Journal of Engineering Research and Education (JERE)

Selection of Filtration Systems to Improve the Quality of Beverage and Paste Production

2025-01-03T02:09:33+00:00

This paper presents the critical role of the selection of filtration system to be used in the beverage industry in the small medium scale production enterprises to ensure quality and consumer satisfaction as well as product competitiveness. Previously, in the small medium enterprise, tedious work is done manually to separate leaves and other contaminants for the filtration process. To maintain the quality of the beverage and paste production, the whole process must be controlled, starting with the homogenizer until the filtration process. Mildheat treatment will be applied in the homogenizer process. The selection process for filtration systems is examined in-depth, considering factors like particle size removal, preservation of flavor and nutritional components, and the prevention of spoilage. The filtration is selected according to the best type of filtration that meets the criteria of improving the quality of the production as well as reducing the manpower and processing time. The filtration will then be placed in the homogenizer unit. Ultimately, the judicious choice of filtration systems which is mesh filtration can significantly enhance the quality and it is selected based on its advantages over the other filtration systems.

Design and Development of Green Trash Compactor for Recyclable Waste Management

2025-01-03T02:40:15+00:00

A trash compactor is a mechanical device invented to reduce the volume of trash, making it suitable for use in various scenes such as domestic, public, and industries. Utilizing this kind of machine provides significant benefits in the waste accumulation system, as it allows for more efficient waste management by compacting the trash, enabling larger quantities to be collected at once. In this study, a Green Trash Compactor is designed and developed as an innovative semi-automated machine to efficiently reduce the size and volume of recyclable materials such as plastics, paper cups, and PET bottles. The project focuses on optimizing the sensor layout to minimize the impact during the compaction process, thereby reducing the requirement for heavy load cells or weight sensors. The working output is achieved by recording different input commands through buttons, where the system employs load cells to identify the detected force, and the microcontroller makes corresponding decisions. The results indicated that the Green Trash Compactor successfully operated with its mechanical and programmed codes, demonstrating impressive volume reduction during the compaction process. This substantial reduction in volume contributes to lowering transportation costs for the trash, making the compactor a highly efficient waste management solution.

Wireless Mass Air Flow Device for Thermal Comfort Data Acquisition

2025-01-03T02:45:34+00:00

This paper aims to build and implement an IoT-based mass air flow sensor device using the FS7 sensor from IST Innovative Sensor Technology and the ESP32. The scope of the project includes design and implementation of the device, the evaluation of its performance, and the presentation of the results. To achieve its objective, the project will employ literature evaluation, hardware design, programming, testing, and data analysis methodologies. The IoT-based mass air flow sensing device has the potential to improve the performance of air flow-dependent systems by providing real-time data, remote monitoring and control, and enhanced precision and dependability. In addition, it will be calibrated, maintained, and upgraded remotely, decreasing the need for on-site maintenance and extending the device's lifespan.

A Study of Heat Insulation Methods for Enhancing the Internal Temperature on Artificial Stingless Bee Hive

2025-01-03T02:49:59+00:00

The stingless bees have gained a large popularity among the beekeepers, particularly in tropical and subtropical regions such as the Americas, Africa, and Southeast Asia. This is because the honey of stingless bees has a distinct flavour and is highly valued for its medicinal qualities. Traditionally, stingless bee colonies constructed from wood logs are fragile and vulnerable to outside attacks. These predator or parasite attacks can cause Colony Collapse Disorder (CCD) if not eliminated. Thus, a PVC, 3D-printed PET-G, and acrylic artificial hive has been created to replace the old one. According to earlier research, stingless bees are especially susceptible to temperatures above 38°C. This paper's main goal is to discuss the results of studies on the best artificial hive insulation method. Over a month and a half, clay, wood powder, polystyrene, bubble aluminium foil, and a water- cooling system were tested as insulators. Results shows that artificial hives with bubble aluminium foil have the biggest average difference between internal and external temperatures (6.4°C) and are closest to traditional hives (8.6°C). The average temperature difference between the artificial hive's exterior and inside was 2.9°C without heat insulation. Clay-insulated artificial hives have the lowest standard deviation value for humidity at 0.46. Since temperature is vital to stingless bee survival, bubble aluminium foil container is the best insulation solution since it increases heat resistance more than other materials.

