Optimizing brushless direct current motor design: An application of the multi-objective generalized normal distribution optimization.

In this study, we tackle the challenge of optimizing the design of a Brushless Direct Current (BLDC) motor. Utilizing an established analytical model, we introduced the Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) method, a biomimetic approach based on Pareto optimality, dominance, and external archiving. We initially tested MOGNDO on standard multi-objective benchmark functions, where it showed strong performance. When applied to the BLDC motor design with the objectives of either maximizing operational efficiency or minimizing motor mass, the MOGNDO algorithm consistently outperformed other techniques like Ant Lion Optimizer (ALO), Ion Motion Optimization (IMO), and Sine Cosine Algorithm (SCA). Specifically, MOGNDO yielded the most optimal values across efficiency and mass metrics, providing practical solutions for real-world BLDC motor design. The MOGNDO source code is available at: https://github.com/kanak02/MOGNDO.

Synthesis and characterizations of super adsorbent hydrogel based on biopolymer, Guar Gum-grafted-Poly (hydroxyethyl methacrylate) (Gg-g-Poly (HEMA)) for the removal of Bismarck brown Y dye from aqueous solution.

Chemical modification of guar gum was done by graft copolymerization of monomer hydroxyethyl methacrylate (HEMA) using azobisisobutyronitrile (AIBN) as initiator. Optimal reaction parameters were settled by varying one reaction condition and keeping the other constant. The optimum reaction conditions worked out were solvent system: binary, [H2O] = 15.00 mL, [acetone] = 5.00 mL, [HEMA] = 82.217× 10-2 mol/L, [AIBN] = 3.333 × 10-2 mol/L, reaction time = 3 h, reaction temperature = 60 °C on to 1.00 g guar gum with Pg = 1694.6 and %GE = 68,704.152. Pure guar gum polymer and grafts were analyzed by several physicochemical investigation techniques like FTIR, SEM, XRD, EDX, and swelling studies. Percent swelling of the guar gum polymer and grafts was investigated at pH 2.2, 7.0, 7.4 and 9.4 concerning time. The finest yield of Ps was recorded at pH 9.4 with time 24 h for graft copolymer. Guar gum and grafted samples were explored for the sorption of toxic dye Bismarck brown Y from the aqueous solution with respect to variable contact time, pH, temperature and dye concentration so as to investigate the stimuli responsive sorption behaviour. Graft copolymers showed better results than guar gum with percent dye uptake (Du) of 97.588 % in 24 h contact time, 35 °C temperature, 9.4 pH at 150.00 ppm dye feed concentration as compared to Guar gum which only showed 85.260 % dye uptake at alike dye fed concentration. The kinetic behaviour of the polymeric samples was evaluated by applying many adsorption isotherms and kinetic models. The value of 1/n was between 0 â†’ 1 showing that there was physisorption of the BB dye that took place on the surface of the polymers. Thermodynamics of BB Y adsorption onto hydrogels was investigated concerning the Van't Hoff equation. -∆G° values obtained from the curve proved the spontanity of the process. Within the context of adsorption efficiency, an investigation was conducted to examine the process of sorption of Bismarck brown Y dye from aqueous solutions. The graft copolymers demonstrated remarkable adsorption abilities, achieving a dye uptake (Du) of 97.588 % over a 24-h period at a temperature of 35 °C, pH level of 9.4, and a dye concentration of 150.00 ppm. The raised adsorption capacity was additionally corroborated by the application of several adsorption isotherms and kinetic models, which indicated that physisorption is the prevailing process/mechanism. Additionally, the thermodynamic research, utilising the Van't Hoff equation, validated the spontaneity of the adsorption phenomenon, as evidenced by the presence of a negative ∆G° values. The thermodynamic analysis revealed herein establishes a strong scientific foundation for the effectiveness of adsorbent composed of graft copolymers based on guar gum. The research conclude the efficiency of the guar gum based grafted copolymers for the water remediation as efficient adsorbents. The captured dye can be re-utilised and the hydrogels can be used for the same purpose in number of cycles.

Multi-Objective artificial bee colony optimized hybrid deep belief network and XGBoost algorithm for heart disease prediction.

