International Journal of Integrated Engineering
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Impact of Data Source on Evapotranspiration Calculation: On-Site Vs. METMalaysia Weather Stations
Get PDFCrop water requirement is the estimation of water that needs to be replenished due to the crop evapotranspiration (ETc) by the crop. This process is critical for ensuring adequate irrigation and maximizing crop yield. In Malaysia, climate data from Malaysia Meteorological Department (METMalaysia) stations are commonly used for ETc estimation. Although these METMalaysia stations are not located directly within the plantation area, these data are easily accessible and widely utilized for ETc calculation. However, misleading climate data will result in a wrong estimation of evapotranspiration (ET), which may lead to over or under-irrigation, resulting in plant damage thus decreasing the yield. Durian (Durio zibethinus), known as the “king of fruits”, holds significant economic importance in Malaysia due to its high demand in both domestic and export markets across ASEAN countries. Understanding the ET of durian is essential for optimizing irrigation practices and enhancing crop revenue for farmers. The objective of this study is to compare ETc from climate data consisting of daily minimum and maximum temperature, humidity, wind speed, and sun radiation, obtained from on-site weather station and METMalaysia weather station. This study is conducted in a durian plantation at Durian Valley, Kluang, Johor. Data analyses were conducted using a T-test. The result shows a significant difference between calculated ETc using climate data obtained from the on-site weather station compared to data from the METMalaysia weather station which emphasizes the importance of accurate, location-specific climate data for effective irrigation management in durian cultivation
Improving the Manufacturing of Square Flange Gasket Through Lean Practices
Get PDFThis paper reports a case study on production line of square flange gasket at a small and medium-sized enterprise (SME) company. The square flange gasket, a high-demand product used as a seal between two flange faces, is currently produced below satisfactory levels due to delays, causing client dissatisfaction. This study aims to identify the root causes of waste in the production line and propose solutions to improve productivity and speed up production. The methodology used in this study is based on PDCA Cycle, starting with the ‘Plan’ approach that focuses on finding the root problems through Lean Practices such as Ishikawa, Yamazumi Chart, 5 Whys Analysis and Pareto Chart using the information gained from the Gemba visit at the company. Lean Practices revealed that the longest cycle time occurs during the quality check process due to inefficient movement between the machine room and quality check room, and the lack of quick measurement tools. ‘Do’ phase is done by developing a Go/No Go Gauge as the solution for the problems that have been identified and the ‘Check’ phase will involve the implementation of the designed gauge and monitoring the results with its function and suitability. The case study will end in the ‘Act’ phase where we make improvements based on the results during ‘Check’ phases and standardise the right practices. The proposed solution led to significant improvements: a 72.73% reduction in movement distance, a 26.29% reduction in cycle time, and a 26.47% increase in weekly production. The gauge eliminated waste like waiting time and unnecessary motion, speeding up measurements. In conclusion, this study highlights the importance of Lean practice in reducing waste and boosting overall productivity
Smart Agribot: Advanced CNN-Based Disease Detection in Green Beans with EfficientDet & Auto-Spraying
Get PDFThe Smart Agribot is a cutting-edge robotic system developed to improve how green beans are grown in the Philippines. It combines advanced technology like Convolutional Neural Networks (CNNs) for disease detection, automated spraying, and efficient crop transportation. This project aims to make farming more productive, reduce waste, and improve plant health. The Agribot\u27s physical design uses common, affordable parts like Arduino Uno, Raspberry Pi, metal frames, and wooden supports, creating a sturdy yet cost-effective machine. Its brain is a CNN model trained on a large set of images showing healthy and diseased green bean plants. This training allows the Agribot to accurately identify different plant diseases. Extensive testing confirmed that the system can reliably detect diseases, with especially high accuracy in spotting Rust, a common issue in bean crops. The Agribot’s automatic sprayer further reduces the amount of chemicals needed by only spraying plants that truly need it, which lowers costs and lessens environmental harm. Additionally, the built-in crop transporter makes harvesting faster and more efficient without significantly affecting crop yields. Together, these features make the Smart Agribot a promising tool for modern farming. It can help farmers save time, reduce costs, and improve overall productivity. As the Agribot continues to be improved, it has the potential to work with other crops and farming systems, supporting more sustainable agriculture in the future
