Optimization of aluminium sheet hot stamping process using a multi-objective stochastic approach

Corn was frozen at harvest time in high-latitude areas, when corn kernel is wetter and more easily broken. When frozen corn was threshed and separated by the longitudinal axial threshing cylinder of a combine harvester, it caused a significantly high kernel damage rate and loss rate. The process parameters of threshing cylinder were optimized using RSM (response surface method) and NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). The drum speed (Ds), feed rate (Fr) and concave clearance (Cc) were determined as the optimized process parameters. The loss rate (Lr) and damage rate (Dr) were indicators of operational performance. The RSM was used to establish a mathematical model between process parameters and indicators. With an elite strategy, NSGA-II was used for multi-objective optimization to obtain the optimal operational performance of the threshing cylinder. Overall, when the drum speed was selected as 384.1 rpm, the feed rate as 8.6 kg/s and the concave clearance as 40.5 mm, according to the requirement of corn harvest, the best operational performance of the longitudinal axial threshing cylinder on frozen corn was obtained. The Lr was 1.98% and the Dr was 3.49%. This result indicated that the applicability of the optimal process parameters and the optimization method of combining NSGA-II and RSM was effective for determining the optimal process parameters. This will provide an optimization method for synchronously reducing the loss rate and damage rate of grain harvesters.

Optimizing process parameters for hot forging of Ti-6242 alloy: A machine learning and FEM simulation approach

Double‐vacuum‐bag (DVB) process, as an effective out‐of‐autoclave (OoA) technology, can manufacture composite materials with low void content and high mechanical properties. Therefore, this paper aimed to achieve low void content, the effects of pressure difference between inner and outer bags, dwelling temperature, and dwelling time on the void of composite laminates were studied based on orthogonal experimental method. The void content and morphology of laminates were statistically analyzed, by observing the microscopic images of the samples on cross‐section. The results show that the pressure difference between the inner and outer bags has a significant impact on the void content and morphology, while the dwelling temperature and dwelling time have little effect. In addition, with the variance analysis and extreme difference analysis, the optimal process parameters were determined as follows: pressure difference between inner and outer bags was 0 MPa, dwelling temperature was 110°C, and dwelling time was 15 min. The void content of composite laminates manufactured under these parameters is 0.07%, less than 1% requirement for aerospace components, and interlaminar shear strength (ILSS) is 110 MPa, which is 54.93% higher than the single‐vacuum‐bag (SVB) process. Generally, the void content and ILSS reached the level of hot press process with 0.6 MPa. Highlights Influence of different DVB process parameters on void were studied. Void content manufactured with the optimal DVB process parameters was less than 1%. ILSS of laminate with the optimal DVB process parameters was equal as hot press process.

Optimization of processing parameters of laser skin welding in vitro combining the response surface methodology with NSGA- II

Integration of RSM with Grey based Taguchi Method for optimization of pulsed TIG welding process parameters

The process parameter selection in any machining process is one of the most challenging criteria for effective machining. Selection of an optimal parametric combination always results in efficient machining. In the current work, a fuzzy TOPSIS method for selection of optimal laser beam micro-marking process parameters, such as current, pulse frequency, and scanning speed, during laser beam marking on gallium nitride is adopted. Response surface methodology (central composite design) is adopted for the experimental design. The mark width, mark depth, and mark intensity are considered as the process responses. The mark width and mark depth are measured with the help of a precision optical microscope. Microscopic images are then treated using image processing software to calculate the mark intensity. A multi-criteria decision-making model is developed considering the effect of process parameters on process response for selection of optimal process parameter in the laser beam micro-marking process. The triangular fuzzy number is used to calculate the weight of each performance criteria, and the fuzzy TOPSIS hybrid approach is used for selection of optimal parametric combination. The results indicate that a small pulse frequency and high current and scanning speed lead to increase in mark intensity.

