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This study aims to examine the impact of specific printing factors, such as layer height, line width and build orientation, on the overall quality of fused filament fabrication (FFF) 3D printed structures. The project also intends to use response surface methodology (RSM) to maximize ultimate tensile strength (UTS) while lowering surface roughness and printing time.

This study used an FFF printer to fabricate samples of polylactic acid (PLA), which were then subjected to assessments of tensile strength and surface roughness. A tensile test was conducted under standardized conditions according to the ASTM D638 standard test method using the AG-50 kN Shimadzu Autograph. The Mitutoyo Surftest SJ-210, which utilizes a needle-tipped inductive method, was used to determine surface roughness. RSM was used for optimization.

This work provides useful insights into how the printing parameters affect FFF 3D printed structures, which may be used to optimize the printing process and improve PLA-based 3D printed products' qualities. The determined optimal values for building orientation, layer height and line width were 0°, 0.1 mm and 0.6 mm, respectively. The total desirability value of 0.80 implies desirable outcomes, and good agreement between experimental and projected response values supports the suggested models.

Previous RSM studies for 3D printing parameter optimization focused on mechanical properties or surface aspects, however, few examined multiple responses and their interactions. This study emphasizes the relevance of FFF parameters like line width, which are often overlooked but can dramatically impact printing quality. Mechanical properties, surface quality and printing time are integrated to comprehend optimization holistically.

The need for materials with superior mechanical and physical properties has recently increased. Inconel 718, one of these superalloys, is frequently used in the aviation and space industry. However, during Inconel 718 superalloy machining, cutting tools and cutting fluid were excessively consumed. This study aims to investigate using an innovative and environmentally friendly cutting fluid in milling the Inconel 718 superalloy.

In this study, a Borax- (BX-)added cutting nanofluid was prepared and used for the first time as a coolant in the minimum quantity lubrication (MQL) system of Inconel 718’s face milling process. Response surface methodology (RSM) was used to determine the effect of the BX element on cutting performance. Face milling operations were carried out by adding BX elements at 1.5% and 3% at two different rates.

As the BX additive ratio in the cutting fluid used in the MQL system increased, the cutting force values decreased. The lowest cutting force value was measured in the tests with cutting fluid containing 1.5% BX. In addition, a smoother surface was obtained by adding 1.5% BX to the cutting fluid. Furthermore, cutting tool life increased by 20% compared to 0% by 3% BX nanofluid concentration.

The study is innovative regarding the material processed, the cutting fluid used and the method used for the aerospace industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0191/

This study aims to investigate the efficacy of Ag@GO/Na₂SiO₃ nanocomposite in eliminating As from aqueous solutions. Employing response surface methodology, the research systematically examines the adsorption process.

Various experimental parameters including sample pH, contact time, As concentration and adsorbent dosage are optimized to enhance the As removal process.

Under optimized conditions, the initial As concentration, contact time, pH and adsorbent dosage are determined to be 32 ppm, 50 mins, 6.5 and 0.4 grams, respectively. While the projected removal of As stands at 97.6% under these conditions, practical application achieves a 93% removal rate. Pareto analysis identifies the order of significance among factors as follows: adsorbent dosage > contact time > pH > As concentration.

This study highlights the potential Ag@GO/Na₂SiO₃ as a promising adsorbent for efficiently removing industrial As from aqueous solutions, and it is likely to have a good sufficiency in the filtration of water and wastewater treatment plans to remove some chemical pollution, including paints and heavy metals.

The simplicity of the nanocomposite preparation method without the need for advanced equipment and the cheapness of the raw materials and its potential ability to remove As are the prominent advantages of this research.

This study aims to develop eco-friendly corrosion inhibitors for aluminum in acidic media by evaluating the corrosion inhibition properties of corn leaf extract (CLE) using response surface methodology (RSM) and experiments.

The RSM was combined with experiments to evaluate the corrosion inhibition properties of CLE on aluminum in acid media.

The effectiveness of the inhibition increased with increasing inhibitor concentration and time but decreased with increasing temperature. The corrosion inhibition mechanism revealed the corrosion process is spontaneous exothermic physical adsorption. Thermodynamic parameters revealed an activation energy between 32.1 and 24.7 kJ/mol, energy of adsorption between −14.53 and −65.07 and Gibbs free energy of −10.12 kJ/mol which indicated the CLE exothermically spontaneously physisorbed. A model was generated to estimate the effect of the process parameters (inhibitor concentration, reaction time and temperature) using the RSM. Optimization of the process factors was also carried out using the RSM. The percentage inhibition efficiency obtained experimentally (85.61%) was closely comparable to 84.89% obtained by the theoretical technique (RSM). The SEM observations of the inhibited and uninhibited Al samples demonstrated that CLE is an effective corrosion inhibitor for aluminum in acid media.