The global rise in heart disease necessitates precise prediction tools to assess individual risk levels. This paper introduces a novel Multi-Objective Artificial Bee Colony Optimized Hybrid Deep Belief Network and XGBoost (HDBN-XG) algorithm, enhancing coronary heart disease prediction accuracy. Key physiological data, including Electrocardiogram (ECG) readings and blood volume measurements, are analyzed. The HDBN-XG algorithm assesses data quality, normalizes using z-score values, extracts features via the Computational Rough Set method, and constructs feature subsets using the Multi-Objective Artificial Bee Colony approach. Our findings indicate that the HDBN-XG algorithm achieves an accuracy of 99%, precision of 95%, specificity of 98%, sensitivity of 97%, and F1-measure of 96%, outperforming existing classifiers. This paper contributes to predictive analytics by offering a data-driven approach to healthcare, providing insights to mitigate the global impact of coronary heart disease.

Influence of Deposition Time on Titanium Nitride (TiN) Thin Film Coating Synthesis Using Chemical Vapour Deposition.

Titanium nitride (TiN) thin film coatings were grown over silicon (p-type) substrate using the atmospheric pressure chemical vapour deposition (APCVD) technique. The synthesis process was carried out to evaluate the effect of deposition time on the physical and mechanical characteristics of TiN coating. Thin films grown over Si substrate were further characterised to evaluate the morphological properties, surface roughness and mechanical properties using a scanning electrode microscope (SEM), atomic force microscopy (AFM) and nanoindentation, respectively. EDS equipped with SEM showed the presence of Ti and N elements in considerable amounts. TiN morphology obtained from the SEM test showed small-sized particles on the surface along with cracks and pores. AFM results revealed that by increasing the deposition time, the surface roughness of the coating also increased. The nanomechanical properties such as nanohardness (H) and Young's modulus (E), etc., evaluated using the nanoindentation technique showed that higher deposition time led to an increase in H and E. Overall, it was observed that deposition time plays a vital role in the TiN coating deposition using the CVD technique.

Improvements in the Engineering Properties of Cementitious Composites Using Nano-Sized Cement and Nano-Sized Additives.

The findings of an extensive experimental research study on the usage of nano-sized cement powder and other additives combined to form cement-fine-aggregate matrices are discussed in this work. In the laboratory, dry and wet methods were used to create nano-sized cements. The influence of these nano-sized cements, nano-silica fumes, and nano-fly ash in different proportions was studied to the evaluate the engineering properties of the cement-fine-aggregate matrices concerning normal-sized, commercially available cement. The composites produced with modified cement-fine-aggregate matrices were subjected to microscopic-scale analyses using a petrographic microscope, a Scanning Electron Microscope (SEM), and a Transmission Electron Microscope (TEM). These studies unravelled the placement and behaviour of additives in controlling the engineering properties of the mix. The test results indicated that nano-cement and nano-sized particles improved the engineering properties of the hardened cement matrix. The wet-ground nano-cement showed the best result, 40 MPa 28th-day compressive strength, without mixing any additive compared with ordinary and dry-ground cements. The mix containing 50:50 normal and wet-ground cement exhibited 37.20 MPa 28th-day compressive strength. All other mixes with nano-sized dry cement, silica fume, and fly ash with different permutations and combinations gave better results than the normal-cement-fine-aggregate mix. The petrographic studies and the Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) analyses further validated the above findings. Statistical analyses and techniques such as correlation and stepwise multiple regression analysis were conducted to compose a predictive equation to calculate the 28th-day compressive strength. In addition to these methods, a repeated measures Analysis of Variance (ANOVA) was also implemented to analyse the statistically significant differences among three differently timed strength readings.

Comparative Study on the Behavior of Reinforced Concrete Beam Retrofitted with CFRP Strengthening Techniques.

