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The goal of this study is to determine the values of the process parameters that should be used during the machining of ceramic tile using the abrasive water jet (AWJ) process in order to achieve the lowest possible values for surface roughness and kerf taper angle.

In the present work, ceramic tile is processed by the AWJ process and experimental data were recorded using the RSM approach based Box–Behnken design matrix. The input process factors were water jet pressure, jet traverse speed, abrasive flow rate and standoff distance, to determine the surface roughness and kerf taper angle. ANOVA was used to check the adequacy of model and significance of process parameters. Further, the elite opposition-based learning grasshopper optimization (EOBL-GOA) algorithm was implemented to identify the simultaneous optimization of multiple responses of surface roughness and kerf taper angle in AWJ.

The suggested EOBL-GOA algorithm is suitable for AWJ of ceramic tile, as evidenced by the error rate of ±2 percent between experimental and predicted solutions. The surfaces were evaluated with an SEM to assess the quality of the surface generated with the optimal settings. As compared with initial setting of the SEM image, it was noticed that the bottom cut surface was nearly smooth, with less cracks, striations and pits in the improved optimal results of the SEM image. The results of the analysis can be used to control machining parameters and increase the accuracy of AWJed components.

The findings of this study present an innovative method for assessing the characteristics of the nontraditional machining processes that are most suited for use in industrial and commercial applications.

In this paper, the performance of a specific gas station (Parvin) has been studied and investigated. The purpose of this research is to design a second-order regression model based on simulated data to optimize the queuing system in line with the fuel sales and costs. Thus, the influential variables including the number of pumps and the number of pump operators need to be optimally determined.

The simulation was combined with design of experiments (DoE) techniques to achieve a predictable model for optimizing Gas Station performance considering both the sales rate and the queue length. First, the Gas Station was simulated with Arena software, and then by using DoE and response surface methodology (RSM), the gas station performance was optimized in terms of three objectives including costs. A face-centered central composite design (CCD) has been implemented to reach the optimal number of pumps and pump workers.

The results of the optimization model derived from the CCD indicate that the performance of the Gas Station system has been improved considerably. Moreover, after the detailed study of optimization and RSM outputs, it seems that the variations of both the pumps and the number of pump operators have significant impacts on the performance of the Gas Station including costs, sales rate and queue length.

In general, it has been proved that simulation-based RSM can be considered as a powerful and effective technique in both single and multi-objective experimental optimization. The present study has been able to help managers to make decisions and conduct the Gas Station in critical conditions in different hours of a day.

The purpose of this paper is to present a model to predict the micro-hardness of friction stir processed (FSPed) AZ31B magnesium alloy using response surface methodology (RSM). Another objective is to identify process parameters and through-thickness position which will give higher micro-hardness values. Moreover, the study aims at defining the factor that exhibits the most effect on the micro-hardness. Friction stir processing (FSP) machine can then be fed with the optimized parameters to achieve desirable properties.

An experimental setup was designed to conduct FSP. Several AZ31B magnesium samples were FSPed at different combinations of rotational and translational speeds. The micro-hardness of all the combinations of process parameters was measured at different through-thickness positions. This was followed by an investigation of the three factors on the resulting micro-hardness. RSM was then used to develop a model with three factors and three levels to predict the micro-hardness of FSPed AZ31 magnesium alloy within the covered range. The analyses of variance in addition to experimental verification were both used to validate the model. This was followed by an optimization of the response.

The model showed excellent capability of predicting the micro-hardness values as well as the optimum values of the three factors that would result in better micro-hardness. The model was able to capture the effects of rotational speed, translational speed, and through-thickness position. Results suggest that micro-hardness values were mostly sensitive to changes in tool rotational speed.

FSP is considered to be one of the advanced microstructural modification techniques which is capable of enhancing the mechanical properties of light-weight alloys. However, the lack of accurate models which are capable of predicting the resulted properties from process parameters hinders the widespread utilization of this technique. At the same time, RSM is considered as a vital branch of experimental design due to its ability to develop new processes and optimize their performance. Hence, the developed model is very beneficial and is meant to save time and experimental effort toward effective use of FSP to get the desired/optimum micro-hardness distribution.

Dissimilar joining of austenitic stainless steels and ferritic steels is a challenging task and has a wide range of applications due to its excellent mechanical and thermal characteristics. They are joined mostly by using conventional modes. In the current investigation, the study and optimization of hot wire TIG welding parameters was carried out.

