Search

Purpose: This paper aims to accomplish friction stir welding (FSW) of Al–Li alloy AA8090 to determine optimal settings of the process parameters for higher tensile strength and higher micro-hardness (MH) to achieve the objective of adequate butt-joint strength. Design/methodology/approach: An empirical relation is implemented to govern the utmost influence parameters, i.e. tool rotation speed (TRS), tool transverse speed (TTS) and dwell time (DT). Taguchi grey relational analysis (GRA) was applied for multi-response optimization of response parameters. The grey relational grades (GRs) have been calculated for both the responses MH and ultimate tensile strength to get optimal parametric settings. The variance test has been performed to check the adequacy of the model. Findings: The Taguchi L9 orthogonal array design was used in establishing the relation between input parameter and output parameter (tensile and MH). TTS and DT have been predicted to be the two most important parameters that influence the extreme quality features of joints by using friction stir welding. Scanning electron microscopy fractography shows the ductile failure of the welded joints. Originality/value: The experimental trials provided the followings results, maximum ultimate tensile strength (UTS) of 219 MPa and MH 107.1 HV under 1,400 rpm of TRS, 40 mm/min of TTS and 8 s of DT founded the optimum value through GRA. [ABSTRACT FROM AUTHOR]

The current study aims to investigate the effects of process parameters on mechanical and microstructural characteristics of Al 6061-SiC composite fabricated via squeeze casting. Seventeen experiments in total have been conducted according to Box-Behnken experimental design which contained three process parameters (squeeze pressure, melt temperature, and SiC wt.%) while recording the responses including ultimate tensile strength, hardness, and percentage elongation. ANOVA (analysis of variance) was employed to evaluate the significance and prediction capability of mathematical models developed through regression analysis. The results indicate that squeeze pressure, melt temperature, and SiC wt.% significantly affect the responses whereas ductility is drastically reduced at higher concentrations of SiC reinforcement. SEM micrographs of failed test specimen have been found to be indicative of ductile fracture at higher levels of squeeze pressure and melt temperature. The multi-objective optimization problem has been transformed to an equivalent single-objective problem using grey relation analysis. The desirability analysis revealed optimum setting of process parameters which was confirmed to have improved the ultimate tensile strength by 1.61%, hardness by 1.56%, and percentage elongation by 11.11% as compared to the initial setting. [ABSTRACT FROM AUTHOR]

This paper is aimed to study in detail about dissimilar welding of aluminium alloy (AA 1100) with mild steel (MS) of thicknesses 3.0mm and 2.0mm respectively. This paper also gives emphasis on the multi-objective optimization by using grey relational analysis (GRA) for samples welded with gas tungsten arc welding (GTAW). The welding input parameters are crucial in obtaining the desired weld quality. The experiments have been performed according to the L-8 orthogonal array. The input parameters chosen are the pulsed DC parameters such as pulsed current, base current, pulse on time percentage and frequency. The weld quality determining parameters are the ultimate tensile strength and Rockwell hardness. Grey relational analysis is used to obtain the optimum input values for the optimum weld quality. [ABSTRACT FROM AUTHOR]

In this research, the dissimilar metals of AA6082 and AA7075 were joined using friction stir welding process with H13 steel as tool material. The parameters such as tool profile, rotational and traverse speeds were selected at three different levels. Taguchi L-9 array was selected to design the experiments. The response factors namely, ultimate tensile strength, % of elongation, hardness and impact strength were considered for optimising FSW parameters. The mechanical properties were evaluated by conducting tension test, hardness test and impact test according to ASTM standards. Taguchi Grey Relational Analysis was used to find the rank of each experiment. From GRA, an optimum parameters were observed at 2nd experimentation i.e. tool profile as circular geometry, tool speed at 900 rpm and feed rate at 40 mm/min. Further, analysis of variance was performed to determine the percentage of contribution of the welding parameters on the responses viz., tensile strength, % of elongation, hardness and impact strength. From the ANOVA grey relational analysis, order of effecting parameters was tool profile (33%) followed by feed rate (32%) and tool speed (26%) on output factors. [ABSTRACT FROM AUTHOR]