Lateral reinforcement has a significant impact on the strength and ductility of concrete. Extra confinement is provided in this project by carbon fiber reinforced polymer (CFRP) sheets wrapped around the outside of reinforced concrete (RC) beams. To determine the failure criteria and maximum load-carrying capacity of beams, numerous specimens were cast and tested in a flexural testing machine. This paper presents the results of an experimental investigation of functionally damaged reinforced concrete beams repaired in flexure with CFRP sheets. The most essential variable in this study is the CFRP sheet scheme, and seven different strengthening schemes (B1 to B7) were explored in the experimental program. In conclusion, the findings of the study showed that flexural retrofitting of reinforced concrete beams with CFRP sheets is functionally effective, with restored strength and stiffness values roughly equivalent to or greater than those of the control beam (CB1). The efficiency of the flexural retrofitting mechanism appears to vary depending on the layout of the CFRP sheet. Steel rupture and concrete crushing were shown to be the most common failure modes in the investigation, causing CFRP sheets to break in retrofitted beams.

Multiobjective Optimization of Chemically Assisted Magnetic Abrasive Finishing (MAF) on Inconel 625 Tubes Using Genetic Algorithm: Modeling and Microstructural Analysis.

The demand for the surface integrity of complex structures is drastically increasing in the field of aerospace, marine and automotive industry. Therefore, Inconel alloy, due to its superior attributes, has a wide scope for the improvement in surface integrity. To achieve the precise surface finish and enhance the process performance, process optimization is necessary. In current paper, chemically assisted MAF process parameters were optimized using the genetic algorithm (GA) approach during finishing of Inconel 625 tubes. Regression models were developed for improvement in internal surface finish (PIISF), improvement in external surface finish (PIESF), and material removal (MR) using Design expert software. Then, the surface microstructure of Inconel 625 tubes was analyzed using scanning electron microscopy (SEM). ANOVA analysis predicts that processing time and abrasive size have the highest percentage contribution in improving the surface finish and material removal. Multioptimization results suggested to set the level of processing time (A) at 75 min, surface rotational speed (B) at 60 RPM, weight % of abrasives (C) at 30%, chemical concentration (D) at 500 gm/lt and abrasive size (E) at 40 microns to obtain optimal parameters for PIISF, PIESF and MR responses.

Impact of Unsustainable Environmental Conditions Due to Vehicular Emissions on Associated Lifetime Cancer Risk in India: A Novel Approach.

The Indian Western Himalayas (IWHs) are a world famous tourist spot, and every year millions of tourists visit this area in fossil fuel-driven vehicles. Emissions from these vehicles persistently deteriorate the pristine environment of the IWHs. Therefore, in the current study, efforts were made to assess the compromised environmental conditions of Manali, Himachal Pradesh, India that resulted from the inflow of tourists and the activities undertaken by them. This study revealed that Manali could sustainably accommodate only 0.305 M tourists/month, and this threshold was reported to be crossed in the months of April, May and June. Furthermore, to augment these findings, water and ambient air samples were collected and analyzed for the presence of elemental carbon (EC) from one of the medium tourism potential regions of Manali, i.e., the Hamta glacier. The tributary receiving water from the Hamta glacier and the ambient air of the area was observed to be contaminated with 42 ± 12 ppb and 880 ± 43 µg m-3 of EC, respectively. It was observed that the inhalation and ingestion of EC-contaminated air and water could jeopardize human health due to a high lifetime cancer risk. However, without the intervention of eco-tourism in the study area, higher environmental health effects were also speculated. The observations made in this study are expected to trigger the interests of the researchers, international scientific community and regional authorities working towards the unsustainable development of the IWHs and deteriorating environmental conditions.

Multifunctional Modified Chitosan Biopolymers for Dual Applications in Biomedical and Industrial Field: Synthesis and Evaluation of Thermal, Chemical, Morphological, Structural, In Vitro Drug-Release Rate, Swelling and Metal Uptake Studies.