A Study of Embedded Fuzzy Logic to Determine Artificial Stingless Bee Hive Condition and Honey Volume

2025-01-03T03:01:02+00:00

Stingless Bee is particularly nutrient-dense in his honey. Therefore, numerous beekeepers for the Stingless Bee have begun this agricultural enterprise, particularly in Malaysia. However, beekeepers encounter challenges when caring for an excessively large stingless bee colony. Due to the risk of causing colony disruption, the beekeeper cannot always access the hives to monitor honey volume and hive condition. Consequently, the purpose of this paper is to aid beekeepers and prevent disruption to bee colonies by determining the condition of the hive and the quantity of honey using an embedded fuzzy logic system. Artificial hives have been created in order to easily measure the weight of a hive of stingless bees and to divide the honey compartment from the brood compartment in order to calculate the honey volume. Since the stingless bee designs its colony with honey on top and larvae on the bottom, honey volume can be determined by weighing the honey compartment using load cell and internal humidity using dht22. DHT22 is used for measuring the internal temperature and humidity, as previous papers have stated that the hive condition can be determined using the internal temperature and humidity. Morever, FLDa (Fuzzy Logic Designer app) by MATLAB was subsequently utilised to construct membership function, rules, fuzzification, and defuzzification. Then, the same input, membership function, and rules that used in FLDa will be implemented on the Nodemcu ESP8266 using eFLL (Embedded Fuzzy Logic Library). A comparison between the crisp output from FLDa and the crisp output from eFLL was conducted to determine whether eFLL is suitable for use in the NodeMCU ESP8266. As a consequence, the standard deviation and averaged percentage error of differences for hive condition, which is 0.22 and 0.17%, is less than the honey volume, which is 0.49 and 0.66%, because hive condition has a strict correlation with temperature. The hive condition will be rated bad (0% when the temperature is cold or hot state), but it will be rated good (100% when the temperature is normal state). As for honey volume, the majority of results correspond to the percentage of honey compartment weight, unless the humidity is dry state, which will cause the value to be cut in half. Finally, the fuzzy logic system is effectively implemented into an embedded system, making it easier for the beekeeper to monitor the hive condition and honey volume without interfering with the activity of stingless bees.

Small Metal Objects Classification Based on The Deep Learning Approach

2025-01-03T03:05:09+00:00

Classification of small metal objects plays a crucial role in various engineering fields, including manufacturing, robotics, and security. With advancements in deep learning techniques, the use of Convolutional Neural Networks (CNNs) has emerged as a powerful tool for image classification tasks. The methodology begins by collecting diverse datasets consisting of images of small metal objects. The datasets are labelled with corresponding object classes to facilitate supervised learning. Preprocessing techniques like re-sizing, normalization, and augmentation are used to improve the quality and diversity of the datasets. The use of CNNs in classification can be a better option compared to commonly used machine learning approaches. The CNN architecture is designed and trained to learn the distinguishing features of small metal objects. The main objective of this study is to assess the accuracy of this classification and explain how CNNs can enhance classification accuracy. The results of this study also show the effect of the optimizer on the classification process, which changes when different types of optimizers such as RMSprop, Adam, and SGD are used. While some optimizers yield slightly lower accuracy results, the Adam optimizer with the CNN ResNet-50 module proves suitable for use with this dataset, achieving a high classification accuracy of 86%.

