Papers by Keyword: Optimization

Abstract: Forming a metallic sheet along with the consideration of computer simulation and experiment had benefited the milling industry for a long time. The ideal forming, without an error, is a concerning topic. So, the computer simulation had the advantage then direct forming. To observe the results before doing the real experiments simulation comes handy. Which helped to set the parameters for the milling process for the single point incremental forming (SPIF) process. For milling, a CAD design was converted into a 3D model. For this, a conical shape of 3D modeling was made in fusion 360. After onwards, it was simulated for finding the maximum depth for the cracking point. Next for the experimental part, the maximum forming depth was considered, and used lubricant grease for reducing friction. While forming with the grease, the impact of parameters was also changed. Throughout the process, an optimization approach was set to reduce the cracking areas for the G-code. Along with the lubricant use, smooth milling finished surface was observed. To reducing the depth forming errors, an optimization approach was introduced in this research.

Abstract: FSW is a welding process which done by movement of tool against the workpiece. Tool is an important part in FSW process because tool generates most of the heat in the FSW process, so the tool material and geometry are important because they receive high stress and temperature. This research was conducted to decide the best pin geometry for tool from the 4-pin geometry that has been decided, which is straight cylindrical, tapered cylindrical, hexagonal, and tapered square. The optimization process is done with Taguchi method using 4 factors where each factor has 4 levels, factors that used in this research are tool rotation speed, welding speed, tool shoulder angle, and tool tilt angle with the respond is temperature at welding joint. The optimization process will be done in all of the pin geometries that has been decided and the best pin geometry out of 4 geometries will be chosen. The best pin out of 4 geometries is the hexagonal pin with the optimized parameters are the rotational speed of 1208 rpm, welding speed of 65 mm/min, tilt angle of 2.5° and concave angle of 2° with max. temperature of 322.48°C. The significant factor obtained was the tool rotational speed and concave angle with significance level of 95%.

Abstract: 2,4,6- Trichlorophenol (TCP) is a toxic, mutagenic, and carcinogenic compound found in the emission from fossil fuel combustion, municipal waste incineration, and water disinfection for domestic usage. TCP has been classified as one of the primary pollutants that should be treated for inland water discharge. This study aims to introduce a new approach to remove the TCP in wastewater through the simple and cost-effective progressive freeze concentration (PFC) method. The effect of coolant temperature and circulation flow rate in the PFC method was investigated, and its effectiveness was characterized by calculating the effective partition constant (K) and the TCP reduction (T_R). Optimisation was performed to determine the optimum condition for the TCP removal using Response Surface Methodology (RSM). The best circulation flow rate and coolant temperature for the one-variable-at-a-time (OVAT) experiment were found to be 900 rpm and -5 °C. Based on ANOVA, the PFC system was predicted to produce a low K value and high T_R with temperature in the range of -4.5 °C to -5 °C and circulation flow rate in the range of 900 rpm to 1000 rpm.

Abstract: According to the ICF (International Classification of Functioning, Disability, and Health), a prosthetic is a device used to restore or replace the function of a missing limb as a result of a rare genetic defect, dangerous incident, surgical trauma, or disease that limits the amputee's ability to participate in daily life. Prosthetic limb sockets were formerly made out of a wide variety of materials before the development of thermoplastics and composites. Plant fibers are favored due to their low density. Both their strength and rigidity are remarkably high considering their low weight and inexpensiveness. Plant fiber is one of the most popular ways to give polymer composites more strength because of its low production costs and stretchability. Following a brief introduction to the many types of natural fibers (both plant and animal), this article provides a comprehensive assessment of the literature from the past decade that focuses on the mechanical characteristics of plant materials. Reinforced polymers are made with fibers. This literature study will focus on the mechanical properties and behavior of plant fibers used to create sockets for prosthetic limbs. If an article is written about the overall features of composites made with fibers made from the plant, it is expected to be of great use to the research community in the field of composites.

