International Journal of Integrated Engineering
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Experimental Analysis of Friction Stir Welding of Dissimilar Aluminium Alloys by Machine Learning
Get PDFThis research focusses on joining of dissimilar materials on AA5083 and AA6082 using friction stir welding process. Tool rotation speed, welding speed and tool tilt angle are optimized using L27 Orthogonal design of experiments with tensile strength as the response. To evaluate potential of sophisticated machine learning methodologies, random forest regressor and artificial neural network algorithms are utilized for predicting the joint strength of friction stir welded dissimilar plates of AA5083 and AA6082. These models are used to investigate discrepancies between experimental and predicted results. Of the available results, 21 readings are chosen for training the model while remaining are used for testing the model. Random forest regressor and artificial neural network techniques were formed using the data associated with the experiment. Moreover, results of the analysis of variances are compared to the machine learning predicted results to determine the variances
An Improved Framework for Managing Uncertainties in Vehicle Recycling: A Case Study in Malaysian Automotive Treatment Facilities
No full textThe legislation for end-of-life vehicles (ELV) is anticipated to be fully enforced, and public awareness is likely to grow over the next few years, assuring the profitability of Malaysia’s ELV recycling enterprises in the future. However, the current state of ELV recycling operations is fraught with uncertainty, which has hampered this industry’s expansion. Thus, this study aims to identify critical uncertainties and provide suitable strategies to mitigate these uncertainties. A case study of multiple automotive treatment facilities (ATFs) in Malaysia was employed to conduct this study. A structured questionnaire comprising both closed-ended and open-ended questions was provided to Malaysian ATFs, and site observations were conducted to investigate the ATFs\u27 production settings. Cross-case synthesis was utilised to compare the cases studied. Meanwhile, the closed-ended questions are assessed on a five-point Likert scale, and the responses were analysed with ATF to conduct the descriptive analysis. As a result, a cross-case synthesis between the ATFs was presented and the uncertainties in ELV recycling operation were identified, consisting of ELV supply (M = 4.250), ELV recycling costs (M = 4.188), ATF infrastructure (M = 4.125), production planning (M = 3.875), ELV characteristics (M = 3.550), and ELV distribution network (M = 2.833). In addition, a conceptual framework for improving the ELV dismantling system in Malaysia’s ATF was proposed. The novelty of this study is a detailed analysis of existing uncertainties in ELV recycling operation in the Malaysian context and an improved framework to enhance the ELV dismantling system for ATFs in Malaysia
Assessment Wind Energy in the Cental Region of Thailand
Get PDFThis study assesses the potential of wind energy resources in central Thailand using data from seven wind measurement stations (Ayutthaya, Bang Na, Chai Nat, Kampaeng Saen, Lop Buri, Nakorn Sawan, and Pathum Thani) and two wind turbine models, namely AN Bonus 1300/62 and Vestas Wind System A/S. The analysis is conducted using the Wind Atlas Analysis and Application Program (WAsP) to examine wind speed data collected over a three-year period at the seven stations. The objective is to identify the top three areas with the highest Annual Energy Production (AEP). Additionally, the study includes an economic analysis, employing metrics such as Present Value of Cost (PVC), Benefit Cost ratio (BCR), Payback Period (PBP), and Levelized Cost of Electricity (LCOE). The results indicate that the AN Bonus 1300/62 model offers greater cost-effectiveness in areas with high wind speeds and relatively high electricity demand. On the other hand, the Vestas V52 model is more suitable for areas with lower wind speeds and lower investment requirements. Based on these findings, the authors recommend prioritizing wind power development in Ayutthaya, Nakorn Sawan, and Lop Buri, using the AN Bonus 1300/62 model, as these areas exhibit high wind speeds and relatively high electricity demand.Overall, this research provides valuable insights for policymakers and investors, enabling them to make well-informed decisions regarding renewable energy investments in Thailand
Non-Linear Modelling and Control of Permanent Magnet Synchronous Machine for Actuator Applications