Image Pre-processing and Quality Analysis Using Structural Similarity Indexing for Drone Applications
Get PDFThe increasing popularity of drones in mapping, surveying, and inspection processes underscores their potential in various industrial applications. Despite their widespread use, the accuracy and reliability of drone imagery for solar panel inspection have not been extensively verified. This paper introduces a novel image quality assessment method for drone applications, utilizing the Structural Similarity Indexing Method (SSIM). The proposed methodology evaluates the quality of images captured by drones, focusing on the drone\u27s positional relationship to the solar panels under diverse conditions. The study compared the quality of images with those subjected to Gaussian and Median filtering. The SSIM was employed as the primary metric to quantify the similarity between the original and processed images, providing a robust measure of image quality degradation or enhancement. In indoor tests, the SSIM values consistently decrease as the height increases from 0.7m to 2.5m for both Median and Gaussian filters. Meanwhile, outdoor tests reveal that the image achieves its highest SSIM score at a height of 1.0m for both Median and Gaussian filters. It is important to note that the Gaussian filter consistently yields slightly higher SSIM values compared to the Median filter at all heights. The SSIM analysis revealed significant insights into the optimal conditions for drone imaging in solar panel inspections. The findings of this research contribute to the development of standardized practices for drone-based inspections, ensuring high accuracy and reliability
Mathematical Modelling Concerning Compressibility of Air In Porosity During Semi-Dry Pressing Process Of Ceramic Powder
Get PDFIn this article, during the pressing of a cylindrical ceramic product from ceramic powder masses with a moisture content of 8...12%, the powder mass is considered as a model consisting of two: elastic (gas-air) and incompressible (mineral particle, water) phases. Based on this, a mathematical model was developed that depends on the initial properties of the powder mass, the allowable residual porosity in the structure of the ceramic product, and the displacement value of the punch during pressing during semi-dry pressing of the ceramic powder mass. This mathematical model allows for analytical calculations of gas-air compression level in powder pores, compressed air pressure, pressing force and pressure
Comprehensive Measurement and Analysis of Traffic Noise Along The Changlun-Kuala Perlis Highway
Get PDFRoad traffic noise, encountered by residents living close to major highway routes, has emerged as one of the most prevalent environmental concerns in recent years. Increasing noise levels result hugely from greater vehicles on the road, higher speeds, and heavier traffic volumes. However, the tire-pavement interaction often constitutes the most prominent noise source on highways. Some studies have discovered that prolonged exposure to highway noise is likely associated with hearing loss and other health problems. Notwithstanding its severity, data available on transport noise emission from highways in Malaysia is still lacking. Therefore, this study aims to analyze the traffic noise index (TNI) and noise pollution level (NPL) in dBA to assess the traffic noise impact along the Changlun-Kuala Perlis Highway, near the residential areas. Different noise indices, including equivalent continuous noise level (LAeq), maximum permissible 10% (L10) and 90% (L90) noise level, and maximum peak noise level (LAFmax) were all determined. The noise level status was also identified based on the measured noise indices to calculate the TNI and NPL. In this present study, the acoustic measurement was performed at various residential areas along the highway through the NoiSee application, which provides a readout of the noise level, using an external calibrated built-in microphone. Results revealed that all residential areas face a traffic noise disturbance with a DOE standard of more than 65 dBA, and 96% of them have TNI values higher than 74 dBA, with 70% of NPL that were below 88 dBA. As indicated by the analysis, it is clear that the residential areas along Jalan Changlun-Kuala Perlis were heavily affected by the traffic noise emitted from highways
An Innovative Water Reaction Turbine of the Ultra Z-Blade Designed for Water Conditions of Low-Head and Ultra-Low Flow
