability, and the use of phase change materials (PCMs) in concrete has gained more attraction. Integration of PCM with building facades is a successful method to reduce energy consumption and improve human comfort. However, no single PCM can work in an all-weather scenario. Hence, in this research work, an attempt is made to select a suitable PCM for Chennai city, India, and this methodology can be employed at any geographical location. The PCM tile is designed by including certain features to increase the thermal conductivity of the PCM zone. The optimum design of the PCM tile is achieved through multi-objective optimization techniques. L27 orthogonal array is employed, and all the tests were conducted through validated numerical simulation. Redesigned PCM tile includes a PCM layer of 2 cm thickness with a 10% mix of copper nanoparticles covered by plaster. Redesigned PCM tile reduces the peak indoor temperature by 6.62℃ compared with conventional roof systems.

Optimizing Cylindrical Grinding Proficiency and Surface Finish for EN24 Steel Alloy with the Use of Taguchi Analysis and Artificial Neural Network

Grinding is a material removal procedure used at the end of manufacturing to obtain high dimensional precision and a desirable surface polish. External cylindrical grinding is a type of grinding procedure that used to grind cylindrical things such as engine shafts, connecting rods, spindles, and axles. This study examines how control settings affect response parameters using EN24 alloy steel on a cylindrical grinding machine. Response parameters are material removal rate (MRR) and surface roughness (Ra), whereas control parameters are workpiece speed (v), feed rate (f), and depth of cut (d). Taguchi DOE is employed with L16 orthogonal array to optimize control parameter levels, followed by cylindrical grinding tests.An artificial neural network (ANN) model was created to validate and predict cylindrical grinding reaction parameters. To train the network, experimental data was used, and ANN predictions were compared to real data. Data collection has also completed.In the purposed work minimum Ra is 0.52 µm and maximum MRR is 0.6588 g/sec found and results indicate that feed rate and workpiece speed are the most dominating parameters of cylindrical grinding. The experimental results can be employed by various manufacturing and industrial firms and they can select suitable combinations of input parameters for desired Ra and MRR

Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology

Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency.

Influence of brown algae filler and process parameters on the surface roughness and MRR of jute fiber polymeric composite machined by abrasive water jet

Traditional manufacturing of polymeric composite leads to delamination. Implementing abrasive water jet machining (AWJM) presents a sustainable solution for shaping the polymeric composites, thereby eliminating the need to dispose of chemically contaminated waste. Brown microalgae, commonly found in aquatic environments, serve as viable additives for enhancing the properties of polymeric composites. This study entails the polymeric composite reinforced with jute fiber fabricated by modulating the weight percentages of brown algae powder by 0, 3, and 6 wt.% utilizing the hand layup procedure. The composites were formed and subsequently subjected to drilling by AWJ machining filled with brown algae. The experimental investigation was done to analyze the effect of AWJ parameters: water jet pressure (WJP), traverse speed (TS), and stand-off distance (SoD)—on the material removal rate (MRR) and average surface roughness ( Ra). Orthogonal Array L27 experimental results revealed that polymeric composite reinforced with jute fiber containing 3 wt.% of brown algae exhibited the highest MRR, with an increase of up to 12% compared to other samples. Additionally, these composites demonstrated a significant reduction in surface roughness, reaching up to 8% when compared to alternative samples. Utilizing the Taguchi-based ANOVA method facilitated a systematic exploration and identification of influential factors impacting both MRR and Ra in AWJ machining. Notably, the WJP and SoD emerged as key factors significantly influencing both MRR and Ra.

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

Crashworthiness study of polyamide bi-tubular thin-walled tubes using hybrid lattice filling