The hydrogel materials are getting attention from the research due to their multidimensional usage in various fields. Chitosan is one of the most important hydrogels used in this regard. In this paper multifunctional binary graft copolymeric matrices of chitosan with monomer AA and various comonomers AAm and AN were prepared by performing free radical graft copolymerization in the presence of an initiator KPS. The binary grafting can be done at five different molar concentrations of binary comonomers at already optimized concentration of AA, KPS and other reaction conditions such as time, temperature, solvent amount, etc. Various optimum reaction conditions were investigated and presented in this work; the backbone as well as binary grafts Ch-graft-poly (AA-cop-AAm) and Ch-graft-poly (AA-cop-AN) were characterized via various physio-chemical techniques of analysis such as SEM analysis, Xray diffraction (XRD), TGA/DTA and FTIR. In the batch experiments, the binary grafts were investigated for the percent swelling with respect to pH (pH of 2.2, 7.0, 7.4 and 9.4) and time (contact time 1 to 24 h). Uploading and controllable in vitro release of the drug DS (anti-inflammatory) was examined with reverence to gastrointestinal pH and time. The binary grafts showed significantly better-controlled drug diffusion than the unmodified backbone. The kinetic study revealed that the diffusion of the drug occurred by the non-Fickian way. In the case of separation technologies, experiments (batch tests) were executed for the toxic bivalent metal ions Fe (II) and Pb (II) sorption from the aqueous media with respect to the parameters such as interaction period, concentration of fed metal ions in solution, pH and temperature. The binary grafted matrices showed superior results compared to chitosan. The kinetics study revealed that the matrices show pseudo-second order adsorption. The graft copolymer Ch-graft-poly (AA-cop-AAm) provided superior results in sustainable drug release as well as metal ion uptake. The study explored the potential of chitosan-based materials in the industry as well in the biomedical field. The results proved these to be excellent materials with a lot of potential as adsorbents.

Effects of Elevated Temperature on the Residual Behavior of Concrete Containing Marble Dust and Foundry Sand.

Concrete is a composite material that is commonly used in the construction industry. It will certainly be exposed to fires of varying intensities when used in buildings and industries. The major goal of this article was to look into the influence of mineral additions such as foundry sand and marble dust on the residual characteristics of concrete. To examine the behavior of residual characteristics of concrete after fire exposure, marble dust was substituted for cement and fine sand was substituted for foundry sand in varying amounts ranging from 0% to 20%. It aided in the better disposal of waste material so that it might be used as an addition. The purpose of the experiment was to see how increased temperatures affected residual properties of concrete, including flexural strength, compressive strength, tensile strength, static as well as dynamic elastic modulus, water absorption, mass loss, and ultrasonic pulse velocity. At temperatures of 200 °C, 400 °C, 600 °C, 800 °C, and 1000 °C, the typical fire exposure behavior of concrete was investigated. The effects of two cooling techniques, annealing and quenching, on the residual properties of concrete after exposure to high temperatures were investigated in this study. Replacement of up to 10% of the cement with marble dust and fine sand with foundry sand when concrete is exposed to temperatures up to 400 °C does not influence the behavior of concrete. At temperatures above 400 °C, however, the breakdown of concrete, which includes marble dust and foundry sand, causes a rapid deterioration in the residual properties of concrete, primarily for replacement of more than 10%.

Preference Index of Sustainable Natural Fibers in Stone Matrix Asphalt Mixture Using Waste Marble.

The present study investigates the preference index of natural fibers such as sisal, coir, and rice straw fibers in stone matrix asphalt mixtures (SMA), using waste marble as filler. Waste marble was used as the filler in asphalt mixtures and was crushed by abrasion machine and sieved according to SMA filler requirements. The SEM topography and EDS analysis of sisal, coir, and rice straw fibers were also carried out. The Marshall test was conducted, which is the most acceptable, cost-effective, and widely adopted method to estimate the optimum bitumen and to examine several Marshall Measures, such as flow value, voids filled with bitumen (VFB), stability, voids in mineral aggregate (VMA), and air voids (VA). Furthermore, tests were performed on the specimen with the optimum amount of bitumen, different percentages of fibers, and waste marble as filler to calculate drain down, moister sensitivity, and Marshall Stability. Multi-criteria decision-making (MCDM) techniques were implemented to obtain subjective and objective weights, which were further used to compute the values of the preference index of natural fiber contents. The outcomes revealed favorable results for the usage of marble dust as filler in Stone Matrix Asphalt (SMA). In addition, the preference index upshots are inclined toward the usage of rice straw over coir followed by sisal fiber. It was observed that the value of the preference index in rice straw at 0.3 varied from 0.918, 0.925, and 0.931 in rice straw using equal, objective, and subjective weights, respectively. The maximum drain down value observed is 0.335 based on ASTM-D 6390 and IRC-SP-79 are against 0.3 percent natural fiber. Moreover, as per the prescribed limit of MoRTH, because of the thin film around aggregates, moisture susceptibility characteristics, i.e., better resistance to moisture, were enhanced by more than 80%.