Get PDFIn comparison to conventional fossil fuels like coal and gas, hydropower offers many advantages. This is because it does not discharge harmful gases into the atmosphere, which contributes to air pollution. Nevertheless, there will be negative ecological effects in the area around a hydropower energy-producing plant if it is built. Hydropower is significantly less dangerous than pico-hydro systems, which only require a trickle of water to generate electricity through the rotation of a turbine. The reaction-type turbine is the topic of this study because it can be rotated by a relatively small amount of water. Cross pipe turbines (CPTs), split reaction turbines (SRTs), and Z-blade turbines (ZBTs) are all examples of older turbine designs that prioritized pressure above flow. There has been little progress made so far to compensate for the low head and ultra-low flow water segment. In order to tap into low head and ultra-flow water resources, this work attempts to address this by developing an ultra z-blade turbine for pico-hydro producing systems with two types of pipes measuring 0.75 inches and 2.0 inches in diameter. The concepts of mass, momentum, and energy conservation are used to generate the equations. The performance of the newly developed U-ZBT is compared to that of the well-established CPT, SRT, and ZBT via an experimental method. As a result, a 0.75-inch pipe size performed better than a 2.0-inch pipe size at a maximum speed of 130 rpm and a water flow rate of 1.77 L/sec
Dynamic Properties of Pot Bearing Via Modal Analysis
Get PDFBearings represent one of the most sensitive and demanding elements in load transfer, particularly in structural support systems, which have some of the highest requirements regarding reliability and performance in structural engineering. One widely used structural bearing is the mechanical pot bearing. This compact bearing is especially useful for transmitting large vertical loads while accommodating extensive movements and multi-directional rotation. Understanding the dynamic behavior of the pot bearing in terms of natural frequencies, mode shapes, and damping is a necessity for enhancing its design and failure limit. Since it is composed of several materials, the pot bearing exhibits complex material behavior, making the measurement of its dynamic properties challenging in real practice. Modal analysis is one of the best methods used to determine the dynamic properties of materials. Consequently, the main objective of this research is to determine the dynamic properties of the pot bearing, specifically natural frequencies, mode shapes, and damping, through numerical modeling and experimental work based on modal analysis. From the findings, the relative errors between the finite element and experimental modal analyses for the first mode are quantified at 15.29%, whereas for the second mode, the corresponding value is 10.13%. The third mode demonstrates a relative error of 9.67%, while the fourth mode exhibits the lowest relative error of 8.81%. A strong agreement in mode shape was observed between the finite element model and experimental modal analysis results. In conclusion, modal analysis proved to be an effective technique for capturing the dynamic characteristics of pot bearings. The validated numerical model offers a reliable basis for further analysis, optimization, and integration into broader structural dynamic assessments
Soft Soil Stabilisation Via Vertical Drainage with Minimal Site Disturbance: A Case Study at Cameron Highlands
Get PDFVertical drains are often adopted to improve poor ground conditions by accelerating consolidation process of soils. This paper describes a case study utilising this technique to stabilise soft soils in Cameron Highlands. This method involves the installation of vertical drains with embankment and the permeable characteristic of the prefabricated vertical drains. The details of the vertical drain design and the construction of the project were also studied. In addition, site disturbance control measures and on-site monitoring methods should be implemented to manage the impact of the construction. In summary, this paper indicates the application of the vertical drain to stabilise high-rise soft soils and recommends the construction process to provide a reference for sites with similar locations or height
Non-Destructive Method for Moisture Content Sensing Inside a Rice Storage
Get PDFRice grains represent the majority of worldwide consumed daily food, especially for most countries in Asia, where rice crops symbolize the feature of the local culture. However, as rice grains are naturally hygroscopic, the total values (quality and quantity) are degrading due to their varying level of moisture content. Currently, a sampling moisture sensing based on a single-point measurement is employed to monitor the moisture content level. In this scenario, the conventional method needs to be revised because it is very localized and only represents part of the moisture distribution inside the bulk grains. Besides, implementing several high-end technologies is considerably expensive for small-scale industries in developing countries. Therefore, this study has developed an RTI system in a prototype scale for a constructive moisture sensing method. RTI is a unique approach that reconstructs an image across the monitored WSN area by exploiting the attenuation of RF signals caused by the presence of targeted subjects. Five rice moisture profiles at the percentage of 15%, 20% and 25% were reconstructed using image reconstruction algorithms, LBP, FBP, NOSER and TR. This study analyses the effectiveness of the proposed method in both simulation and experimental studies. The results positively support the possibility of engaging the RTI technique to localize the moisture distribution in rice storage