Thin-Walled Tubes (TWT) are widely used as crashworthiness elements to absorb and dissipate kinetic energy during collision through plastic deformation. Various design strategies, including nested tubes, triggers, and filling with lattices, are commonly used to enhance the crashworthiness of TWT. Additive Manufacturing (AM) offers unique opportunities to produce complex lattice-filled TWT with higher precision, but challenges persist in the design and fabrication of bi-tubular TWT to enhance crashworthiness. The aim of this study is to propose an approach for hybrid lattice filling in bi-tubular structures. In the preliminary phase, the parametric study was conducted to understand the influence of tube cross-section geometry, thickness, and trigger hole diameter on the crashworthiness of empty TWT using Taguchi’s L9 orthogonal array. Empty TWTs were fabricated using Selective Laser Sintering (SLS) with PA12 material and compressed uni-axially at 8 mm/min speed. In the second phase, bi-tubular TWT was filled with three different unit cells such as Cube, Kelvin, and Octet Truss (OT) having 30% relative density. In the lattice filling approach, two different strategies were followed such as uniform and hybrid lattice filling. Designed TWTs were fabricated and tested under uni-axial compression at two different speeds such as 8 mm/min and 8 mm/sec. Based on the results of the preliminary study, it has been observed that cross-section geometry and tube thickness significantly enhance SEA through an increase in the stiffness and number of folding. With the help of the Signal to Noise (S/N) ratio graph, appropriate levels were selected as input for the hybrid lattice-filling approach. The results of the second phase revealed that hybrid lattice filling significantly enhances the deformation modes, energy absorption, and crashworthiness properties of TWTs. Hybrid lattice-filled TWT offers better Specific Energy Absorption (SEA) as 18.32 kJ/kg at 8 mm/sec compression speed, which is 113.9% higher than empty and 42.8% higher than uniform lattice-filled TWT. This work demonstrated that adopting the hybrid lattice-filling approach is one of the potential ways to enhance the crashworthiness of protective equipment such as crash boxes and frames.

Enhancing the insecticidal efficacy of Allium sativum extracts through microencapsulation via complex coacervation

Garlic (Allium sativum L.) has been widely studied for its insecticidal properties. The primary bioactive molecule in garlic extracts include allicin, alliin, S-allylcysteine, diallyl disulfide, diallyl trisulfide, diallyl sulfide and ajoene. However, these compounds degrade under environmental conditions once extracted. This study aimed to enhance the effectiveness of garlic extracts in controlling Tenebrio molitor by optimizing microencapsulation techniques. The garlic extracts were encapsulated using the complex coacervation method, with independent variables including pH levels (3, 6 and 9), whey protein isolate (WPI) (4 %, 6 % and 8 % w/v) and pectin (0.50 %, 0.75 % and 1.00 % w/v). A Taguchi L9 (33) orthogonal array was employed to design 9 treatments, and T. molitor mortality was assessed 72 h after a 10 sec immersion of the insects in the treatments. Statistical analysis revealed that WPI had the most significant influence (24.52 %), followed by pH (18.82 %) and pectin (7.79 %). The interaction between pH and pectin had the greatest effect on the encapsulation process, accounting for 38.65 % of the influence. The optimal microencapsulation conditions were predicted by software to be pH 3, a pectin concentration of 0.75 % w/v and a WPI concentration of 4.00 % w/v, resulting in a signal-to-noise (S/N) ratio of 42.30. Experimental validation of these conditions produced an S/N ratio of 18.54, corresponding to a T. molitor mortality rate of 92 % ± 4.47 %. The resulting microcapsules had diameters ranging from 1–5 ?m. Complex coacervation is a highly promising method for microencapsulating garlic extracts and preserving their insecticidal properties.

COMPARATIVE STUDY OF DIFFERENT CUTTING FLUIDS ON TOOL-WORK INTERFACE TEMPERATURE DURING TURNING OPERATION ON 6061 ALUMINUM ALLOY

This study investigated the impact of tool-work interface temperature during the turning process of a cylindrical workpiece made of 6061 aluminum alloy. The experiment utilized four different cutting fluids: palm oil-based cutting fluid (POBCF), neem seed oil-based cutting fluid (NOBCF), orange seed oil-based cutting fluid (OSOBCF), and mineral oil-based cutting fluid (MOBCF) using uncoated carbide cutting tool of grade H13A. Various machining parameters were considered, including spindle speed (180, 250, 355, 500 rpm), feed rate (0.105, 0.116, 1.4, 1.6 mm/rev), and depth of cut (0.5, 1.0, 1.5, 2.0 mm). The experimental design followed the Taguchi specified L16 (43) orthogonal array and was conducted on a Lathe Machine XL 400. To measure the tool-work interface temperature, an infrared thermometer (KM 690) was employed during the aluminum alloy machining process. Subsequently, a mathematical model for the tool-work interface temperature values was developed through regression analysis using Minitab 16. The significance of the chosen machining parameters and their respective levels on the tool-work interface temperature was determined using analysis of variance (ANOVA) and F-test. The findings indicated that machining under orange seed oil-based cutting fluid (OSOBCF) conditions resulted in a 9.02%, 16.4%, and 21.7% lower temperature at the tool-work interface compared to palm oil-based cutting fluid (POBCF), neem seed oil-based cutting fluid (NOBCF), and conventional oil-based cutting fluid (MOBCF), respectively. This suggests a potential for producing higher-quality products under orange seed oil cutting fluid conditions compared to other wet conditions.