Experimental analysis and low-damage machining strategy for composite ultrasonic vibration-assisted grinding of silicon carbide based on DA-MLP-NSGA-II algorithm

Titanium alloys such as Ti–6Al–4V offer biocompatibility, corrosion resistance, and superb mechanical properties and are considered the most important metallic biomaterial for medical applications. However, mechanical machining of titanium alloys is still highly difficult and even more challenging for micro-scale machining such as micro-milling. Severe burr formation and rapid tool wear create significant problems such as poor surface roughness. In order to improve the performance of micro-milling Ti–6Al–4V alloy, this study proposes an integrated method in selecting the toolpath and optimum process parameters which can meet micro-machining requirements and constraints. Controlled micro-end-milling experiments for measuring burr formation and surface roughness, finite element simulations for predicting forces and tool wear, and mathematical modeling and optimization techniques have been utilized for determining optimum toolpath strategy and process parameters. Based on the micro-end-milling tests on a circular thin rib feature, process optimization results are validated and indicate a significant improvement in process performances in terms of minimizing burr formation, maximizing tool life, and surface quality.

This experiment was centred on the concept of using pectin gel to manufacture fairy tofu in order to determine the ideal parameters for the creation of natural fairy tofu. Based on the single-factor test, The Box-Behnken central combination design approach was employed to investigate the optimal production process of fairy tofu. According to the findings, there were substantial changes (P<0.05) in the qualitative attributes of tofu at varied material-to-liquid ratios, drying temperatures (the leaves of Premna microphylla Turcz) and grinding temperatures during the production process. The optimal process parameters were: material-to-liquid ratio of 1:60 (g:g), drying temperature of 20 °C and a grinding temperature of 90 °C. The yield of fairy tofu produced under this process parameter was 46.02 g/g, which was 55.33% higher than the yield of fairy tofu produced by the unoptimized process. It indicated that the optimized process conditions for the production of pure natural fairy tofu are feasible and can produce a high-yield and high-quality of fairy tofu. This study provides a theoretical basis for the reuse of the leaves of Premna microphylla Turcz. and lays the foundation for the large-scale production of fairy tofu.

Antioxidant peptides can inhibit lipid peroxidation and scavenging free radicals, maintain the balance of free radicals, and against a variety of diseases. Response surface methodology was used to optimize process conditions for producing antioxidative peptides from goat’s milk casein hydrolysate with Alcalase. The results suggested that the optimal process parameters were: temperature at 62.5°C, pH 8.9, E/S ration at 2.5%, substrate concentration at 4.4% and hydrolysis time was 173min). Metal-chelating effect, superoxide anion radical scavenging activity and 1, 1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging activity were shown to be 87.21±0.88%, 49.18±1.42% and 69.07±1.26% respectively under the optimal condition. The actual and predicated value were closely which indicated the optimized data fit well to model and the optimized parameters are reliable.

In this study, a multi-objective optimization technique involving response surface methodology (RSM)-based desirability function approach is used in optimizing the process parameters for friction stir welding of AA6063-T6 pipes. Two process parameters, namely, tool rotational speed and weld speed, are optimized for achieving a weld joint having superior tensile properties, viz., maximum yield, and ultimate tensile strength and maximum % of elongation. A regression model, with a 95% confidence level, is developed using response surface methodology to predict the tensile strength of the weld joint. ANOVA technique is used to determine the adequacy of the developed model and identify the significant terms. The desirability function is used to analyze the responses and predict the optimal process parameters. It is found that tool rotational speed and weld speed have equal influence over the tensile strength of the pipe weld. Tool rotational speed 1986 rpm and weld speed 0.65 rpm have yielded a maximum ultimate tensile strength of 167 MPa, yield strength of 145 MPa, and % elongation of 8.3, under considered operating conditions. Microstructural attributes for superior weld properties are also discussed.

