Research Output
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PublicationReview of Control Strategies for Improving the Photovoltaic Electrical Efficiency by Hybrid Active Cooling( 2024-06-01)Photovoltaic (PV) cooling systems are used widely in order to increase the PV efficiency. Most review paper was published for the role, design and cooling techniques of PV applications, there is a lack of collected and organised information regarding the latest and the newest updates on control strategies for PV cooling control systems. Hence, this paper presents a comprehensive review of PV cooling control strategies discussing the latest research works during the years from 2010 to 2022. PV/T hybrid cooling types are highlighted, followed by the main focus of this paper an extensive review of the control schemes for diverse types of PV cooling systems that have been carried out. This paper summarises most of the related work and also pays a special focus on research trends regarding the control of PV cooling systems that have been previously published in the literature. This review paper will be helpful to new researchers when identifying research directions for this particular area of interest.
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PublicationModeling, experimental investigation and real-time control of active water cooling system for photovoltaic module( 2024-01-01)Photovoltaic (PV) cells are integral in harnessing solar energy, yet their performance is hindered by excessive heat generation, impacting efficiency and sustainability. Addressing the challenge of efficiency loss in photovoltaic (PV) cells due to overheating, this study focuses on optimizing active water cooling control for PV modules. The aim is to develop a dynamic, sustainable model and integrate a PID controller tuned by Sine Cosine Algorithm (SCA), targeting optimal operating temperatures. This study introduces a dynamic model and a closed-loop control system to manage PV cell temperature, investigating the correlation between water flow and temperature regulation. Experimental data is gathered using a pseudo-random binary sequence (PRBS) as an excitation signal, forming the foundation of an Auto Regressive eXogenous (ARX) model. The closed-loop system incorporates a PID controller and tuned using the Sine Cosine Algorithm (SCA) to optimize performance. The resulting model is rigorously validated through experimental investigation, demonstrating its precision in capturing the system’s dynamics. Moreover, the implementation of a controller-based cooling system substantiates the model’s practical efficacy. The research demonstrates significant improvements when implementing a controller-based water-cooling system for photovoltaic (PV) modules. Compared to the baseline scenario without cooling, the system achieves a 34.5% reduction in average PV temperature (from 59.2°C to 38.9°C) and a 9.46% increase in average power output (from 196.7W to 215.3W). Moreover, this system utilizes only 248.8 liters of water, marking a substantial 64% decrease in water consumption compared to traditional free-flow cooling methods, which use 790.9 liters. The research demonstrates that the controller-based cooling approach is a sustainable option, delivering power output comparable to the free-flow method, yet significantly lowering water consumption. This research signifies a turning point for sustainability, offering an efficient and water-conscious approach for enhancing PV system performance, a crucial step toward a greener and more environmentally responsible energy future.
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PublicationPower Generation Improvement using Active Water Cooling for Photovoltaic (PV) Panel( 2021-01-01)Photovoltaic (PV) cooling systems are commonly used to improve photovoltaic panels power generation and efficiency. Photovoltaic (PV) panels require irradiance to generate power, although increasing irradiance is often correlated with increasing temperature. These rapid increases of temperature in photovoltaic (PV) panels severely affect the power conversion operation. With a proper cooling process on its surface, a solar photovoltaic (PV) system can operate at a higher efficiency. This research aims to study the power improvement of active water-cooling on photovoltaic (PV) panels. A fixed minimum water flow of 5.80 l/min is sprayed onto the panel's front surface to reduce the temperature. The sprayed water created a thin water film and managed to reduce the temperature. Other than that, there is also reference photovoltaic (PV) panel, which is a panel without any cooling system. The outputs compared are the module temperature, maximum output power, open circuit voltage, and short circuit current. As the irradiance starts increasing, the panel temperature also begins to spike. However, with active water cooling, the temperature was able to be reduced by 37.67% during the day's hottest temperature. This reduction of temperature creates power improvement to the cooled panel up to 253W, compared to the reference panel output of only 223W. During the overheating of a photovoltaic (PV) panel, the open circuit voltage was found to be the most affected. This increase in power with active water cooling can potentially have a massive impact on large-scale photovoltaic (PV) panel installations.