Hand-Held Shelf Life Decay Detector for Non-Destructive Fruits Quality Assessment

2025-01-03T03:17:32+00:00

Perishable food such as fruits have a limited shelf life and can quickly degrade if not properly stored. One method for detecting decay in these foods is the use of ethylene gas. Ethylene is a naturally occurring hormone that is released by fruits as they ripen. By measuring the levels of ethylene in the storage area, it is possible to detect when fruits and vegetables are starting to degrade. This information can then be used to act, such as removing spoiled produce and adjusting storage conditions, to extend the shelf life of the remaining products. By utilizing ethylene gas for early detection of decay, it is possible to improve food safety and reduce food waste. The project aims to utilized ethylene gas from perishable food such as fruits before decay. This project proposed portable or hand-held detection ethylene gas by including temperature and humidity. The sensor will be measuring the level of ethylene gas, temperature and humidity. Next, machine learning method; K-Nearest Neighbour(KNN) were used to evaluate the accuracy of the proposed system. This project, a hand-held decay detector for perishable food products is believed can help to prevent food waste by detecting early signs of spoilage in fruits.

Unravelling the Magnetic Pull: Decoding Tourist Decision-Making Amidst Northeast Monsoon Floods in Terengganu

2025-01-03T03:23:56+00:00

Terengganu, situated on Peninsular Malaysia's east coast, is a renowned tourism hotspot, celebrated for its pristine beaches, vibrant marine ecosystems, rich cultural heritage, and flourishing ecotourism prospects, despite its susceptibility to monsoon floods. This study aims to investigate key factors influencing tourists' decision-making regarding travel to destinations affected by monsoon floods, using Terengganu as a case study. Through an extensive literature review, several variables have been identified, which the independent factors been assessed by utilizing a regression model. The findings reveal that five of the six independent variables exhibit p-values less than 0.05, indicating their significance in influencing tourists' decisions. These variables encompass safety assurance, information reliability, communication mediums, flood control, and promotional strategies. Notably, the factor related to flood resilience yields a p-value of 0.621, exceeding the 0.05 threshold. Consequently, the hypothesis that flood resilience plays a significant role in shaping tourists' decisions towards Terengganu is rejected. Given the paramount importance of the tourism industry in Terengganu, the analysis serves as a pivotal foundation for crafting a comprehensive model guiding tourists' decision-making processes when considering destinations susceptible to northeast monsoon floods. This model, tailored to Terengganu's unique context, directly contributes to enhancing the region's tourism sustainability.

Effects of Air Vortex Finder Length and Outlet Diameter Variations on Oil Palm Loose Fruit Collector

2024-11-22T02:55:33+00:00

Oil palm is one of the largest economy sectors in Malaysia. Among the problems faced in the estates are oil palm loose fruits deposition which is currently being collected manually in the industry. Hence, an oil palm loose fruit collector is designed using cyclone separator mechanism and was studied using computational fluid dynamics (CFD). In the current study, Reynold’s stress model (RSM) and the Discrete phase model (DPM) was employed to navigate numerical simulations where the vortex finder of the cyclone separator was varied with two factors which are the vortex finder length and outlet diameter. Wall was set to a no slip condition with standard wall functions. Hydraulic diameter of the gas outlet is B_c=0.1 . Hydraulic diameters of the particle’s outlet are J_c=0.15 and 0.2 respectively. Turbulence intensity at the gas and particles outlet are specified at 5%. An injection with density 995.7 and 0.04 was set to simulate oil palm loose fruit collection into the system. Ultimately, effects of vortex finder and outlet variations on the pressure drop and collection efficiency were then analyzed. Results indicate that an outlet diameter of 0.18 m and vortex finder length of 0.405 m is favourable for the oil palm loose fruit machine with a collection efficiency of 88.71 % and pressure drop of 477.66 Pa.