Get PDFPermanent magnet synchronous motors grabbed the attention due to their intrinsic characteristics. Aerospace applications necessitate great dependability and while reducing weight, complication, fuel intake, working expenses, and environmental effects. All these demands can be fulfilled to some extent with the PMSM motors because of their characteristics. The mathematical modelling of an Interior permanent magnet synchronous motor (IPMSM) including nonlinearities is proposed in this paper. The conventional models neglect nonlinearities such as hysteresis and eddy current losses, parameters variation with respect to rotor angle, magnetic saturation, cross-coupling effect, armature reaction, etc. The present model considers core loss and inductance varying concerning rotor position. Usually, the core loss is taken as a constant loss, but it varies with the speed. Ignoring the above parameters may deteriorate the performance of the motor in real-time compared to linear model. To validate the efficacy of the proposed model, two models are simulated in MATLAB and the results are compared
Patient-Specific Design of Prosthesis for Below Knee Amputee: Analysis Between Different Gait
Get PDFMajor that often associated with prosthetic leg are poor comfort and high cost. The study is conducted to construct custom-made passive below knee prosthesis and to analyse the response to applied load in different gait condition. The scope of the study is the utilization of three-dimensional printing material, acrylonitrile butadiene styrene (ABS) in the manufacturing of prosthetic leg socket and pylon whereas the foot made from polyurethane. By using the Sense three-dimensional scanner, the subject\u27s residual leg was scanned. SolidWorks and Meshmixer were the software used for the three-dimensional designing of prosthetic leg parts. By using 3-Matic, aligning and meshing were carried out. von Mises stress and displacement of model applied with axial load were obtained from simulation using Marc Mentat. The load applied for midstance, heel strike and toe off phases were 350 N, 1545 N and 2450 N, respectively. The constraints position was different for each phase. The peak stress of the model was reported during toe off (20.86 MPa) followed by heel strike (13.41 MPa) and midstance (4.89 MPa). The stress during all three phases not exceeding the yield of respective materials. In displacement, the model experience highest displacement (54.95 MPa) during toe off and the lowest during midstance (6 mm). In conclusion prosthetic leg with ABS components shows acceptable durability during different gait
Prediction of Storm Surges in the East Coast of Peninsular Malaysia in Response to Climate Change
Get PDFThis study employed the MIKE 21HD modeling framework, integrating data from the future climate database, "Policy Decision Making for Future Climate Change (d4PDF)" on selected critical ensembles to investigate the impact of climate change on storm surge height (SSH) along the East Coast of Peninsular Malaysia during the Northeast Monsoon season. Three scenarios, including past-historical data, future climate with a 2°C increment (+2K), and future climate with a 4°C increment (+4K), were analyzed. The study had validated model accuracy through root mean square error (RMSE), demonstrating alignment with observed data. Results indicated a correlation between temperature increase and storm surge height (SSH), with higher temperature scenarios leading to more severe surge outcomes. The analysis identified the Future +4K scenarios as yielding the most critical SSH across all stations, with recorded SSH at Kuala Pahang (SSHmax = 1.379 m), Chendering (SSHmax = 1.344 m), Geting (SSHmax = 1.251 m), and Tanjung Sedili (SSHmax = 1.251 m) stations. Considering the findings, it was recommended to reassess the baseline provision for coastal engineering projects, suggesting a storm surge resilience design exceeding the observed maximum. The utilization of d4PDF data in this study laid the groundwork for targeted strategies to mitigate the impacts of climate-induced storm surges in vulnerable coastal regions
An Experimental Investigation on Effect of B4C/CeO2 Reinforcements on Mechanical, Fracture Surface and Wear Characteristics in Al7075 Hybrid Metal Matrix Composites
Get PDFStircasting method is commonly used to efficiently produce high-grade Metal Matrix Composites (MMCs). In the current study, we produced hybrid materials by altering the weight percentages of B4C, which were 2%, 4%, 6%, and 8%, while maintaining a constant weight percentage of 5% for Cenosphere. Following that, we performed examinations of microstructure, hardness, and tensile properties on both the as-cast materials and the hybrid composites. The microstructural analysis unveiled a consistent dispersion of reinforced particles throughout the base matrix, which was observed in both the as-cast and hybrid composite samples. Highest hardness of 86.55 VHN is achieved for the 8% B4C + 5% cenosphere reinforced MMCs. The maximum tensile strength of 180.58 MPa is obtained for 6% B4C + 5% cenosphere reinforced MMCs. Minimum wear loss is observed in the 6% B4C + 5% cenosphere reinforced MMCs. The ductility of the hybrid composite is decreased as the amount of reinforcement was increased. The tensile fractured sample shows the voids, micro-cracks and particles pullouts. It indicates the strong adhesion between the reinforcements and the matrix material, with bonding influenced by the reinforcement geometry and grain size. The wornout surfaces of the as-cast show the deep grooves, delamination and ploughs on the wear directions. However, hybrid MMCs micro-graphs indicate the deep grooves, particles pullouts and voids in the wear directions. It is due to the high hard reinforcement’s presence in the matrix and resists wear of MMCs