These parameters will govern the desired characteristics of the joint. Solutions were found out through multi-response optimization by using response surface methodology and single response optimization using particle swarm optimization.

Optimized input welding parameters that were achieved are electrode current 180 amps, wire feed rate 1870 mm/min and hot wire current 98 amps and the optimized UTS is 665.45 MPa. The results from PSO were compared with RSM and the optimized input welding parameters for the electrode current, hot wire current and wire feed rate exhibited maximum ultimate tensile strength which were also confirmed from response and contour plots.

Sensitivity analysis was also performed to understand the effect of each individual parameters on the response. Microstructure features were evaluated for the joints and was found that the characteristics are within the desired criteria.

In this research, electro discharge machining (EDM) of Ti-5Al-2.5Sn titanium alloy is performed taking gap voltage, pulse on time, peak current and duty cycle as process parameters. The purpose of this paper is to find out the optimal process parameters setting for getting higher machining efficiency.

For experimental design, a face-centered central composite design (FCCCD)-based response surface methodology (RSM) is used. Multi-objective optimization like grey relational analysis (GRA) is adopted to achieve the higher machining efficiency by means of lower radial overcut (ROC), surface roughness (Ra), tool wear rate (TWR) and higher material removal rate (MRR). For the statistical study, analysis of variance (ANOVA) has been carried out.

The result shows that gap voltage, peak current and pulse on time are the most efficient parameters for the responses. An optimal parameter setting has been obtained for achieving higher machining efficiency. For validation of the study, confirmation experiment has been performed at optimal parameters setting.

Optimum parameter level for higher machining performance of Ti-5Al-2.5Sn Titanium alloy has been achieved machined by copper electrode during EDM operation.

This study aims to investigate the interaction of independent variables [Reynolds number (Re), thermal power and the number of ball grid array (BGA) packages] and the relation of the variables with the responses [Nusselt number ((Nu) ¯ ), deflection/FPCB’s length (d/L) and von Mises stress]. The airflow and thermal effects were considered for optimizing the Re of various numbers of BGA packages with thermal power attached on flexible printed circuit board (FPCB) for optimum cooling performance with least deflection and stress by using the response surface method (RSM).

Flow and thermal effects on FPCB with heat source generated in the BGA packages have been examined in the simulation. The interactive relationship between factors (i.e. Re, thermal power and number of BGA packages) and responses (i.e. deflection over FPCB length ratio, stress and average Nusselt number) were analysed using analysis of variance. RSM was used to optimize the Re for the different number of BGA packages attached to the FPCB.

It is important to understand the behaviour of FPCB when exposed to both flow and thermal effects simultaneously under the operating conditions. Maximum d/L and von Misses stress were significantly affected by all parametric factors whilst (Nu)¯ is significantly affected by Re and thermal power. Optimized Re for 1–3 BGA packages with maximum thermal power applied has been identified as 21,364, 23,858 and 29,367, respectively.

This analysis offers a better interpretation of the parameter control in FPCB with optimized Re for the use of force convection electronic cooling. Optimal Re could be used as a reference in the thermal management aspect in designing the BGA package.

This research presents the parameters’ effects on the reliability and heat transfer in FPCB design. It also presents a method to optimize Re for the different number of BGA packages attached to increase the reliability in FPCB’s design.

Mixed fruit nectars present a combination of different tastes and flavors with combined nutritional attributes. Therefore, the purpose of this paper is to develop and optimize the process variables for blended nectar based upon papaya (Carica papaya) and bottle gourd (Lagenaria siceraria).

The nectar based upon papaya and bottle gourd was prepared with varying levels of papaya/bottle gourd juice concentration (1.5:1‐ 4:1), sugar concentration (12‐21 per cent), citric acid concentration (0.30‐0.50 per cent) and optimized using response surface methodology. A central composite rotatable design (CCRD) with three levels for three independent variables was used for optimization studies. The responses measured were pH, TA, TSS, flavor and taste of the developed nectar. Responses were numerically optimized in combination with design expert software.

The models developed for all responses were significant without significant lack of fit. Papaya/bottle gourd juice concentration ratio, sugar concentration and citric acid level were optimized at 2.47:1, 20.95 and 0.30 per cent, respectively, in order to obtain a pH, titrable acidity and TSS of 3.99, 0.348 and 20.80, respectively, with hedonic scale sensory ratings of 7.43 and 7.18 for flavor and taste, respectively, of the nectar.