Impact of Process Variables of Acetone Vapor Jet Drilling on Surface Roughness and Circularity of 3D-Printed ABS Parts: Fabrication and Studies on Thermal, Morphological, and Chemical Characterizations.

Ever since the introduction of 3D printing, industries have seen an exponential growth in production and efficiency. Three-dimensional printing is the process of additive manufacturing (AM) in which the conventional method of material removal is challenged. Layer-on-layer deposition is the basic principle of the AM. Additive manufacturing technologies are used to create 3D-printed objects. An object is built in an additive technique by laying down successive layers of material until the object is complete. Each of these layers can be viewed as a cross-section of the item that has been lightly cut. When compared to traditional production methods, 3D printing allows the creation of complicated shapes with less material. In conventional methods, the materials go through several damages due to the tool-workpiece contact creating friction between them and the dissipated heat that damages the material. Overcoming the conventional method of machining with the help of 3D printing is a new advancement in the industries. The process involves using non-conventional methods for the machining of the parts. This research was oriented towards the chemical vapor jet drilling of the acrylonitrile-butadiene-styrene (ABS) materials. ABS materials are highly machinable and can be recycled for further usage. This paper focused on the usage of acetone as the chemical for drilling. The surface roughness and circularity of the drilled hole was taken into account for this research paper. We set up a manual experiment to run tests and get results. A vapor jet machine was designed with acetone as the core for the vapor. Various analyses were also formulated and conducted during experimentations. Surface roughness analysis provided the insight of roughness after the machining with the help of acetone vapor jet spray. SEM and micro-image parameters were also considered for more clear and advanced reports. In this research paper, DSC and FTIR analysis were performed to understand changes in the internal structure and the material properties of the ABS. Moreover, the research aimed to investigate the effect of various inputs processing parameters such as pressure, flow rate, and stand-off distance on the surface roughness and circularity of ABS workpiece material. The Taguchi L9 orthogonal array design was utilized to conduct tests by chemical vapor jet drilling using acetone and to evaluate the performance of the set-up while reducing the influence of interfering factors in order to provide reliable surface finish and circularity results. The results and conclusion of the research paper aimed to determine the most suitable parameters for the non-conventional acetone vapor jet drilling of the ABS material. The theoretical calculations predicted 1.64432 and 0.3289080 values of surface roughness and circularity, respectively. On the other hand, the experimental values were recorded as 1.598 for surface roughness and 0.322 for circularity. Therefore, a negligible error of 0.046 for surface roughness and 0.0031 for circularity, respectively, was noted which validate the statistical equations and the consistency of the combined vapor jet drilling process.

Comparative Drug Release Investigations for Diclofenac Sodium Drug (DS) by Chitosan-Based Grafted and Crosslinked Copolymers.

The hydrogels responding to pH synthesized by graft copolymerization only and then concurrent grafting and crosslinking of monomer N-isopropyl acrylamide (NIPAAM) and binary comonomers acrylamide, acrylic acid and acrylonitrile (AAm, AA and AN) onto chitosan support were explored for the percent upload and release study for anti-inflammatory diclofenac sodium drug (DS), w.r.t. time and pH. Diclofenac sodium DS was seized in polymeric matrices by the equilibration process. The crosslinked-graft copolymers showed the highest percent uptake than graft copolymers (without crosslinker) and chitosan itself. The sustainable release of the loaded drug was studied with respect to time at pH 2.2, 7.0, 7.4 and 9.4. Among graft copolymers (without crosslinking), Chit-g-polymer (NIPAAM-co-AA) and Chit-g-polymer (NIPAAM-co-AN) exhibited worthy results for sustainable drug deliverance, whereas Crosslink-Chit-g-polymer (NIPAAM-co-AA) and Crosslink-Chit-g-polymer (NIPAAM-co-AAm) presented the best results for controlled/sustained release of diclofenac sodium DS with 93.86 % and 96.30 % percent release, respectively, in 6 h contact time. Therefore, the grafted and the crosslinked graft copolymers of the chitosan showed excellent delivery devices for the DS with sustainable/prolonged release in response to pH. Drug release kinetics was studied using Fick's law. The kinetic study revealed that polymeric matrices showed the value of n as n > 1.0, hence drug release took place by non-Fickian diffusion. Hence, the present novel findings showed the multidirectional drug release rate. The morphological changes due to interwoven network structure of the crosslinked are evident by the Scanning electron microscopy (SEM) analysis.

Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling.

Additive manufacturing has gained popularity among material scientists, researchers, industries, and end users due to the flexible, low cost, and simple manufacturing process. Among number of techniques, fused deposition modeling (FDM) is the most recognized technology due to easy operation, lower environmental degradation, and portable apparatus. Despite numerous advantages, the limitations of this technique are poor surface finish, dimensional accuracy, and mechanical strength, which must be improved. The present study focuses on the implementation of the genetic algorithm and Taguchi techniques to achieve minimum dimensional variability of FDM parts especially for polymeric biocomposites. The output has been measured using standard testing techniques followed by Taguchi and genetic algorithm analyses. Four response variables were measured and were converted into single variable with combination of different weightages of each response. Maximum weightage was given to width of FDM polymeric biocomposite parts which may play critical role in biomedical and aerospace applications. The advanced optimization and production techniques have yielded promising results which have been validated by advanced algorithms. It was found that layer thickness and orientation angle were significant parameters which influenced the dimensional accuracy whereas best fitness value was 0.377.

Predictive modeling of surface and dimensional features of vapour-smoothened FDM parts using self-adaptive cuckoo search algorithm.

Despite numerous advantages of fused deposition modeling (FDM), the inherent layer-by-layer deposition behavior leads to considerable surface roughness and dimensional variability, limiting its usability for critical applications. This study has been conducted to select optimum parameters of FDM and vapour smoothing (chemical finishing) process to maximize surface finish, hardness, and dimensional accuracy. A self-adaptive cuckoo search algorithm for predictive modelling of surface and dimensional features of vapour-smoothened FDM-printed functional prototypes has been demonstrated. The chemical finishing has been performed on hip prosthesis (benchmark) using hot vapours of acetone (using dedicated experimental set-up). Based upon the selected design of experiment technique, 18 sets of experiments (with three repetitions) were performed by varying six parameters. Afterwards, a self-adaptive cuckoo search algorithm was implemented by formulating five objective functions using regression analysis to select optimum parameters. An excellent functional relationship between output and input parameters has been developed using a self-adaptive cuckoo search algorithm which has successfully found the solution to optimization issues related to different responses. The confirmatory experiments indicated a strong correlation between predicted and actual surface finish measurements, along with hardness and dimensional accuracy.

Investigations on Melt Flow Rate and Tensile Behaviour of Single, Double and Triple-Sized Copper Reinforced Thermoplastic Composites.

Thermoplastic composite materials are emerging rapidly due to the flexibility of attaining customized mechanical and melt flow properties. Due to high ductility, toughness, recyclability, and thermal and electrical conductivity, there is ample scope of using copper particles in thermoplastics for 3d printing applications. In the present study, an attempt was made to investigate the Melt Flow Index (MFI), tensile strength, and electrical and thermal conductivity of nylon 6 and ABS (acrylonitrile butadiene styrene) thermoplastics reinforced with copper particles. Thus, the experiments were conducted by adding different-sized copper particles (100 mesh, 200 mesh, and 400 mesh) in variable compositions (0% to 10%) to ABS and nylon 6 matrix. The impact of single, double, and triple particle-sized copper particles on MFI was experimentally investigated followed by FTIR and SEM analysis. Also, the tensile, electrical, and thermal conductivity testing were done on filament made by different compositions. In general, higher fluidity and mechanical strength were obtained while using smaller particles even with higher concentrations (up to 8%) due to improved bonding strength and adhesion between the molecular chains. Moreover, thermal and electrical conductivity was improved with an increase in concentration of copper particles.