Effect of Process Parameters on the Tensile Strength of the Developed Composite of Al 6065 in Stir Casting Process
Get PDFThere are numerous techniques for producing metal matrix composites (MMC) like infiltration, stir casting process, sinter-forging, diffusion bonding, etc. The stir casting process is amongst the most known techniques to synthesize MMC. In the current study, an agro-based MMC is prepared by stir casting process using waste eggshell and rice husk as primary and secondary reinforcements and Al 6065 as base material. Process parameters (PP) significantly impact the tensile strength of the finally prepared composite. The major factors also called process parameters in the stir casting process that have a determining impact on the tensile strength of hybrid MMC are temperature and the speed of stirring, duration of stirring, and temperature at which the reinforcement is allowed to be poured. The primary aim behind the current work is to evaluate the optimal values of process parameters in the friction stir casting process. 9 separate samples have been prepared at different Process Parameter for analyzing the tensile strength of the composite and these samples were machined as per the ASTM standards for performing the test of tensile strength. It was concluded that the maximum tensile strength value was found at a stirring speed of 320 rpm, the optimal stirring temperature was 630? and the time of stirring was 25 minutes. At these values of PP, the tensile strength of the prepared composite was improved by 35% in contrast to that of the base material
Design and Implementation of Fuzzy-based Fine-tuning PID Controller for Programmable Logic Controller
Get PDFThe Proportional-Integral-Derivative (PID) controller, already known for its stability, is widely used in industrial applications and integrated into many Programmable Logic Controllers (PLCs). However, most PLCs do not support the self-tuning mechanism for PID controller parameters. Therefore, users must manually adjust several times to achieve the desired outcomes. This manual adjustment is time-consuming and must be repeated as control object parameters change over time. This study proposed a fine-tuning mechanism for the PID controller’s parameters based on a fuzzy-PD controller. The mechanism was designed and simulated using MATLAB/Simulink on an identified plant, then converted into a Structured Control Language (SCL) code for implementation on the PLC programs. Experimental results on the Siemens S7-1200 PLC demonstrated the proposed mechanism’s effectiveness in stabilizing the thermal plant by adjusting the initial parameters of the integrated PID controller. The system response was more stable, and the overshoot was minimized in comparison with the built-in auto-tuning feature on the S7-1200. Specifically, overshoot decreased to 0.79% from 0.94%, and the setting error declined to 0.1 °C from 0.45 °C. The above results indicate the effectiveness of the proposed self-tuning mechanism when used to improve the quality of PID controllers in PLCs. In addition, due to its ability to self-tuning parameters, it helps users reduce the time required to design PID controllers
Artificial Intelligence-Based Classification of Multipath Types for Vehicular Localization in Dense Environments
Get PDFMultipath-geometry is the most promising approach for vehicular localization in line of sight (LOS) and non-line of sight (NLOS) scenarios. In such approach, identifying the type of the propagated multipath (MP) is an important pre-required process. However, identifying the type of the MP in dense multipath environments is challenging. The previous works proposed iterative methods for this task. The iterative methods have their limitations such as required more in-depth analysis and high complexity of computation. However, leveraging artificial intelligence advantages, a lower complexity identification method is proposed in this work. We utilized supervised learning algorithms to distinguish the direct link, first-order, and higher-order MPs of millimeter-Wave Vehicle-to-Infrastructure communication. In particular, four models namely KNN, and SVM, MLP, and LSTM have been applied. The characteristics of the received signal paths including received signal strength and elevation and azimuth angle of arrival are considered as features of the training dataset. The results showed that the accuracy rates of the classification are ranged between 96.70% and 84.0%. The best accuracy rate was 96.70% obtained by LSTM, followed by 94.47 % obtained by MLP. Whereas, 93.67% and 84.0% accuracy rats were achieved by KNN and SVM respectively