The Development and Usability of KITATORA for the Topic of Algebraic Expressions in Form 1

2025-01-03T03:31:37+00:00

This study aimed to develop KIT Tambah Tolak Algebra (KITATORA), which is designed to teach students how to add and subtract two or more algebraic expressions, according to the Secondary School Standard Curriculum (KSSM) Mathematics at Form 1 in Malaysia. The study also sought to determine the validity and usability of KITATORA. The research design used for this study was Design and Development Research (DRD). The sample for the validity of KITATORA included a mathematics lecturer from a public university and two experienced mathematics teachers. The study sample consisted of 30 Form 1 students from a school in the state of Selangor. This study used two types of instruments: the Kit Validation Assessment Form (KVAF) and the Kit Usability Survey (KUS). The validity, reliability, and usability data were analysed using Content Validity Index (CVI) calculations, Cronbach's alpha value, and interpretation of minimum scores. The study findings showed a CVI value of 1.00, a Cronbach's alpha value of 0.938, and an average minimum score of 3.83. In conclusion, this study suggests that KITATORA has satisfactory validity and usability. Therefore, teachers can use KITATORA as an alternative teaching aid for the topic of adding and subtracting two or more algebraic expressions. The educational significance of KITATORA lies in its ability to enhance students' understanding of algebraic concepts while promoting greater engagement with the subject, making algebra more accessible and enjoyable for learners.

Alternative Assessment for Enhancing Complex Problem-Solving Skills in Mechanical System Design Course

2025-01-03T03:34:19+00:00

Traditional assessment methods in engineering education, such as exam-based evaluations, often fail to adequately measure complex problem-solving skills and practical application of knowledge, necessitating the exploration of innovative assessment approaches. This paper introduces the Constructive-Teamwork-Experiential-Presentation (CTEP), an alternative assessment approach applied in the Mechanical System Design course (ENT348) for undergraduate mechanical engineering students. The CTEP model is tailored to enhance complex problem-solving (CPS) abilities and engage students in complex engineering activities (CEA). It aligns with the 2020 standards of the Engineering Accreditation Council (EAC) and the Malaysian Qualifications Framework (MQF) 2.0, specifically addressing Programme Outcomes (PO) 3 (Design) and PO10 (Communication). Over four academic terms, this model incorporated interactive design tasks, collaborative teamwork, simulation exercises, and student presentations. The findings indicate notable improvements in achieving PO3 and PO10, with average attainment rates rising to 80% and 78%, respectively. Beyond academic achievements, the model also supported the development of essential skills such as creativity, collaboration, and effective communication. Challenges related to time management and limited resources were mitigated through guided supervision and institutional backing. Future studies aim to evaluate the potential of extending the CTEP model to other engineering disciplines.

The Characterization and Development of Kenaf and Graphene Nanoplatelets in Polylactic Acid Composites

2025-01-03T03:39:04+00:00

Kenaf fiber is in high demand due to the need for lightweight composites, particularly in the automobile industry and occasionally for interior building materials. Its remarkable strength and low density are the main causes of this. The use of natural fiber as a bio-composite material is limited because it is less heat resistant compared to synthetic fiber. To bolster the mechanical robustness of kenaf composites, graphene nanoplatelets (GnP) are incorporated as a supplementary reinforcing agent. Numerous studies have explored the mechanical properties of composites made from natural fibers and polymer matrices, with the recent market introduction of polylactic acid (PLA) polymers as biodegradable matrix options for biocomposites. The objective of this study is to determine the effects of incorporating graphene fillers on the tensile and flexural properties of PLA, kenaf, GnP composites. Hot pressing compression moulding is employed to fabricate the composite samples consisting of varying compositions, ranging from 95% PLA, 5% kenaf, and 0% GnP to 80% PLA, 15% kenaf, and 5% GnP. The result shows that adding 5% Graphene Nanoplatelets as a reinforcing filler will enhance the tensile strength and tensile modulus up to 18.2% and 53.2% respectively. While the flexural strength and flexural modulus enhanced up to 46.1% and 53.2% respectively. Besides that, DSC analysis shows that adding GnT does not alter the thermal properties of the composite with a melting point of 161.5 ℃. Overall, the results confirm that the addition of graphene improves the mechanical properties of the composites. It is suggested that further research should investigate the optimal ratio of GnP, kenaf, and PLA composition in order to achieve the optimum mechanical properties so that this composite has the potential to be used in various applications.