Experimental Investigation of Electro-Discharge-Machined EN-24 and EN-42 Alloys

<div>The EN24 and EN42 materials were machined by the electric discharge machine (EDM). The study aimed to optimize the input variables for the multiple outputs, such as metal removal rate (MRR), tool wear rate (TWR), and surface roughness. The machining of the metal is essential to analyze the surface quality and the production rate. The MRR is a prediction of the production rate and surface roughness resembling the quality of the surface. The input variables were current (A), pulse on time (t<sub>on</sub>), and pulse duty factor (T). The three levels of current were 3A, 6A, and 9A. The t<sub>on</sub> time was selected as 30 μs, 50 μs, and 70 μs. The pulse duty factors were selected as 4, 5, and 6. The Taguchi optimization techniques are used to optimize process parameters. The L9 orthogonal array was selected for the process. ANOVA analysis was employed to check the rank of the input parameters relative to the output. The maximum MRR were at 9A, 70 μs, and 4 duty factor for the EN24. The best MRR were at 9A, 70 μs, and 5 duty factor for the EN42. The contribution of t<sub>on</sub> was maximum compared in the tool wear analysis. The optimum value of tool wear was at 6A, 70 μs, and 4 duty factors for the machining of EN42 and EN24. The surface analysis for EN24 was yielding at 9A, 70 μs, and 4 duty factor, and 9A, 70 μs, and 5 duty factors for the EN42. The maximum contribution of pulse on time for surface finish for machining both the materials. The scanning electron microscopy (SEM) analysis also analyzed the surface quality.</div>

The effect of pulverized glass waste particle sizes on the mechanical properties of AA6061-T6 friction stir welded joints.

Abstract The study sought to investigate the effect of pulverized glass waste (PGW) particle size as reinforcement for AA6061-T6 joints produced by Friction Stir Welding. The study utilized three particle sizes of 15 microns, 45 microns and 75 microns of the PGW as reinforcement alongside the established process parameters ranges of 900-1400rpm, 25-63mm/min and 1-2.5° in a Taguchi L9 orthogonal array for the welding process experimental design. The welding experiments were repeated for each reinforcement particle size mentioned above. Parallel-hole reinforcement strategy was used on all joints for the application of the PGW, Tensile strength, Hardness tests and Microstructural Analysis were carried out on the welded joints and subsequently, analysis of the data. For tensile strength, several sample sets showed a trend of higher tensile strength the smaller the PGW particles size (Figure 6). For hardness, however, there was no overall, discernable trend/pattern of increase in hardness as the particle size decreased. The highest average tensile strength value obtained was 85.25MPa. The lowest tensile strength was 14.26MPa. A distinguishing feature between the highest and lowest value for tensile strength is that the former was obtained with a traverse speed of 25 mm/min while the latter was obtained using a 40 mm/min traverse speed. The higher the rotational speed of the tool pin, the greater the heat of friction generated while the lower the traverse/welding speed, the greater the heat of friction generated as the tool pin spends enough time per unit length to generate sufficient heat and cause plastic deformation sufficiently high enough to cause grain refinement. Using imageJ, percentage distribution of PGW for each crucial zone (Nugget/Stir zone, Thermo mechanically affected zone and Heat affected zone) of the FSWed joint was generated for samples selected for microstructural analysis. The average value for each sample was obtained as well. The highest tensile strength value (85.25MPa) was obtained with a sample using the smallest PGW size (15 µm), in line with the trend (figure 6) in which tensile strength was greater the smaller the PGW size used. The highest hardness value (90.90 BHN) was obtained with the sample having the highest average value for percentage distribution of the PGW (58.06%). A distinct trend was noted in which the greater the percentage distribution of the PGW, the higher the hardness value obtained (figure 30).

