Papers by Keyword: DOE

Abstract: The powder bed fusion with electron beam (PBF-EB) process is characterised by a preheating step that keeps the building temperature high and produces partial sintering of the metallic powder particles. The influence of the preheating parameters can be studied through numerical simulations, such as those conducted with the phase field (PF) method. PF can describe the neck formation among the particles under the sintering mechanisms. In this regard, PF simulations usually account for the diffusion mechanisms only, neglecting the rigid body motion (RBM), particularly during PBF-EB. The current work analyses the effect of RBM on neck formation and growth among particles subjected to the typical working conditions of a PBF-EB. Owing to the lack of literature, the parameters that describe the rigid translation of the particles undergoing the sintering are identified using a structured design of numerical experiment. Including the RBM during sintering produces a larger neck among the particles and faster densification. This result has been found in agreement with the current literature. However, the decision to include or not the RBM should be adequately waited, considering that in the current study including RBM increased the simulation time. The results revealed that each parameter plays a different role in the rigid translation of the particles, causing a different neck dimension.

Abstract: The research centered on creating magnetic water hyacinth biochar (MWHB) by chemically co-precipitating Fe²⁺ and Fe³⁺ ions onto the initial biomass, which was pyrolyzed at 450°C for an hour. This MWHB was then utilized in a series of batch adsorption experiments to evaluate its effectiveness in removing nitrates from simulated wastewater. The investigation focused on understanding the impact of pH, amount of adsorbent used, and duration of contact on nitrate removal efficiency. These parameters were selected using a 2^k+1 Full Factorial Design of Experiments (DOE). The data collected from the experiments underwent analysis in JMP® (SAS institute) using Pearson’s Correlation test, providing a comprehensive statistical analysis beyond utilizing the software's Prediction Profiler. The findings revealed that the quantity of adsorbent used significantly affected the nitrate removal efficiency of the magnetic biochar, demonstrating a correlation coefficient (r) of 0.8459. On the other hand, pH and contact time exhibited relatively weaker effects, obtaining correlation coefficients of-0.1943 and 0.2915, respectively. The DOE suggested the optimal conditions for nitrate removal to be at pH 3, utilizing 0.40 grams of adsorbent, and maintaining a contact time of 90 minutes, with a predicted nitrate removal efficiency of approximately 99.10%, while the actual removal efficiency stood at 97.31%. Additionally, Scanning Electron Microscopy (SEM) analysis was employed to examine the surface morphology of the MWHB before and after nitrate removal, aiding in understanding the factors contributing to the observed nitrate removal efficiency.

Abstract: This paper presents the problem of determining the optimal input process parameters of a Fused Deposition Modelling 3D printer for improved mechanical strength of the 3D printed objects. Polylactic Acid material tensile test and Izod impact test specimen are printed as per the ASTM standards. Various critical input parameters infill density, infill pattern, raster angle and number of contours are analysed on the material. The tensile and impact strengths were determined by conducting 16 experiments using a Tensometer for tensile test while a pendulum impact test is used for Izod impact test. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is used to train input and output data and optimal parameters are obtained for improved mechanical strength. The tensile strength and impact strength have been improved by 19.8% and 18.3% respectively with the optimal set of input parameters determined in the analysis.

Abstract: Fiber-reinforced 3D printing filaments are composite materials compounded with short, chopped additives (in this paper case glass fibers) in a polymer matrix base. Engineering filaments and reinforced filaments have gotten a lot more popular in the last few years due to their capabilities and added properties given by the reinforced material. The biggest drawback reinforced materials have other than the cost is the printability. Due to the abrasive nature of glass fiber to be able to successfully print it certain modifications to the FDM equipment must be made, such as using a tempered steel nozzle. It is also recommended to print the components in a temperature-controlled room and to keep the humidity level of the material before printing as low as possible. In this paper a glass fiber reinforced PA6 filament was tested using different printing parameters (temperature, printing speed, layer height) to establish the optimal parameters for reducing the risk reinforced materials pose for the FDM equipment while also looking for the best mechanical properties of the printed parts.

Abstract: The objective of this work is to use PLA plastic matrices printed using the FDM additive manufacturing technique as an alternative to conventional sheet metal bending. In this way, the demand of the industry to obtain highly customized short series bent parts at a reduced price is covered. To demonstrate this hypothesis, first, the maximum compressive strength of FDM printed specimens with different manufacturing parameters was characterized by performing a parametric analysis using a factorial design of experiments (DOE) model and based on the ISO 604 standard. Once the results were analysed, an articulated bending tool was designed and printed with the best configuration obtained previously. Then, 50 S280GD galvanized steel sheets of 1 mm thickness were bent. Finally, the bending angles of the sheets were examined, checking that the bending was performed correctly, obtaining the desired shape in the sheet. As for the analysis of the economic impact, a 97.75% reduction in the manufacturing price of the tooling with respect to conventional tooling was observed, demonstrating the viability of these dies in an industrial environment.