Optimization of FFF Process Parameters by Naked Mole-Rat Algorithms with Enhanced Exploration and Exploitation Capabilities.

Fused filament fabrication (FFF) has numerous process parameters that influence the mechanical strength of parts. Hence, many optimization studies are performed using conventional tools and algorithms. Although studies have also been performed using advanced algorithms, limited research has been reported in which variants of the naked mole-rat algorithm (NMRA) are implemented for solving the optimization issues of manufacturing processes. This study was performed to scrutinize optimum parameters and their levels to attain maximum impact strength, flexural strength and tensile strength based on five different FFF process parameters. The algorithm yielded better results than other studies and successfully achieved a maximum response, which may be helpful to enhance the mechanical strength of FFF parts. The study opens a plethora of research prospects for implementing NMRA in manufacturing. Moreover, the findings may help identify critical parametric levels for the fabrication of customized products at the commercial level and help to attain the objectives of Industry 4.0.

Deposition angle prediction of Fused Deposition Modeling process using ensemble machine learning.

In present study, artificial intelligence systems intertwine with mechanical systems for reducing the manufacturing time and cost of products. In Fused Deposition Modeling (FDM) optimum value of deposition angle significantly varies with product geometry; hence, prediction and validation is performed using ensemble based random forest machine learning model. The training data is generated using different shapes and geometries whereas correlation based feature selection technique is employed to explore the crucial features of products. To check the effectiveness of the random forest model K-fold cross validation method is used. The empirical evaluation shows a prediction accuracy of 94.57%, remarkably superior than other methods. The proposed robust model efficiently predicts the optimum deposition angle for any geometry which would further enhance the applicability of digitally manufactured products.

Taguchi S/N and TOPSIS Based Optimization of Fused Deposition Modelling and Vapor Finishing Process for Manufacturing of ABS Plastic Parts.

Despite several additive manufacturing techniques are commercially available in market, Fused Deposition Modeling (FDM) is increasingly used by researchers and engineers for new product development. FDM is an established process with a plethora of advantages, but the visible surface roughness (SR), being an intrinsic limitation, is major barrier against utilization of fabricated parts for practical applications. In the present study, the chemical finishing method, using vapour of acetone mixed with heated air, is being used. The combined impact of orientation angle, finishing temperature and finishing time has been studied using Taguchi and ANOVA, whereas multi-criteria optimization is performed using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The surface finish was highly responsive to increase in temperature while orientation angle of 0° yielded maximum strength; increase in finishing time led to weight gain of FDM parts. As the temperature increases, the percentage change in surface roughness increases as higher temperature assists the melt down process. On the other hand, anisotropic behaviour plays a major role during tensile testing. The Signal-to-noise (S/N) ratio plots, and ANOVA results indicated that surface finish is directly proportionate to finishing time because a longer exposure results in complete layer reflowing and settlement.

Mechanical Strength Enhancement of 3D Printed Acrylonitrile Butadiene Styrene Polymer Components Using Neural Network Optimization Algorithm.

Fused filament fabrication (FFF), a portable, clean, low cost and flexible 3D printing technique, finds enormous applications in different sectors. The process has the ability to create ready to use tailor-made products within a few hours, and acrylonitrile butadiene styrene (ABS) is extensively employed in FFF due to high impact resistance and toughness. However, this technology has certain inherent process limitations, such as poor mechanical strength and surface finish, which can be improved by optimizing the process parameters. As the results of optimization studies primarily depend upon the efficiency of the mathematical tools, in this work, an attempt is made to investigate a novel optimization tool. This paper illustrates an optimization study of process parameters of FFF using neural network algorithm (NNA) based optimization to determine the tensile strength, flexural strength and impact strength of ABS parts. The study also compares the efficacy of NNA over conventional optimization tools. The advanced optimization successfully optimizes the process parameters of FFF and predicts maximum mechanical properties at the suggested parameter settings.