https://ph01.tci-thaijo.org/index.php/lej/issue/feed Engineering and Technology Horizons 2025-06-25T13:51:12+07:00 Prof. Dr. Uma Seeboonruang kmitl.eng.jnl@gmail.com Open Journal Systems <p><em>Engineering and Technology Horizons</em> (ETH), formerly known as Ladkrabang Engineering Journal, is an academic refereed journal organized by the School of Engineering, King Mongkut's Institute of Technology Ladkrabang (KMITL) in Thailand. ETH is an open-access scientific journal that focuses explicitly on publishing original academic and research articles related to engineering and technology. The journal provides a platform for researchers, scientists, and academicians to share their knowledge and ideas with the broader scientific community through online publications.</p> <p><strong>Journal Abbreviation: </strong>Eng. &amp; Technol. Horiz.</p> <p><strong>ISSN: </strong>2985-1688 (Online)</p> <p><strong>Starting Year: </strong>1983</p> <p><strong>Language: </strong>English</p> <h3><strong>Aims</strong></h3> <p>Engineering and Technology Horizons strives to advance the field of engineering and technology through theoretical and practical approaches. The journal's aims include:</p> <ul> <li>To publish high-quality articles on engineering and technology, both nationally and internationally.</li> <li>To serve as a platform for exchanging research results and knowledge in engineering and technology among students, researchers, and teachers.</li> <li>To become a repository of valuable academic research articles in engineering and technology.</li> </ul> <h3><strong>Scope of the Journal</strong></h3> <p>Articles that are suitable for publication should be related to the field of engineering and technology. This includes research reports the author has experimented with, created, or directly participated in. The published article should present a new idea or principle that is supported by adequate theoretical evidence. It should also be an interesting and useful academic article for students and researchers. It is essential to note that the authors must have played a direct role in or organized the majority of the article. The journal covers the fields of engineering and technology as follows:</p> <ul> <li>Civil engineering, environmental engineering, and engineering related to architecture</li> <li>Electrical engineering, electronic engineering, and computer engineering</li> <li>Chemical engineering and petroleum engineering</li> <li>Agricultural engineering and food engineering</li> <li>Industrial engineering, management engineering, and production engineering</li> <li>Telecommunication engineering and information engineering</li> <li>Mechanical engineering, rail engineering, and mechatronic engineering</li> <li>Measurement and control engineering</li> <li>Biomedical engineering.</li> </ul> <h3><strong>Type of Article</strong></h3> <p>ETH accepts two types of articles: research and academic articles.</p> <ul> <li><strong>Research article: </strong>A research article is a document with a form of research according to academic principles; for example, there is a hypothesis or a reasonably identified problem. In addition, it must clearly state objectives, systematic research, collect data for consideration, analysis, interpretation, and conclusion of research that can provide answers to certain objectives or principles that will lead to academic advancement or practical application.</li> <li><strong>Academic article:</strong> An academic article is written in the manner of analyzing, criticizing, or proposing new ideas from an academic basis that has been compiled from the academic work of one's own or that of others, or an academic article written for general knowledge for the public.</li> </ul> <p>Manuscripts submitted to the journal must not have been previously published or under consideration elsewhere. Researchers must follow the highest standards of scientific integrity while submitting manuscripts, ensuring that their research is ethical and rigorous. Manuscripts presenting innovative and original research and contributing to developing new theories, methodologies, and techniques are encouraged.</p> <h3><strong>Language</strong></h3> <p>All submissions must be in clear and concise English with proper grammar and correct spelling.</p> <h3><strong>Peer Review</strong></h3> <p>The articles will undergo a double-blind review process by at least three experts. This ensures that the reviewers' comments are academically sound and their recommendations are helpful to the authors.</p> <h3><strong>Publication Frequency</strong></h3> <p>The journal is published every three months, with four issues per year. </p> <ul> <li><strong>Issue 1:</strong> January - March</li> <li><strong>Issue 2:</strong> April - June</li> <li><strong>Issue 3:</strong> July - September</li> <li><strong>Issue 4:</strong> October - December</li> </ul> <h3><strong>Publication fee</strong></h3> <p>Publication is free of charge as all costs are covered by the School of Engineering, King Mongkut's Institute of Technology Ladkrabang.