A comprehensive study on the effects of printing parameters on the mechanical properties of PLA

Purpose This study aims to investigate the effects of five different printing parameters, namely, printing speed (PS), printing temperature/nozzle temperature/extrusion temperature, heated-bed temperature, raster angle (RA) and layer height (LT), on mechanical properties. Design/methodology/approach American Society for Testing and Materials (ASTM) standards were used for the specimen design. Then, the Taguchi method was used for the design of the experiment and an L16 orthogonal array was preferred. Tensile, Shore D and surface roughness tests were conducted on polylactic acid test specimens. The test results were analyzed using the signal-to-noise ratio and analysis of variance (ANOVA). Findings As a result of the study, it was seen that RA is the most important parameter for the tensile strength, PS is for the hardness and LT is for the surface roughness. According to the ANOVA results, the effects of the RA, PS and LT on the maximum tensile strength, hardness and surface roughness were 41.59%, 69.51% and 44.6%, respectively. Originality/value To the best of the authors’ knowledge, this study is one of the most comprehensive parameter optimization studies for additive manufacturing in the literature because it includes five different printing parameters and three mechanical test procedures.

An assessment of PLA/wood with PLA core sandwich multilayer component tensile strength under different 3D printing conditions

Material extrusion is increasingly used to make functional parts in small batches that are challenging to produce with traditional machining. Also, intensive efforts are being made to develop new eco–friendly materials. This work investigates the strength of multilayer samples made in sandwich form with 4–5–4 layers of 0.3 mm layer thickness, externally with polylacticacid wood (PLA/wood, 61.5 % of specimens' material) and internally with pure PLA (38.5 % of specimens' material), under tensile loads. The intent is to investigate the possibility of manufacturing biocompatible components that take advantage of the excellent surface properties of wood externally and the durability properties of PLA internally. For this purpose, a designed experiment following the Taguchi L9 orthogonal array was prepared, and nine samples were fabricated: three with pure PLA, three with a sandwich PLA/wood–PLA–PLA/wood form, and three with composite PLA/wood form. Printing speed and temperature were varied during the experiment, and the results were examined using the analysis of means and residuals. Sandwich specimens improve tensile strength and elastic modulus by 100 % and 50 % compared to PLA/wood components while exhibiting slightly better surface roughness parameters, i.e., Ra and Rz, about ∼10 % lower values. Additionally, even if PLA parts showed better strength and surface texture than sandwich parts (∼100 % and ∼56 % higher tensile strength and elastic modulus), they had lower performance in terms of PLA–PLA/wood material ratio, i.e., 160 % more PLA than sandwich parts. The findings of this research, with the potential to design functional and sustainable new products with optimal performance, are significant and can be exploited in various industries.

Taguchi Method Statistical Analysis on Characterization and Optimization of 18-nm Double Gate MOSFETs

A bi-layer graphene with a multigate structure was intensified and analysed on an 18-nm Metal Oxide Semiconductor Field-Effect Transistor (MOSFET) device to obtain an optimal performance parameter. The device has a gate structure made of Titanium Dioxide (TiO2) that serves as a high-k material and a metal gate made of Tungsten Silicide (WSix). The Silvaco TCAD Software which are ATHENA and ATLAS modules were used to enhance the fabrication process of virtual devices and to verify the electrical properties of a specific device. According to the International Technology Roadmap Semiconductor (ITRS) specifications of 0.179 V ± 12.7% for threshold voltage (VTH) and 20 nA/m for leakage current (ILEAK), the Taguchi L9 orthogonal array strategy was used to improve the device process parameters for optimum VTH and ILEAK. For the NMOS device, the process parameter of VTH Adjust Implant Dose was used as the dominant factor while Source/Drain (S/D) Implant Energy was used as the adjustment factor whereby for PMOS device, S/D Implant Energy was the dominant factor while S/D Implant Tilt was the adjustment factor in order to achieve a robust design through the Taguchi method implementation. The percentage affecting the process parameter is then applied to the results of the signal to noise ratio (SNR) of Nominal-the-best (NTB) for VTH and Smaller-the-better (STB) for ILEAK.