The selection of welding process parameters is a tedious operation that demands the process evaluation. Multi criteria decision-making strategies for assessing friction stir welding (FSW) process parameters are scanty. Therefore, a comparative study between five different multi-criteria decision-making methods was applied within friction stir welding process to show the deviations in the ranking of the alternatives. The goal is to find the welding parameters (including rotation speed, shoulder diameter, and travel speed) that result in the highest performance scores or rankings for the considered responses, such as ultimate tensile strength, hardness, and surface roughness. In the following, different decision-making strategies (including TOPSIS, GRA, hybrid GRA-TOPSIS, CoCoSo, and MACROS) are applied to calculate the weight of all different decision-making using entropy. The proposed methods in this study are validated by representing the accurate decision maker's preferences and consideration of uncertainty. The decision-makers choose GRA-TOPSIS and TOPSIS as the best approach with higher efficiency. GRA was determined to be more time-consuming and to have the most variety of outcomes, whereas CoCoSo and MACROS were unable to produce a definite best result. The study is highly promising for researchers and machining specialists to produce quality friction stir welds. [ABSTRACT FROM AUTHOR]

Studies dealing with process improvement of aluminum alloys and their grain structure refinement are the current area of interest in casting companies and foundries, the aim being to enhance the properties of the base metal. In this study, the microstructural and mechanical properties of commercial Al-Si9.8-Cu3.4 alloy die castings influenced by different additions of Al-3.5FeNb-1.5C master alloy (viz. 0 wt.%, 0.1 wt.%, and 1.0 wt.%) as a new grain refiner and Al-6Ni master alloy (viz. 0 wt.%, 0.5 wt.%, and 5.0 wt.%) as an alloying element have been investigated. A multi-criteria decision-making approach for the improvement of the die casting process was performed using grey relational analysis (GRA) and TOPSIS analytical techniques. It was observed that the primary aluminum α-grains were significantly refined, particularly at the lower addition level 0.1 wt.% of Al-3.5FeNb-1.5C, and conversely, poor grain refining efficiency was observed at a higher addition level 1.0 wt.% of Al-3.5FeNb-1.5C. Due to the refinement by Al-3.5FeNb-1.5C grain refiner and the effect of Ni alloying element additions, the ultimate tensile strength (UTS) and hardness (Brinell and micro) of the Al-Si9.8-Cu3.4 alloy are improved, particularly at 0.1 wt.% of Al-3.5FeNb-1.5C and 0.5 wt.% of Al-6Ni master alloys. Quantitatively, UTS, Brinell hardness, and microhardness values have been increased by 12.3%, 7.0%, and 20%, respectively. [ABSTRACT FROM AUTHOR]

This work aims to optimize the mechanical performance of ramie and kenaf fibers in epoxy composites developed using the hand layup technique. Fiber reinforcement at 0–10 wt% and benzoyl chloride treatment at 0–5 wt% were incorporated with this composites. Taguchi‐based grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods were used to determine the optimized conditions for overall mechanical properties of the developed composites. Optimization techniques concluded that 10 wt% ramie (R)/10 wt% kenaf (K) with 5 wt% benzoyl chloride treatment (T) based epoxy composites observed good mechanical properties with ultimate tensile strength of 37.39 MPa, ultimate flexural strength of 63.53 MPa, and impact strength of 70.36 J/m due to hybridization and the reduction in hydrophilic nature by the surface treatment process. The optimized GRA and TOPSIS combination with 10 wt% R/10 wt% K/5 wt% of T observed reduced water absorption nature with a contact angle of 64.72°. [ABSTRACT FROM AUTHOR]

The study predicts friction stir process (FSP) parameters using an artificial neural network (ANN) model. A design of experiment (DoE) approach is used to conduct experiments on FSP and to evaluate the best operating parameters of FSP. ANN uses 30 neurons, 1 hidden layer, and an input and output layer in the Matlab® environment. ANN predicts the output parameters with R values of 0.999, 0.995, and 0.992 for training, validation, and test datasets, respectively, while the overall R-value is 0.997. GRA is used to optimize and rank the parameters of the processes and revealed that the rotational tool speed should be 1180 rpm, traverse feed rate 38 mm/min, and tool tilt angle 1° for best results. The optimized values obtained are 380 MPa, 3.8 μm, 138 HV, and 14% for tensile strength, grain size, microhardness, and elongation, respectively. According to the analysis of variance (ANOVA) and grey relational analysis, the order of influencing parameters on output factors was rotational speed (80%), followed by transverse feed (19%) and tool tilt angle (1%). An ANN is further used to predict using the two most significant parameters--rotational speed and traverse feed. The modified ANN has nearly the same R values as the original ANN. Thus modified ANN may be used for prediction. [ABSTRACT FROM AUTHOR]