This work aimed to extract fixed oil from moringa seeds by optimizing the oil extraction process parameters with the aid of response surface methodology (RSM). The effects of three independent oil extraction process factors particle sizes (0.3–0.7 mm), temperature (50–70 °C) and time (6–8 h) for oil extraction from moringa seeds were studied. The proximate analysis of moringa seeds: ash content, acid value, ester value and saponification value were 5 ± 0.46, 2 ± 0.77, 257 ± 73 and, 260 ± 0.50wt.%, respectively. A quadratic model was used to correlate the interaction effects of the independent variables for maximum oil extraction at the optimum process parameters by employing central composite design (CCD) with RSM. The work indicates that the interaction of temperature and particle sizes is the most significant parameters among the model terms, followed by the interaction of temperature and extraction time effect on oil yield and finally, interaction of particle sizes and extraction time had no significant effect on oil yield. The studied results reported a better oil yield: 43.18 ± 0.52% at extraction temperature of 59.79 °C, particle size of 0.41 mm and extraction time of 6.54 h with supported a maximum desirability of 1. The oil obtained was analysed for various parameters: acidity value 2.2 ± 0.05, iodine value 63.4 ± 0.08, refractive index 1.52 ± 0.01 and density 0.90 ± 0.01. This study concludes that oil obtained from moringa seeds could be utilized as a source of edible oil for human consumption.

The present work focuses on modeling and optimization during Nd:YAG laser microgrooving of Ti6Al4V titanium alloy material with an objective to find the optimum process parameters settings for the groove upper width as well as depth and heat-affected zone. The experiments are performed as per Box–Behnken design of experiments (BBDOEs) with four process parameters (diode current, pulse frequency, scanning speed, and number of passes) for parametric optimization in order to control the technological response characteristics of the precision microgrooves on Ti6Al4V titanium alloy. Analysis of variance (ANOVA), response surface methodology (RSM) and particle swarm optimization (PSO) are subsequently proposed for predictive modeling and process optimization. The methodology described here is expected to be highly beneficial for manufacturing industries.

When laser cladding is used to repair parts, the interaction of parameters has a significant influence on equipment performance. In order to explore the process parameters and quality of Ni60PTA coating, the statistical relationship between the process parameters (laser power, scanning speed, and powder feeding rate) and the responses (dilution ratio, ratio of layer width to height, and contact angle) was established by experiments using the response surface method (RSM) and variance analysis. The results show that the laser power is the dominant factor affecting the dilution ratio. However, the scanning speed has the greatest influence on the ratio of layer width to height and contact angle. These experimental results show that the proposed model can predict the actual data. In addition, the microstructure and microhardness of the samples prepared with the optimum process parameters were characterized. The results show that the quality of the cladding layer is good without cracks, deformation, and pores. The microstructure of the cladding zone is mainly composed of γ (Ni), FeNi3, M (M = Fe, Ni, Cr)23C6, M7C3, and CrB. The average microhardness of the coating is about 620 HV0.2, which is about 3.1 times that of 45 steel substrate.

This study experimented on microwave-vacuum (MWV) drying of kiwifruit (Actinidia deliciosa) slices as a way to improve drying productivity and the quality of dried fruit. The effects of microwave power density, sample thickness and vacuum degree on the drying characteristics of kiwifruit slices were studied. The results showed that these three factors had significant effects on the vitamin C and chlorophyll contents and on the rehydration capacity of dried kiwifruit slices, as well as the total drying time. The processing parameters of MWV drying of kiwifruit slices were optimized by using Box–Behnken design with a quadratic regression model built by response surface methodology. The optimum processing parameters were experimentally determined as microwave power density at 7.7 W, sample thickness of 6.0 mm and MWV drying for 11.5 min at a vacuum degree of −90 kPa. High-quality dried kiwifruit slices can be created under these conditions using this drying process. Practical Applications Kiwifruit (Actinidia deliciosa) has become a popular fruit because of its bright green flesh, high level of vitamin C and because it contains a wide variety of phytonutrients, including carotenoids, lutein, phenolics, flavonoids and chlorophyll. It needs some form of preservation to extend its shelf life. Microwave-vacuum (MWV) drying is a novel alternative that combines the advantages of both microwave drying and vacuum drying. The objectives of this study were to investigate the effect of microwave power density, sample thickness and vacuum degree on the MWV drying characteristics and quality of MWV-dried kiwifruit slices, and to evaluate a suitable drying model for describing the drying process. In addition, the process parameters of MWV drying were optimized by response surface methodology. This present study provides the theoretical basis for industrial-scale production.