Engineering Journal (Faculty of Engineering, Chulalongkorn University, Bangkok)
Not a member yet
1223 research outputs found
Sort by
Compressive Behaviors of Hydrophobic Sheets Using Finite Element Analysis
Get PDFThai Microelectronics Centre (TMEC) used soft lithography techniques to fabricate hydrophobic sheets made of PDMS material for various micropillar patterns. The F8 and F13 micropatterns had high water contact angle and resisted high compressive load on top of hydrophobic sheets [17]. This research aimed to reinvestigate for truly understanding compressive behavior of these micropillar patterns under compressive loading. The finite element models of F8 and F13 micropatterns were constructed in Ansys APDL 2019R3 software. The accurate material model for PDMS under compressive loading was Ogden 3rd parameter material model as discussed in [13]. We introduce a novel mathematical technique implemented in MATLAB R2021a software. This technique aims to ascertain material constants and their associated stability regions. While the proposed method for determining material constants is deemed innovative and intriguing. Finally, uniform compressive load as a function of vertical deformation was found for each micropillar pattern. We found that load-deflection curves were stiffer than previous study discussed in [17] since we had no strain limit range in our study. Finally, the maximum uniform compressive loads, before the initial collapse of micropillar patterns, were 34.334 kPa and 16.694 kPa for F8 and F13 micropatterns respectively
Diabetic Retinopathy Classification: Performance Evaluation of Pre-trained Lightweight CNN using Imbalance Dataset
Get PDFDiabetic Retinopathy (DR) is an eye complication that arises from long-term diabetes and damages the retinal blood vessels. Various clinical studies claim that Diabetic retinopathy infects about eighty percent of patients who suffer from diabetes type 1 for the last 15 years and a hundred percent of patients with this disease for 20 years. The human evaluation method is challenging but useful because it can detect diseases by the presence of lesions associated with Diabetic Retinopathy in most cases, but it is also time-consuming, erroneous, and requires a sophisticated medical setup. An efficient and automatic Diabetic Retinopathy identification method is still a challenging task. The feature extraction part is a very significant part and plays a vital role in the automatic Diabetic Retinopathy identification system. CNN has demonstrated its efficiency in medical image classification tasks as compared to other neural networks and traditional image processing methods. In this study, two lightweight CNN models: MobileNet and MobileNetV2 are used via transfer learning for binary (2-class) and multiclass (5-class) Diabetic Retinopathy classification using the DDR dataset, which is highly imbalanced. The efficiency of the models is measured using accuracy, precision, recall, and F1-score values. The ROC curve is generated for both models in binary and multiclass classification. The MobileNet model performed slightly better than MobilenetV2 in Diabetic Retinopathy classification for binary and multiclass classification. MobileNet shows 80% and 71% accuracy whereas MobileNetV2 shows 79% and 69% in binary and multiclass classification, respectively
The Effect of Pyrolysis Temperature on Sawdust-Biomass Activated Carbon Using NaOH and NaCl Activators
Get PDFThe biomass pyrolysis refers to the process of heating and degradation of biomass to promising sustainable energy production. For our study, we selected the pyrolysis process to compose the biomass. Pyrolysis reactor (PR) was carried out to process carbonation of sawdust using activated carbon. The yield from this sawmill ranges from 20–40% of the volume of logs, depending on the diameter of the logs being sawed. Sawdust is put into the pyrolysis reactor, and pyrolysis is carried out at temperatures of 300, 325, 350, and 375 °C for 1 hour. The pyrolysis product, in the form of carbonated sawdust biomass, is produced using the activators NaOH and NaCl through an activation process. The adsorbent was then filtered, neutralized, and set at 110 °C for 3 hours. Based on the research that has been carried out, the quality of activated carbon is affected by increasing the pyrolysis temperature. Activation with 15% NaOH increases bound carbon levels, similar to 35% NaCl, but 35% NaCl causes a decrease in fixed carbon levels at 400 °C. Activation with 15% NaOH produces a pore morphology with the largest pore size of 7.17 μm, while activation with 35% NaCl produces activated carbon with impurities at a pore size of 7.80 μm. Study results can form the basis for obtaining fuel, chemicals, and environmental improvements
An Evaluation of the Accuracy of GNSS Receivers Integrated with MEMS-IMU Sensors for Optimal Angle Determination in Tilted Observation Scenarios Using the NRTK GNSS Technique in Thailand