</p> <p> </p> <h2>Policy</h2> <h3><strong>Editorial Policy </strong></h3> <p>Independent reviewers will evaluate academic and research articles for publication. The articles must include substantial supported theories, innovative work, substantial experimental results, useful and constructive discussions, and academic articles in the fields of engineering and technology. An electronic journal is available on the website (<a href="https://ph01.tci-thaijo.org/index.php/lej/">https://ph01.tci-thaijo.org/index.php/lej/</a>). The Editors have the right to request revisions to the submitted manuscript before it is finally accepted. The institute and the editorial board do not take responsibility for the views or content expressed by the authors of individual articles. Acknowledgment is required for any copying.</p> <h3><strong>Open Access and Archiving Policies</strong></h3> <p>This journal promotes the global exchange of ideas and knowledge by providing open access to its research content.</p> <p>The Engineering and Technology Horizons journal's articles are available on Thailand's central electronic journal database, Thai Journal Online (ThaiJO). You can access all the published articles for free from the archives section on their website (<a href="https://ph01.tci-thaijo.org/index.php/lej/issue/archive">https://ph01.tci-thaijo.org/index.php/lej/issue/archive</a>). The authors hold the copyright of their articles, and they are permitted to self-archive their articles in PDF format.</p> <h3><strong>Publication Fee Policy</strong></h3> <p>The Engineering and Technology Horizons journal is an open access publication founded by the School of Engineering, King Mongkut's Institute of Technology Ladkrabang in Thailand. Its purpose is to publish high-quality academic and research articles on engineering and technology. The journal is open to anyone whose research work meets the editorial board's criteria, and there are no page charges for submissions. The School of Engineering fully covers the cost of publication.</p> <h3><strong>Peer-reviewed Policy</strong></h3> <p>Manuscripts submitted to Engineering and Technology Horizons undergo editorial and peer review. Editors assess whether a manuscript is technically sound and scientifically valid before sending it for double-blind peer review. Authors can suggest peer reviewers in the ETH article <a href="https://ph01.tci-thaijo.org/index.php/lej/libraryFiles/downloadPublic/967">submission form</a>, but the Editor's decision is final. Authors should not recommend recent collaborators or colleagues from the same institution. If an Editor has competing interests, another member will oversee peer review. Authors should include copies of related papers with their submission.</p> <p> </p> <h2>Management</h2> <h3><strong>Ownership</strong></h3> <p>The School of Engineering at KMITL is the rightful owner of the Engineering and Technology Horizons journal. The school provides all necessary facilities to ensure the journal maintains its high publication standards, rigorous peer-review process, and open-access availability to researchers and readers worldwide. The Office of Academic Journal Administration, under the President's Office, has been assigned to oversee the overall management of the journal, in line with the School of Engineering's vision. For further information about the School of Engineering, KMITL, please visit <a href="https://engineer.kmitl.ac.th/">https://engineer.kmitl.ac.th/</a>.</p> <h3><strong>Copyright and Licensing</strong></h3> <p>Engineering and Technology Horizons values copyright protection and licensing to secure the author’s rights. We publish articles under a Creative Commons Attribution License (CC BY), which allows sharing, adaptation, and proper attribution, while authors retain copyright ownership. This fosters openness, accessibility, and responsible sharing, benefiting authors and the research community while honoring intellectual property rights.</p> <h3><strong>Revenue Source</strong></h3> <p>The School of Engineering at KMITL is the primary revenue source for the journal, which is utilized to sustain its operations and ensure transparency. Any revenue sources for the journal do not influence editorial decisions. Manuscripts submitted for publication are evaluated solely on their scientific merit. Throughout the submission and publication process, we maintain transparency and high publication standards.</p> <h3><strong>Advertising and Direct Marketing</strong></h3> <p>Our advertising policy is transparent and ethical. Advertisements, if any, are displayed separately from published content, and decisions regarding advertising are made based on relevance and quality. We prioritize professionalism, ethics, and the separation of advertising from scientific content to uphold editorial independence and article integrity. Additionally, we approach direct marketing activities cautiously to maintain ethical standards, prioritize transparency, obtain consent, and respect data privacy regulations.