A HYBRID MEREC-TOPSIS APPROACH FOR THE IMPROVEMENT OF PHYSICAL VAPOUR DEPOSITED TITANIUM CARBO-NITRIDE COATING

Titanium carbo-nitride (TiCN) comes under the metal nitride group which can provide a combined property of titanium carbide (TiC) and titanium nitride (TiN) coating. TiCN Coating possess an excellent mechanical and tribological, properties which leads its application in many industries particularly in the Automotive and aerospace industries. TiCN films can be very hard and strong based on the composition and synthesis process. Physical Vapor Deposition (PVD) technique is widely used for the preparation of thin film coating because of its ability to precisely control the composition and thickness of the coatings. The properties of the developed coating significantly affect by the PVD process parameters and their levels. Multi-Criteria Decision Making (MCDM) methods are widely used in many sectors for the selection of process parameters based upon some specific criteria. In the present work TiCN coatings were synthesized by using one of the most widely used PVD method called magnetron sputtering. L16 orthogonal array was used as a design of experiment for the experimental work by varying the sputtering process parameters like bias voltage, N2 flow rate and substrate to target distance. After the synthesis, the developed films were tested using atomic force microscopy (AFM), Scanning electron microscopy (SEM), and Nanoindentation. From the characterization three response parameters such as hardness (H), Modulus of elasticity (E) and surface roughness (Ra) of the coating has been considered. A hybrid method based on improved removal effects of criteria- technique for order performance by similarity to ideal solution (MEREC-TOPSIS) approach has been considered for the for the process parameters selection. The results have also been compared with other weight calculation techniques. In all the cases it is observed that experiment no 16 and 15 have got the 1st and second rank respectively. However, experiment no 1 is the last rank in all the cases. From the correlation analysis it is found a strong positive correlation between MEREC-TOPSIS and other methods. The method provides a significant advancement in the selection of optimal parameters, ensuring enhanced coating properties crucial for industrial applications.

Optimization of Polyvinylidene Fluoride/Polyvinyl Alcohol Electrospun using Taguchi Method for Tissue Engineering Application

Composite nanofibers for tissue engineering applications were prepared with polyvinylidene fluoride and polyvinyl alcohol via a horizontal electrospinning process. The effect of the processing parameters (polymer concentration, voltage, feed rate and tip-to-collector distance) on the fibre diameter was studied using L9 orthogonal arrays of the Taguchi Method, S/N ratio, and ANOVA to produce uniform and finest fibre. The optimum parameters were at 90 wt% PVDF ratios for polymer concentration, applied voltage at 10 kV, feed rate at 0.5 mL/h and tip-to-collector distance at 15 cm. The PVDF/PVA electrospun compromises 171.60 nm nanofiber diameter with homogenous morphology and no bead formed. MTT and live/dead kit assay analysis toward human (HSF) cells confirmed the potential of the PVDF/PVA electrospun to be used as an alternative tissue template to allow new cell or tissue formation in the future.

Evaluating the effectiveness of the TOPSIS approach for three-wire electrode machining of D2 steel using the wire EDM method

Due to the high demand for D2 steel as a tool material and the difficulty of the machine, optimization of process parameters in advanced manufacturing machines is needed. This study investigates three wire electrodes: brass, coated copper, and annealed copper, analyzing their impact on tool material. Employing 0.25 mm wires, 10 mm D2 steel cubes are cut for consistent comparison. An L27 orthogonal array tests six parameters at three levels, optimizing with analytic hierarchy process technique for order preference by similarity to the ideal solution (AHP-TOPSIS). The response parameters were the metal removal rate (MRR) and kerf width (KW). Pulse on/off time, wire tension, spark voltage, input current, and wire feed rate vary systematically for each wire. The tests validate the efficacy of the AHP-TOPSIS method in optimizing WEDM parameters and machining performance. ANOVA reveals pulse-on and pulse-off times as crucial factors for various wire electrodes. Under diverse conditions, pulse duration increases spark efficiency. Based on the AHP-TOPSIS method results, weights of outputs revealed that the annealed copper wire yields the highest MRR value (0.232 mm3/sec). The brass wire exhibited the lowest MRR value (0.127 mm3/sec) compared to the others.

Taguchi-based grey relational analysis for multi-response optimization of the characteristics of HRAMMCs reinforced with agro-waste and SiC produced by ultrasonic-assisted bottom pour two-stage stir casting