Abstract: The application of laser-structured metal surfaces to combine plastics and metals is a promising option to enable low-cost lightweight and resource-efficient multi-material joints. The mechanical properties (especially strength), as well as production time and costs, depend on the microstructure of the metal surface (e.g. the number, distance and shape of cavities). Thus, in order to design optimal joints, the properties from the mechanical, as well as production and cost domain, must be considered simultaneously during product development. Therefore, in this paper, a model-based optimization approach is presented with the goal of identifying an optimum between the strength of the joint and laser manufacturing costs. Parameterized models for the strength estimation, as well as calculation of laser manufacturing time and costs, are developed. The models are linked in an optimization workflow and the optimum positioning and shape of the cavities on the joining zone is determined using a genetic optimization algorithm. The results show that, compared to a benchmark, the manufacturing costs can be reduced by 82 % for the same strength using the proposed model-based optimization approach.

Abstract: The statistical model is created for predicting penetration depth in an alternating current-based additional axial magnetic field controlled shielded metal arc welding of ASTM A 516 Gr.70 steel. The design for the trials is developed using the Placket-Burman design and response surface methodology. The created model determines the optimum process variables for getting excellent penetration depth. The input variables (current, magnetic field density, and magnetic frequency) are chosen for a response like penetration depth. This model can predict the main effects and the interacting effects of three process variables. The findings reveal that a higher current value with a low magnetic field density leads to deeper penetration and vice versa. Furthermore, a greater penetration depth is achieved at lower magnetic field density and higher magnetic frequency. With a desirability of 98.8%, the optimum process variables are 110 A, 0 mT, and 60 Hz. The predicted response values produced from the regression equation based upon process variables are extremely similar to the observed output, demonstrating the usefulness of second-order regression equations. For improved joint efficiency, a high level of penetration is needed.

Abstract: Now a days, Non-Conventional Machining process is gaining more attention by the researchers. Abrasive Water jet machining (AWJM) is one of such machining process where material is removed with abrasive slurry as cutting tool. The present work discuss about the development of an optimal solution for minimizing surface roughness using a response surface methodology (RSM) while machining of EN grade steel. The machining parameters considered for the study are Abrasive Grain Size (AGS) and Hydraulic Pressure (HP) and Stand Off Distance (SOD) and the Abrasive Flow Rate (AFR). The response parameter is surface roughness (Ra). The experiments are performed based on the Box-Behnken design. Additionally, the significance of the developed optimization design has been identified using analysis of variance (ANOVA). Finally, the validity and adequacy of the developed model are done through confirmation tests. Key Words: Abrasive Water jet Machining, Response Surface Methodology, Optimization, ANOVA

Abstract: The article deals with the use of granite filer as a concrete admixture. It examines the filter in detail not only as a whole (one component in concrete) but separates it into fractions. Since it is a filter produced during cutting, grinding and polishing of granite elements, it is granite slurry. For these reasons, the simplest method of separation - sedimentation in a flowing liquid - was applied to separate the individual fractions. After drying, the individual fractions were examined for their suitability for use in concrete. The most important physical and chemical parameters - bulk density, specific surface area, grain shape and size, chemical composition - were determined. Based on the measured values and in relation to previous in-house investigations, granite filer can be considered as a suitable admixture for cement composites.

Abstract: The sands, used in concrete mixes, differ significantly in their coarseness of grading, voidness, apparent density and other characteristics, which largely affects the properties of concrete. At the same time, there is practically no possibility of evaluating the properties of concrete by any one general characteristic of sand. Such a characteristic of sands as "reduced voidness", which was used to evaluate the properties of fine concrete with sands of different grades, is proposed in the article to evaluate the quality of sands. This work presents a theoretical interest, and is also of practical importance, contributing to increased accuracy of concrete mixes design and prediction of its strength and other construction properties.

Abstract: Conducting experiments for material modeling is very costly and time-consuming when many parameters are involved, resulting in a large number of test conditions. Therefore, it is expedient to develop algorithms for the iterative identification of optimal test conditions. This method should allow the model to learn automatically so that only a small number of test conditions are selected at the beginning of the model calibration. In order to decide whether further experiments should be carried out and which test conditions need to be investigated, meta-models are generated, and the expected gain score is calculated. The next sample is selected based on the highest score, and this procedure continues until the material models meet a termination criteria. The result from the study shows that the implemented method uses 12 test conditions to generate a phase transformation model for 22MnB5 steel. The material models fitted with the proposed method provide acceptable predictions when compared with experimental data.