Get PDFThis paper evaluates the performance and accuracy of GNSS receivers integrated with MEMS-IMU sensors for optimal angle determination in tilted observation scenarios within obstructed environments. Utilizing the Network-based RTK (NRTK) GNSS technique, two GNSS receiver brands, Tersus Oscar (OS) and e-Survey E600, were tested at various tilt angles, ranging from 0° to 60°, at specific locations on the rooftop of the Engineering Building at Chulalongkorn University, Bangkok, Thailand. These test points included open areas and obstructed positions, such as corners and doors, where satellite visibility is reduced. The study assesses the Root Mean Square Error (RMSE) in both horizontal and vertical positions, as well as the Position Dilution of Precision (PDOP). Results indicate that horizontal accuracy decreases with increased tilt angles in obstructed environments, with the 'Door' point showing the highest errors due to significant obstructions. Conversely, 'Corner right' consistently demonstrates superior accuracy across all conditions. The integration of tilt-compensation technology is shown to improve positioning precision, especially in challenging environments where physical obstructions affect satellite signal reception. This research provides valuable insights for improving the accuracy of GNSS-based cadastral surveys and other high-precision applications in obstructed environments
High-Density Polyethylene Film Price Forecast in Southeast Asia Market with Deep Learning
Get PDFNeural networks (NN) have been used for over a decade to predict time series data, with various algorithms including linear and non-linear models. Forecasting and assessing polymer market prices are crucial for plastic resin producers due to the complexity and uncertainty of resource availability. This encompasses feedstock planning, raw material procurement, technological advancements for product transitions, sales planning, pricing strategies for commercialization, and investments driven by macroeconomic factors. Previous literature primarily utilized numerical data as input for deep learning models. This research contended that structured data by itself was inadequate for models to precisely predict outcomes in the volatile, uncertain, complex, and ambiguous (VUCA) environment. Three deep learning architectures, Long-Short Term Memory (LSTM), Encoder-Decoder, Temporal Convolutional Network and Recurrent Neuron Network (TCNRNN), were reviewed in this research to determine the most effective architecture for analysing structured data. Additionally, Natural Language Processing (NLP) was implemented in this research to gather market sentiment and enhance forecast accuracy. The study utilizes commodity market price announcements, economic indicators, and insight reports from reputable publishers. The study utilizes commodity market prices, economic indicators, and insightful reports. All information was obtained from a reputable publisher. The results were compared with the legacy model, which involved a human analyst and a linear regression model. Model performance was assessed using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Symmetric Mean Absolute Percentage Error (SMAPE), and ANOVA. The linear regression forecast together with the human analyst model has an acceptable accuracy with a MAPE of 45.1%. Neural networks containing sentiment analyzers have been found to surpass the performance of human analysts and a linear regression model, with a MAPE of 17.1%
Cost-Effective IIoT Gateway Development Using ESP32 for Industrial Applications
Get PDFThe Industrial Internet of Things (IIoT) connects industrial devices, such as measuring equipment and production line machines, to the Cloud system via the internet, creating a database for equipment data storage and performance analysis. Implementing an IIoT system requires an IIoT Gateway to interface with industrial controllers using protocols like Modbus TCP/IP or OPC UA, enabling data transmission to the Cloud. These Gateways, often produced by PLC manufacturers, are typically expensive. This research investigates using an ESP32 microcontroller as a cost-effective alternative to the Simatic IOT2050 IIoT Gateway. The study focuses on connecting the Siemens Simatic S7-1200 12144C AC/DC/RLY PLC via Modbus TCP/IP and facilitating data transmission between cloud systems using MQTT and REST API protocols. Results show that the IIoT Gateway's response time for writing 16-bit payload data to the PLC via Modbus TCP/IP averages 0.0591 seconds. Additionally, the device supports data scaling from 16-bit Integer to 32-bit Float for Modbus TCP/IP communication and converting 32-bit Float data to Message data for transmission via MQTT to ThingSpeak Cloud and REST APIs to Blynk Cloud. This approach offers a viable, cost-effective solution for IIoT implementations
Operational Process Improvement for Outpatient Services at a Private Medium-Sized Hospital
Get PDFThis study is dedicated to enhancing the efficiency and efficacy of a medium-sized community hospital's services, which have limited space and experience a high volume of visits from diverse patient types with distinct service processes. The hospital challenges meeting the waiting time Key Performance Indicator (KPI) primarily from internal factors. The research methodology involves a comprehensive approach, encompassing the collection of qualitative and quantitative data, interviews with hospital staff, on-site observations, and a detailed examination of processing times at each step within the outpatient department. Upon data analysis, the study identifies and categorises key issues within the current Outpatient Department (OPD). These issues are encapsulated in three main categories, i.e., the unavailability of doctors during critical periods, insufficient staff for document delivery, and ineffective communication. Addressing the imperative of minimising patient system dwell time, a key competitive objective in the healthcare sector, this article is dedicated to identifying and