Abstract This study aims to examine the impact of agricultural waste materials—specifically silicon carbide (SiC) and palm sprout shell ash (PSSA)—on the mechanical properties, including density, porosity, tensile strength, compression strength, impact strength, and hardness, as well as the tribological behavior of Al-Cu-Mg alloy-based HRAMMCs. Parametric optimization was conducted on HRAMMCs to predict the effect of input constraints on the performance of the composite, considering the weight percentage of SiC, PSSA, and ultrasonic-assisted stirring time. Taguchi’s L9 orthogonal array was used for the design of experiments (DOE), and the composites were fabricated accordingly. Their physical, mechanical, and tribological properties were determined experimentally. Taguchi-based Grey Relational Analysis for multi-optimization highlighted the potential of the HRAMMCs, with a density of 2.545 g cm−3, porosity of 5.810%, ultimate tensile strength of 341 MPa, flexural strength of 321 MPa, compressive strength of 394.016 MPa, Vickers hardness of 136.883 HV, wear rate of 6.88E-12 m3 m−1, and a coefficient of friction of 0.397. ANOVA shows that the developed mathematical model is a better fit for examining the impact of various factors on the GRG of and corresponding properties of developed HRAMMCs, Indicating the R2 value of the developed model is 99.33% (0.9933). The 2 wt% SiC, 2 wt% PSSA, and a stirring time of 7 min are optimal parameters for the present HRAMMCS; to reduce porosity, wear loss, and the coefficient of friction while increasing, ultimate tensile strength, compressive strength, and Vickers microhardness. Moreover, the examination of the tensile and impact fracture surfaces and worn surfaces was carried out using SEM analysis of the alloy and composite produced under the optimal experimental conditions. The results of the fracture surface analysis indicated that the failure of both tensile and impact fractures was due to an amalgamation of ductile and brittle behaviors. The composites exhibited lower ductility than that of the base alloys. A study of the wear mechanism revealed that it was a mixture of adhesive and abrasive wear mechanisms. The SiC and PSSA ceramic reinforcements demonstrate higher hardness compared to the alloy, which restricts the fluid-like movement of the matrix. When these reinforcements were added to the alloy, they substantially decreased the occurrence of severe delamination and the formation of adhesive wear particles.

Efficient optimization of friction stir welding parameters for AA7075 and AA6082 alloys: A Hungarian method approach

Friction stir welding (FSW) is a key technique for welding high-strength aluminium alloys without melting, making it indispensable in industries where maintaining material integrity is of utmost importance. The current study presents a novel application of the Hungarian method, a combinatorial optimization technique, to determine the optimal FSW parameters for AA7075 and AA6082 alloys. The weldments were produced by applying different feed rates (40, 50 and 60 mm/min) and rotational speeds (1000, 1100 and 1200 rpm) in accordance with a L9 orthogonal array. The optimal combination was, a feed rate of 40 mm/min and a rotational speed of 1200 rpm, yielding an ultimate tensile strength of 162.26 MPa, a percentage elongation of 2.56 and an impact energy of 2.5 J/mm². The microstructural investigation showed substantial improvement in the grain refinement of the weld nugget, which significantly contributed to improved mechanical properties. However, under optimal welding conditions, the weld nugget exhibited a significant negative corrosion potential compared to the base metals, indicating a higher susceptibility to corrosion. These results show that the Hungarian method provides a systematic approach to optimizing FSW parameters, but it might be necessary to adapt post-weld treatment to lower propensity to corrode. This study illustrates not only the application of the Hungarian method in the optimization of operating parameters of FSW but also establishes a base for further studies dealing with combinatorial optimization problems in welding and other manufacturing processes.

Optimization of process parameters in fabricating AA6082/Nip surface composite using friction stir processing technique

Abstract In this present study, an attempt was made to improve the Ultimate Tensile Strength (UTS) and Microhardness (MH) of friction stir-processed AA 6082 with Nip surface composites without affecting the ductility of the Base Metal (BM). Nip micron particle with an average size of 149 μm (99.99 purity) was utilized as reinforcement and AA6082 as a matrix for fabricating the surface composites. Process parameters namely rotational speed, transverse speed, and volume fraction with three levels considered as input parameters for this study. Moreover, ultimate tensile strength, microhardness, and wear rate were determined as process output. For this study, experiments were conducted as per Taguchi’s L9 orthogonal array (OA) by repeating each trial three times and the average values were used for further analysis. ANOVA was performed to ensure the influential process parameter and the results exhibited that the volume fraction of Nip exhibited the most influential parameter among the three process parameters. Additionally, Grey relational analysis (GRA) was used to grade the rank of the experimental samples using the Grey Relation Coefficient (GRC). Based on this method, the optimal process parameters (Rotational Speed = 1250 rpm, Transverse Speed = 40 mm min−1, Volume Fraction = 18%) were chosen and the optimal sample (Rank 1) attained a UTS of 247 MPa and MH of 100 HV. The results revealed that the fabricated composite (AA6082/Nip) demonstrated an improvement in UTS (26.02%), MH (56.25%), and wear rate (57.38%) as compared to BM (AA6082). Eventually, the surfaces of the optimized samples were also analyzed by x-ray diffraction (XRD), energy dispersive x-ray analysis (EDAX), and field emission-scanning electron microscopy (FE-SEM) methods to confirm the composition of surface composite and the uniform distribution of particles.