Friction stir welding (FSW) is gaining traction as a preferred technique due to its potential to reduce heat input and enhance the mechanical properties of welded joints. However, the path to commercializing FSW for flange joints is not without challenges. Two primary obstacles are the complexity of the welding path and the intricate design requirements for the fixtures. These factors contribute to the difficulty in determining the ideal weld settings and process parameters, which are critical for achieving optimal results. The current study addresses these challenges by applying FSW to flange joints using custom-engineered fixtures. These fixtures are meticulously designed to hold the pipes and plates securely during the welding process. The focus of the research is on optimizing the multi-performance characteristics of FSW for Al 6063 flange joints through the hybrid Grey-based Taguchi method. The integrity of the weld joint is assessed by examining various mechanical properties within the weld zone, including rotation speed, travel speed, tool profile, and shoulder diameter. The study identifies the optimal parameter settings for the FSW process: a rotation speed of 3000 rpm, a travel speed of 3 mm/min2, a shoulder diameter of 20 mm, and a conical tool profile. Under these ideal conditions, the welded material exhibited a tensile strength of 170.169 MPa, a hardness of 63.7709 HV, and a corrosion rate of 0.022 mm/year. These findings underscore the effectiveness of the optimized FSW process in producing robust and durable flange joints. [ABSTRACT FROM AUTHOR]

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO2/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO2/Gr composites were made from stir casting with 6-weight percent ZrO2 as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L27 OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (Kw) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO2 with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (Toff) of 40 µs, a pulse on time (Ton) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response. [ABSTRACT FROM AUTHOR]

This experimental work compared the Taguchi design along with Grey relational analysis and Box–Behnken design when turning of Inconel 718 aerospace alloy. Three input parameters, i.e., the cutting speed, feed rate, and depth of cut with three levels each, were employed to compare these approaches. In this study, the BBD with 15 runs and 3 center points and Taguchi OA-L9 are used. Initially, designs are evaluated based on their fraction of design space. Then, Mono-objective and Multi-objective optimization was conducted in three ways: firstly, by using S/N ratio-based Taguchi method for Mono-objective optimization; secondly, by using Taguchi design assisted by GRA for Multi-objective optimization; and thirdly, by using Desirability function based-BBD for Multi-objective optimization. Finally, comparison of tool wear tests is achieved through optimal solutions. From the results of Taguchi analysis for Mono-objective optimization, the maximal prediction error attained 38.41% for cutting force (Fy). Relating to the Grey–Taguchi approach, the error percentage decreases to 23.86% against the Taguchi technique and reflects a fitness amelioration of 61.0% when predicting (Fy). The maximal prediction error that exposes the accuracy of the Desirability approach can reach 20.22%, which is closer to the error value obtained with Grey–Taguchi approach. Tool wear tests for machinability assessment show that the cutting speed of 168 m/min involved from Desirability optimization process is more suitable for machining of Inconel 718 than that involved from Grey–Taguchi technique (220 m/min). Therefore, this approach can offer a new idea when attempting to solve Multi-response optimization problem. [ABSTRACT FROM AUTHOR]

Despite having poor cooling property, minimum quantity lubrication (MQL) is very commonly utilised in machining processes because of its superb lubrication, cleanliness, fewer costs and ease of handling. However, the optimum process parameters and the cutting fluid selection are very important for efficient machining. Moreover, an easy technique for optimisation is required so that the technicians can easily find their optimum parameter combinations for any manufacturing process. Considering multiple objectives synchronously for selecting optimum conditions helps to enhance the overall machinability. In this work, optimisation of cooling/lubrication environment, speed and feed were accomplished for minimum cutting temperature, roughness, cutting force along with maximum MRR and chip thickness ratio in turning 42CrMo4 alloy steel. Three powerful multi-variant hybrid techniques, such as Taguchi-based PCA-GRA, PCA-MOORA and DEAR, were implemented for multi-response optimisation, which provided identical results. The optimal process parameters were: MQL with cutting oil with the speed of 352 m/min and feed of 0.10 mm/rev. But among these methods, compared to the complex PCA-GRA, the DEAR is the computationally simplest because it did not require weight calculation before optimisation and then PCA-MOORA. However, the limitation of the DEAR method is that it can work for the problem having conflicting objectives. [ABSTRACT FROM AUTHOR]