Abstract: Mechanical joining techniques like clinching are standard joining techniques for processing aluminum and steel alloys in the automotive car body manufacturing. When using conventional methods, joints will have a high quality after a finally tool check on a specific joining press system. However, if the press system during manufacturing will changed, it can occur that joints get other quality values e.g. smaller interlock. The reason for that has multiple influences,this paper considers especially the press-sided ones. With optical measurements of press deformation and punch speed during real joining processes, new 3D-halfsymmetric simulation models were built up, which take into account of press-side behavior such as joining velocity and angular as well as lateral misalignment of the joining tools during clinching process. Sensitivity analyses identifies significant influencing variables. On the base of this, equations of quality changes can be determined. Finally, this allows better prediction of the modification about joint quality after a press change from system A to B or C during manufacturing.

Abstract: The awareness on sustainability of the environment among the researchers leads to the exploration of natural fiber composite materials. Hybridization of synthetic fiber and natural fiber is one of the potential strategies to enhance the mechanical properties as well as the degradability of such composite materials. However, less information concerning the optimization of tribological properties of this hybrid composite is available in literature. The aim of this study is to propose a statistical model to predict and optimize wear and coefficient of friction of kenaf/carbon reinforced epoxy composite. The value of parameters; load and sliding velocity ranges from 10 to 30 N and 20.9 to 52.3 m/s, respectively, are used to assess wear and coefficient of friction (COF) of different stacking sequences using the Analysis of Variance (ANOVA). The tribological test was conducted using a pin-on-disc tribometer. Multifactorial design analysis was employed to optimize the test control variables. It was found that, the optimized factors that affects the coefficient of friction and wear is at load 30 N and sliding velocity of 52.36 m/s. The proposed statistical models for wear and COF have 99.5% and 97.6% reliability, respectively. The generated equation models are bounded within the wear test control factors and ranges. The outcome from this study will be very useful for main parameter prediction for an optimized wear and COF.

Abstract: In present work, Aluminium 6061 was reinforced by varying the percentage of sugarcanebagasse ash (SCBA). Al-SCBA composite samples were fabricated by stir casting method. The weartest conducted on the samples using a pin on disc machine under the normal sliding condition. Basedon the testing parameters (Volume fraction ‘V’, Load ‘L’, sliding speed ‘S’) an L27 Orthogonal arraydesign was selected. According to L27 array, the wear & friction test was conducted. variance analysis(ANOVA) was performed to find out the important parameter and contribution in percentage for eachparameter on the composite material. To verify the analysis results with experimented resultconfirmation test was carried out. Further, to find the wear mechanism on the composite sampleselectron microscopy (SEM) test was used.

Abstract: Study of input factors play a vital role in controlling of process responses such as surface finish, cutting temperature, energy consumption etc. in machining process. Design of Experiment (DOE) is one such tool used by researchers to identify the key factors and levels and optimize the process.An attempt was made to identify and experiment turning of AISI 4340 steel using 6 factors viz. cutting speed, feed rate, depth of cut, MQL nozzle orientations (distance from the cutting tool-chip interface, nozzle angle) and different cutting fluid (Coolant). The response variable selected for study was surface roughness of the work-piece which needed to fit criteria smaller-the-better. L₂₅ Orthogonal Array-OA design was selected for 6 factors and 5 levels. Comparison of results of average responses of different levels of factors, analysis of variance (ANOVA) of the process is detailed. Experimental results showed that the key contributors in the turning process are due to cutting speed, feed and depth of cut covering from 12% to 40%. The major contributor to the process was the cutting speed. Selection of MQL fluids and nozzle orientation contributed to 10% showing least significance.This experiment helps us to understand the importance of machine cutting conditions as key success factors which can be assisted with MQL fluids and other input factors.

Abstract: With the requirement of the research on the stealthy aircraft’s infrared characteristic, the design and analysis have got more attention. Depend on synthesizing the main factors, include the surface IR radiation, the scatter radiation from the environment, the temperature distribution and the coat distribution of the surface, which effect the stealthy capability, a stealthy aircraft’s IR characteristic simulation model was proposed. Based on MODTRAN, the environment radiation model was built and was used in the simulation model. Finally, the proposed simulation mode was used in design and optimizing one stealthy aircraft, using combined the muti-island genetic algorithm with the sequential quadratic programming. The results of the mid-wave and long-wave radiation were got separately. These results provided considerable reference for infrared stealthy aircraft’s design.