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PublicationAddressing labour ergonomics through automation in oil palm plantation activities a necessity for sustainable agriculture( 2024)A key element of the potential of robotics is understanding how effective automation can improve labour‐intensive jobs while also considering worker ergonomics. These sectors often depend on manual labour, which exposes employees to considerable ergonomic stress, especially musculoskeletal disorders (MSDs) that can result from repetitive and physically demanding activities like harvesting, pruning, and lifting heavy items. By coordinating automation tools such as harvesters, unloaders, and driverless carts with the various manual tasks that workers perform, we can significantly lower safety risks. The main objective of introducing automation is to reduce the physical strain on workers, which not only aims to alleviate MSD‐related health problems but also helps to lessen worker fatigue. Effectively integrating artificial intelligence (AI) and big data analytics will improve workforce efficiency, making the Brightfield industry stronger. Transitioning from manual tasks to automated solutions is just the initial step toward enhancing production in this field. By tackling these ergonomic issues through automation, this paper highlights the dual advantages of promoting worker health and increasing productivity in the industry.
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PublicationOptimization of FDM process parameters to minimize surface roughness with integrated artificial neural network model and symbiotic organism search( 2022-01-01)Fused deposition modeling (FDM) has shown to be a highly beneficial process for product development. However, one of the great challenges in using FDM is maintaining the surface quality of the produced part. Poor texture quality can be regarded as a defect. It is not part of the geometric prototype but results from the fabrication process. Poor input parameters typically cause these defects by the user. This paper presents the integration between an artificial neural network (ANN) and symbiotic organism search, known as ANN–SOS, to model and minimize the surface roughness (Ra) of the FDM process. The FDM input parameters considered were layer height, print speed, print temperature, and outer shell speed. The experimental data were collected using the central composite design response surface method. Then, the surface roughness model was established using an ANN. After validating the model's accuracy, it was combined with symbiotic organism search (SOS) to determine the optimal parameter settings for the minimum surface roughness value. The results illustrate that ANN–SOS with a 4-8-8-1 network structure would be the best model for surface roughness prediction. It was observed that decreasing the layer thickness, printing speed, print temperature, and outer shell speed of the FDM input parameters for ANN–SOS resulted in minimum surface roughness of approximately 2.011 µm, which was 12.36% better than the RSM method.
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PublicationRisk evaluation on D power press operation report at D manufacturing company in Malaysia( 2021-05-03)This paper reports a case study of accidents or incident analysis in the power press machine at a press machine area in a manufacturing company. Hazard identification, cause and effect, risk level and solutions was assessed. There are total of seven hazards identified in the power press machine. These seven hazards consist of six medium level of risk and one low level of risk respectively. These listed hazards in the workplace will directly affect the worker in the view of safety and health. However, there are some solutions regarding these hazards had been proposed. By carry out some discussion, certain solution is suggested to solve the hazard in the workplace. The suggested solution shown in the HIRARC analysis can be said as simple solution which the company can conduct it successfully. It can help to reduce or solve the hazards that will protect their workers well. This will also increase their worker's productivity and comfortability in work. Pareto analysis had shown clearly with the higher risk hazards consist in the workplace that can let the company to solve the hazards with priority according to the analysis shown. Pareto analysis will help to solve the problem effectively. All these solutions suggested will only take about 2 months to solve all the hazards.
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PublicationARx modeling of flexible beam system using bat algorithm( 2021-05-03)This paper describes the development of dynamic model of flexible beam system using system identification method based on nature inspired algorithm i.e. bat algorithm. At first, input-output data from the experimental rig of flexible beam were collected such that input signal is taken from piezo actuator and output signal from the laser displacement sensor. Then, linear parametric model structure is accomplished using auto regressive with exogenous inputs (ARX). The optimal parameters of the ARX model are identified using bat algorithm. The best parameter setting estimation is selected based on the best fit criterion i.e mean square error (MSE). The identified model is compared with the model from conventional estimation approach. Simulation results show that bat algorithm can outperform the least square algorithm in parametric modelling of the flexible beam.