Pure aluminium poses inferior properties that limit its use in load-bearing applications. Reinforcing multiwall carbon nano-tube (solid lubricant) and graphene to aluminium matrix offers better (antifriction, hardness, and wear resistance) properties in composites for such applications. A stir casting processing route is employed to prepare the hybrid composite (aluminium-multiwall carbon nanotube-graphene Al-MWCNT-GR). The Taguchi L16 experimental matrix representing four variables (percent reinforcement of graphene, die temperature, melt temperature, and stir speed) operating at four levels were studied to analyze and obtain higher hardness and low wear rate in hybrid composites. Percent reinforcement of graphene showed maximum impact, and die temperature resulted with the least contribution towards both the responses. Criteria importance through intercriteria correlation (CRITIC) method is applied to determine the weight fractions (importance) for hardness and wear rate equal to 0.4752 and 0.5482, respectively. Grey relational analysis (GRA) and multi-objective optimization by the ratio analysis (MOORA) method converts multiple objective functions into a single objective function with weight fractions assigned to each output. Taguchi-CRITIC-MOORA outperformed the Taguchi-CRITIC-GRA method, which could result in 31.77% increase in hardness and a 36.33% decrease in wear rate compared to initial conditions. The optimal conditions ensure a dense microstructure with minimal pores, result in enhanced properties compared to that obtained for initial and average stir casting conditions. The worn-out surface results in a few thin and slender grooves between tracks with less crack propagation, ensuring self-lubrication in composites fabricated with the optimized condition. The better properties resulted in the hybrid composites correspond to optimized stir casting conditions and can be implemented in industries for large-scale applications. [ABSTRACT FROM AUTHOR]

Lightweight design is one of the important ways to reduce automobile fuel consumption and exhaust emissions. At the same time, the fatigue life of automobile parts also greatly affects vehicle safety. This paper proposes a multi-objective reliability optimization method by integrating Monte Carlo simulation (MCS) with the NSGA-II algorithm coupled with entropy weighted grey relational analysis (GRA) for lightweight design of the lower control arm of automobile Macpherson suspension. The dynamic load histories of the control arm were extracted through dynamic simulations of a rigid-flexible coupling vehicle model on virtual proving ground. Then, the nominal stress method was used to predict its fatigue life. Six design variables were defined to describe the geometric dimension of the control arm, while mass and fatigue life were taken as optimization objectives. The multi-objective optimization design of the control arm was carried out based on the Kriging surrogate model and NSGA-II algorithm. Aiming at the uncertainty of design variables, the reliability constraint was added to the multi-objective optimization to improve the reliability of the fatigue life of the control arm. The optimal design of the control arm was determined from Pareto solutions by entropy weighted grey relational analysis (GRA). The optimization results show that the mass of the control arm was reduced by 4.1% and the fatigue life was increased by 215.8% while its reliability increased by 7.8%. The proposed multi-objective reliability optimization method proved to be feasible and effective for lightweight design of a suspension control arm. [ABSTRACT FROM AUTHOR]