Results herein provide novel information on the possible application of CLEs as effective eco-friendly corrosion inhibitors.

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.

This study aims to optimize the levels of factors for a green supply chain (GSC) while concurrently gaining valuable insights into the dynamic interrelationships among several factors, leading to reductions in CO₂ emissions and the maximization of the average service level, thereby enhancing overall supply chain performance.

Response surface methodology (RSM) is employed as a technique for multiple response optimization. This study uses a supply chain simulation model that includes decision variables related to the level of inventory control parameters and vehicle capacity. The desirability approach is adopted to achieve optimization objectives by focusing on minimizing CO₂ emissions and maximizing service levels while simultaneously determining the optimum levels of considered decision variables.

The high R² values of 97.38% for CO₂ and 97.28% for service level, along with adjusted R² values reasonably close to predicted values, affirm the models' capability to predict responses accurately. Key significant model terms for CO₂ encompassed reorder point, order up to quantity, vehicle capacity, and their interaction effects, while service level is notably influenced by reorder point, order up to quantity, and their interaction effects. The study successfully achieved a high level of desirability value of %99.1 and the validated performance levels confirmed that the results fall within the prediction interval.

This study introduces a metamodel framework designed to optimize various design parameters for a GSC combining discrete event simulation (DES) and RSM in the form of a simulation optimization model. In contrast to the literature, the current study offers an exhaustive and in-depth analysis of the structural elements of the supply chain, particularly the inventory control parameters and vehicle capacity, which are crucial for comprehending its performance and environmental impact.

The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined and analyzed.

The extracting process was optimized using the response surface methodology (RSM) approach. Material-liquid ratio, temperature and time were chosen as variables and the absorbance as a response. The stability of the tea stem pigment at the different conditions was tested and analyzed.

The optimized extraction technology was as follows: material-liquid ratio 1:20 g/ml, temperature 50°C and time 60 min. The stability test results showed that tea stem pigment was sensitive to oxidants, but the reducing agents did not affect it. The tea stem pigment was unstable under strong acid and strong alkali and was most stable at pH 6. The light stability was poor. Tea stem pigment would form flocculent precipitation under the action of Fe²⁺ or Fe³⁺ and be relatively stable in Cu²⁺ and Na²⁺ solutions. The tea stem pigment was relatively stable at 60°C and below.

No comprehensive and systematic study reports have been conducted on the extraction of pigment from discarded tea stem, and researchers have not used statistical analysis to optimize the process of tannase-assisted tea stem pigment extraction using RSM. Additionally, there is a lack of special reports on the systematic study of the stability of pigment extracted from tea stem.

This paper aims to find the effective 3D printing process parameters based on mechanical characteristics such as tensile strength and hardness of poly lactic acid (PLA)/carbon fibre composites (CF-PLA) by implementing intelligent frameworks.

The experiment trials are conducted based on design of experiments (DoE) using Taguchi L9 orthogonal array with three factors (speed, infill % and pattern type) and three levels. The factors have been optimized by solving the regression equation which is obtained from analysis of variance (ANOVA). The contour plots are generated by response surface methodology (RSM). The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness.

The influencing parameters are found by using Box–Behnken design. The second order response surface model demonstrated the optimal combination of input parameters for higher tensile strength and hardness. The results obtained from RSM are also confirmed by implementing the machine learning classifiers, such as logistic regression, ridge classifier, random forest, K nearest neighbour and support vector classifier (SVC). The results show that the SVC can predict the optimized process parameters with an accuracy of 95.65%.

3D printing parameters which are considered in this work such as pattern types for PLA/CF-PLA composites based on intelligent frameworks has not been attempted previously.

The purpose of this study is to investigate starch mucor (SM) in potassium iodide (KI) as corrosion inhibitor of aluminium in hydrochloric acid (HCl) medium.

The SM in KI was characterized by gravimetric, scanning electron microscopy, electrochemical impedance spectroscopy measurements, potentiodynamic polarization and gas chromatography-mass spectrometer techniques. The inhibition efficiency was optimized using response surface methodology.

The result revealed that the inhibitor inhibited corrosion at a low concentration with the rate of inhibition increasing as the concentration of the inhibitor increased. The inhibition efficiency increases as the temperature was increased with slight incorporation of the inhibitor (SM in KI). This indicates that the corrosion control is both inhibitor (SM in KI) and temperature dependent.

The research results can provide the basis for using SM in KI as corrosion inhibitor of aluminium in HCL medium. Mixed-type inhibitor nature of SM was proved by cathodic and anodic nature of the polarization curves.