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PublicationOptimizing Surface Finish and Dimensional Accuracy in 3D Printed Free-Form Objects( 2023-12-18)3D printing of free-form objects presents inherent complexity due to their organic and intricate shapes. Designers engage with such objects, considering a range of factors including aesthetics, engineering viability, and ergonomic comfort. This research is focused on achieving the most effective printing parameters for a free-form object utilizing the Digital Light Processing (DLP) technique within a 3D printer. Within this study, a squeezed hexagonal tube-shaped CAD model was employed as an experimental subject, following the principles of the Response Surface Method (RSM). The model represents a free-form model that deviates from traditional geometric norms and emphasizes artistic expression and creativity. The research delved into the optimization of printing parameters, particularly layer thickness and exposure time, to enhance the dimensional accuracy and surface quality of the free-form model. Two levels were established for each factor: layer thickness was set at 0.06 mm (low) and 0.08 mm (high), while exposure time was tested at 6 s (low) and 8 s (high). The assessment of surface quality involved a qualitative evaluation employing a digital microscope to identify potential defects and imperfections in the print outcomes. The investigation culminated in the identification of the optimal printing parameters: a layer thickness of 0.0753 mm and an exposure time of 7.2143 seconds, which were interpolated from the two levels of each parameter. This achievement not only enhances the understanding of 3D printing variables in the context of intricate free-form models but also contributes to the broader field of additive manufacturing parameter optimization.
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PublicationOptimizing Fused Deposition Modeling with ANN: Material Consumption and Tensile Strength Predictions( 2023-01-01)Conventional modelling was once favored for process modelling for its straightforward nature and simplicity. However, conventional modelling is incapable of modelling complex processes such as fused deposition modelling (FDM). This study aims to model an accurate FDM process using an artificial neural network (ANN) to predict material consumption and tensile strength based on layer height, infill density, printing temperature and printing speed. The design of the experiment (DOE) was constructed using face-centered central composite design (FCCCD) yielding a total of 78 specimens. The material consumption was measured by weighting the specimen using a densimeter while the tensile strength of the specimen was tested using a universal testing machine (UTM). Best ANN structures were first identified in a trained network before being modelled for comparison. Models were compared using the lowest mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and highest coefficient of determination (R2). The best predictive model structure for material consumption is 4-19-14-1 with the lowest MSE of 0.00096 while the best predictive model structure for tensile strength is 4-16-15-12-1 with the lowest MSE of 0.005274145.
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PublicationElektronik asas : untuk pelajar mekanikal( 2015)Buku ini mengandungi lapan (8) bab kesemuanya di mana ia telah disusun dan mencakupi bab-bab asas yang penting untuk membentuk satu ilmu asas Teknologi Elektrik yang lengkap untuk para pelajar Kejuruteraan Mekanikal. Antara bab-bab tersebut ialah, Asas Kejuruteraan Elektrik, Litar Arus Terus, Litar Arus Ulang-alik, Sistem Tiga Fasa, Elektromagnetik, Pengubah, Mesin Arus Terus dan Mesin Pearuh Tiga Fasa. Di samping itu, buku ini juga diharapkan dapat menjadi rujukan para pelajar dari politeknik khasnya dan institusi pengajian tinggi amnya kerana bilangan buku-buku rujukan yang terdapat dalam Bahasa Melayu adalah terhad. Dalam usaha untuk menambah bilangan buku-buku rujukan yang ditulis dalam Bahasa Melayu, penghasilan buku ini diharapkan dapat membantu pelajar Kejuruteraan khususnya Kejuruteraan Mekanikal untuk lebih memahami dan menguasai Asas Teknologi Elektrik.
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