Wire Electrical Discharge Machining (WEDM) is a competent method employed for machining intricate shapes in electrically conductive harder materials. Metal Matrix Composites (MMCs) possesses improved properties and considered as an alternate material for various engineering applications. An enduring issue with MMCs is that they are problematic for machining, because of abrasive nature of hard reinforcing phase. This current exploration is dealing the WEDM machinability analysis of LM6/SiC/Dunite Hybrid Metal Matrix Composites (HMMC) fabricated by two step stir casting process and to develop an artificial intelligence decision making model for WEDM the process parameters. The influence of input machining process variables namely Pulse ON, Pulse OFF, Flushing Pressure, Wire Feed and Servo Voltage against the desired output like Material Removal Rate (MRR), Surface finish, overcut, circularity error and perpendicularity error are investigated. Grey Relational Analysis (GRA) method is employed and grey relational coefficient values are given as input values for evolving the Adaptive Neuro Fuzzy Inference System (ANFIS) to predict the desired performance characteristic. A comparative study has been accomplished for validating the outcomes attained from evolved models and experimentation outcomes. The performance analysis of developed model proves that the developed model and this method are efficacious for predicting the desired performance measures. [ABSTRACT FROM AUTHOR]

Sustainable machining necessitates energy-efficient processes, longer tool lifespan, and greater surface integrity of the products in modern manufacturing. However, when considering Ti6Al4V alloy, these objectives turn out to be difficult to achieve as titanium alloys pose serious machinability challenges, especially at elevated temperatures. In this research, we investigate the optimal machining parameters required for turning of Ti6Al4V alloy. Turning experiments were performed to optimize four response parameters, i.e., specific cutting energy (SCE), wear rate (R), surface roughness (Ra), and material removal rate (MRR) with uncoated H13 carbide inserts in the dry cutting environment. Grey relational analysis (GRA) combined with the analytic hierarchy process (AHP) was performed to develop a multi-objective function. Response surface optimization was used to optimize the developed multi-objective function and determine the optimal cutting condition. As per the ANOVA, the interaction of feed rate and cutting speed (f × V) was found to be the most significant factor influencing the grey relational grade (GRG) of the multi-objective function. The optimized machining conditions increased the MRR and tool life by 34% and 7%, whereas, reducing the specific cutting energy and surface roughness by 6% and 2% respectively. Using Taguchi-based GRA by analytic hierarchy process (AHP) weights method, the benefits of high-speed machining Ti6Al4V through multi-response optimization were achieved. [ABSTRACT FROM AUTHOR]

The use of aluminum alloys, nowadays, is swiftly growing from the prerequisite of producing higher strength to weight ratio. Lightweight components are crucial interest in most manufacturing sectors, especially in transportation, aviation, maritime, automotive, and others. Traditional available joining methods have an adverse effect on joining these lightweight engineering materials, increasing needs for new environmentally friendly joining methods. Hence, friction stir welding (FSW) is introduced. Friction stir welding is a relatively new welding process that can produce high-quality weld joints with a lightweight and low joining cost with no waste. This paper endeavors to deals with optimizing process parameters for quality criteria on tensile and hardness strengths. Samples were taken from a 5 mm 6061-T6 aluminum alloy sheet with butt joint configuration. Controlled process parameters tool profile, rotational speed and transverse speed were utilized. The process parameters are optimized making use of the combination of Grey relation analysis method and L9 orthogonal array. Mechanical properties of the weld joints are examined through tensile, hardness, and liquid penetrant tests at room temperature. From this research, rotational speed and traverse speed become significant parameters at a 99% confidence interval, and the joint efficiency reached 91.3%. [ABSTRACT FROM AUTHOR]

Welding distortion is a critical issue as it leads to severe deterioration of structural integrity of welded work piece and dimensional precision. This study aims at studying the effects of shielded metal arc welding (SMAW) parameters on the evolution of mechanical properties, including tensile strength, impact toughness, and hardness, along with angular distortion on a welded joint from SA 516 grade 70. Such parameters are analyzed and optimized by employing the Taguchi method and Grey relational analysis. SA 516 grade 70 is commercially used for fabrication of storage tanks, boilers and pressure vessels. SMAW is investigated with three levels of root gap, groove angle, electrode diameter, and pre-heat temperature, which were varied on a butt joint in flat (1 G) position to determine their effects on response variables at room temperature. Nine experiments were designed using a Taguchi L9 orthogonal array, welded according to American Society of Mechanical Engineers (ASME) section IX, and samples were prepared and tested as per ASTM A 370. The Taguchi method and Grey relational analysis were employed to observe the most significant parameters and optimal levels that synergically yield improved responses. Results are validated by conducting confirmatory experiments that show good agreement with optimum results. [ABSTRACT FROM AUTHOR]