The commercial production of such nectar using these optimized conditions may add new dimension to the health beverage industry.

Development of such health‐promoting mixed fruit nectars will boost demand of healthy beverage foods in society.

The product can be developed successfully using these optimized conditions. Since both papaya and bottle gourd have beneficial nutritional and medicinal properties, the development of nectar using these fruits with high sensory acceptance can prove a boon for market promoting health foods.

Toner is a crucial dry colorant composite used in printing based on the electrophotographic process. The quality of printed images is greatly influenced by the toner production method and material formulation. Chemically in situ polymerization methods are currently preferred. This paper aims to optimize the characteristics of a composite produced through emulsion polymerization using common raw materials for electrophotographic toner production.

Emulsion polymerization provides the possibility to optimize the physical and color properties of the final products. Response surface methodology (RSM) was used to optimize variables affecting particle size (PS), PS distribution (PSD), glass transition temperature (T_g°C), color properties (ΔE) and monomer conversion. Box–Behnken experimental design with three levels of styrene and butyl acrylate monomer ratios, carbon black pigment and sodium dodecyl sulfate surfactant was used for RSM optimization. Additionally, thermogravimetric analysis and surface morphology of composite particles were examined.

The results indicated that colorants with small PS, narrow PSDs, spherical shape morphology, acceptable thermal and color properties and a high percentage of conversion could be easily prepared by optimization of material parameters in this method. The anticipated outcome of the present inquiry holds promise as a guiding beacon toward the realization of electrographic toner of superior quality and exceptional efficacy, a vital factor for streamlined mass production.

To the best of the authors’ knowledge, for the first time, material parameters were evaluated to determine their impact on the characteristics of emulsion polymerized toner composites.

To reduce energy consumption, the time needed of drying, and the loss of ß-carotene content, and ascorbic acid content, response surface methodology (RSM) was employed for optimization.

To reduce energy consumption, the time needed of drying, and the loss of ß-carotene content, and ascorbic acid content, response surface methodology (RSM) was employed for optimization.

The results show that the optimum solar-assisted heat pump drying (SAHPD) conditions for drying pumpkin slice were: drying temperature of 67.40 °C, loading density of 1.05 kg/m³, and material thickness of 4 mm. Under these conditions, slice of pumpkin were dried in 440.637 min, where the unit energy consumption, ascorbic acid content, and ß-carotene content were 16.737 kJ/g, 25.682 mg/ (100–g dried sample), and 10.202 mg/g, respectively. The structure of the samples dried using the optimized SAHPD method exhibited a more complete cell morphology than those dried using heat pump drying when examined using scanning electronic microscopy.

This suggests that the optimized SAHPD conditions used in this study are important for production and processing.

This paper aims to optimize the quantum of aonla pulp that could be mixed with guava pulp to make a nutritional rich fruit bar. The developed fruit bar will not only help in the improvement of processing value of both Guava and underused but highly nutritional Aonla but also serve the purpose of improvement in nutritional status of consumers.

Response surface methodology (RSM) using Box–Behnken design was used with the process variables as aonla and guava pulp ratio, PR (30:70, 40:60, 50:50); pectin concentration, PC (0, 0.15, 0.30%); and drying temperature, DT (50, 60, 70°C) for optimization of process conditions. The prepared mixed fruit leather was evaluated for physico-chemical, textural and sensory properties such as titratable acidity (TA), ascorbic acid content (AA), L value (lightness), cutting force (CF), taste and overall acceptability (OAA).

Second-order regression models fitted for TA, AA, L value (lightness), CF, taste and OAA were highly significant (P = 0.01) with the coefficient of determination (R² = 0.85). The TA and AA of mixed fruit bar increased whereas L value, CF, taste and OAA decreased with increasing level of aonla pulp in the blend formulation. The optimum process conditions for mixed aonla-guava bar with desirable characteristics were 40:60 (PR), 0.02% (PC) and 56°C (DT). The corresponding optimum values of TA, AA, L value, CF, taste and OAA were 1.00%, 164 mg/100 g, 50, 5066 g, 7.83 and 7.92, respectively. The design formulation and data analysis using RSM validated the optimum solution.

This paper demonstrates that optimum blending of aonla and guava pulp has improved the overall nutritional characteristics and acceptability of the final product. This will not only help in reducing the associated post-harvest losses but also encourage the cultivators/local processing industries by stabilizing the price during glut sea.