implementing tools within a Lean framework. Tools such as root cause analysis, Poka-Yoke, and visual control are identified and implemented to optimise outpatient operations. Using simulation software, quantitative data is utilised to simulate and evaluate the outpatient process. The simulation results underscore significant periods during which doctors are absent, and an imbalance in workforce distribution emerges as a bottleneck. From a Lean perspective, recommendations are formulated to address these issues, emphasising the need for schedule balancing and minimising batch size through a proposed document method. The efficacy of these recommendations is subsequently validated using the simulation models. Through a series of optimisations and experiments, the average time in the system of social security patients has demonstrated a noteworthy reduction from 1,999 seconds to 1,820 seconds, reflecting an 8% improvement
Theoretical Study of Flexible Guided Mode Resonance Formed by Embedding Silver Nanoparticles in the Polymer Matrix for Strain Sensing Applications
Get PDFThis paper presents a theoretical analysis of flexible guided mode resonance (GMR) structure with a configuration of an enhanced refractive index polymer nanocomposite with silver nanoparticles coated on top of a casted or imprinted grating made of the original polymer. Controlling both the volume fraction of the embedded nanoparticles (NPs) and the film thickness tunes the device sensitivity for application in mechanical lateral strain detection. The work introduces the use of the scattering matrix method (SMM) with a modification in the effective index to accurately predict the resonance wavelength peak. The results show a good agreement with rigorous coupled waves analysis (RCWA) particularly for the phase matching condition between the fundamental guided mode and diffraction. The sensitivity is calculated by perturbing the grating period due to lateral strain and correlating it to the produced wavelength shift. Using SMM for resonance wavelength calculation reduces the computational cost by a factor of 144 times while keeping a good agreement with both RCWA and the finite difference frequency domain method (FDFDM)
A Review of Challenges and Opportunities in BIM Adoption for Construction Project Management
Get PDFThis research investigates the transformative impact of Building Information Modeling (BIM) on construction project management, highlighting its potential to enhance traditional processes through digital innovation. As the construction industry evolves amidst global economic integration and heightened competition, the demand for quality, efficiency, and sustainability escalates, presenting new challenges for project managers. Traditional management practices, while foundational, lack the dynamism and integrative capabilities offered by BIM technology. BIM emerges as a revolutionary paradigm, facilitating a shared digital environment that promotes precision, efficiency, and improved collaboration across the project lifecycle. By integrating BIM with artificial intelligence (AI), this study explores novel synergies that further refine project management methodologies, addressing complex challenges in the design, execution, and maintenance phases. The research employs a comprehensive review of existing literature, case studies, and practical applications to assess the effectiveness of BIM in various project management contexts. The findings reveal that while BIM significantly enhances project outcomes, its adoption faces technological, organizational, and cultural barriers. This necessitates a comprehensive strategy encompassing innovation, education, and policy reform to unlock its full potential. The study underscores the critical role of BIM in driving the future of construction project management, advocating for a collaborative effort among industry stakeholders to foster a conducive environment for BIM adoption and leverage its benefits for sustainable development in the construction sector
Optimization of Forming Process Parameters for Automotive Advanced High Strength Steel Parts Using the Taguchi Method
Get PDFThis paper presents a comparative analysis between finite element simulation results and actual formed parts, utilizing different material model combinations. The Bow-RF panel part made from JSC980Y advanced high strength steel was chosen as a case study and investigated by using the finite element method (FEM). The comparison revealed that the combination of the Barlat 1989 yield criterion and the Yoshida-Uemori hardening rule in the finite element simulation gave the best predicted result of the panel part during the drawing process. This combination achieved the highest percentage of area in the displacement range of -1 to 1 mm (approximately 83.17%). Subsequently, Taguchi's Design of Experiments (DOE) and Analysis of Variance (ANOVA) were employed to analyze the influence of each process parameter on the simulation results, including blank holder force, die gap, and blank width. Finally, a statistical mathematical model was created using regression analysis. The results indicated that the most influential parameters, in decreasing order of significance, were die gap, blank holder force, and blank width. The optimal process parameters for achieving the highest percentage of area in the displacement range within -1 to 1 mm were determined to be a blank holder force of 41.21 tons, a die gap of 0.9 mm, and a blank width of 297.47 mm