</p> <p><strong>Engineering and Technology Horizons (ETH)<br />Research and Innovation, Academic Support Section</strong><strong><br />Dean's Office, 2nd Floor 6-storey building<br />School of Engineering, King Mongkut’s Institute of Technology Ladkrabang</strong><br />No. 1, Chalong Krung 1, Chalong Krung Road, Lat Krabang Sub-district,<br />Lat Krabang District, Bangkok, 10520, Thailand<br />Tel/Fax: 02-329-8301 Ext. 249, E-mail: kmitl.eng.jnl@gmail.com</p> https://ph01.tci-thaijo.org/index.php/lej/article/view/260645 Enhancing Planning and Control for Sustainable Custom and Project-Based Furniture Manufacturing 2025-02-20T13:41:43+07:00 Suphattra Sriyanalugsana suphattra.sr@spu.ac.th Kong Suwantararangsri kong.su@spu.ac.th <p class="Abstractcontent">This study investigates production planning and control (PPC) challenges in the Thai furniture industry, particularly in custom and project-based manufacturing. A mixed-methods approach was adopted, combining structured interviews, on-site observations, and the analysis of historical production data to identify inefficiencies in scheduling, task coordination, and resource utilization. The factory implemented integrated PPC strategies such as standardized task planning, workforce optimization, and refined scheduling. As a result, it achieved a 23.58% reduction in delivery delays, a 14% improvement in labor utilization, and a 77.78% increase in the production rate. These outcomes highlight the effectiveness of agile coordination and structured planning in enhancing operational efficiency and supporting more sustainable manufacturing operations in high-variability, make-to-order environments.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260847 Min-Max Policy Implementation for Inventory Management in Steel Supply Sector 2025-03-04T08:30:47+07:00 Tinnakorn Phongthiya tinnakorn.phongthiya@cmu.ac.th Chompoonoot Kasemset chompoonoot.kasemset@cmu.ac.th <p class="Abstracttext"><span style="letter-spacing: -.2pt;">This study explores the application of the Min<span lang="TH">-</span>Max inventory management policy to improve stock control efficiency at a steel supply company in Chiang Mai Province, Thailand<span lang="TH">. </span>The company operates two branches<span lang="TH">: </span>a central warehouse and a retail store located 40 km apart<span lang="TH">. </span>Due to the absence of a formal inventory management policy, the retail branch frequently experiences stock shortages, leading to daily replenishment trips from the main warehouse, causing operational inefficiencies and excessive transportation costs<span lang="TH">. </span>The research focuses on four top<span lang="TH">-</span>selling products from the company<span lang="TH">’</span>s highest sales<span lang="TH">-</span>value category<span lang="TH">. </span>A Min<span lang="TH">-</span>Max policy was proposed where the minimum stock level was set based on the average daily demand multiplied by the minimum lead time, and the maximum level based on average demand multiplied by the most likely lead time<span lang="TH">. </span>Historical demand data from May 2022 to May 2023 were analyzed to determine appropriate Min<span lang="TH">-</span>Max thresholds<span lang="TH">. </span>Demand analysis revealed low average daily sales coupled with high variability, indicating the need for a structured inventory approach<span lang="TH">. </span>Trace<span lang="TH">-</span>driven simulations were conducted using historical demand data to assess the impact of the Min<span lang="TH">-</span>Max policy<span lang="TH">. </span>The simulation results showed a significant reduction in the number of transportation trips and cost compared to the company<span lang="TH">’</span>s current practice of daily restocking<span lang="TH">. </span>The study concludes that implementing the Min<span lang="TH">-</span>Max policy can reduce operational inefficiencies and transportation costs for the company<span lang="TH">. </span>However, the results are limited to the selected products and may not reflect the entire inventory's performance<span lang="TH">. </span>The simplicity of the Min<span lang="TH">-</span>Max policy makes it practical for SMEs, though further refinements such as demand forecasting techniques could optimize its performance in environments with high demand variability<span lang="TH">.</span></span></p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260843 Comparative Study of Modern VPN Solutions: Impact of Cloudflare, ZeroTier, and WireGuard on Network and Server Performance 2025-03-11T11:13:00+07:00 Pratchaya Jaisudthi pratchaya.j@rbru.ac.th Pachara Threerapat Sridee pachara.t.s@hotmail.com Natthakran Phungkoed nattakan.p@rbru.ac.th Kanyaphak Srisuk kanyaphak.s@rbru.ac.th Vasupon Phueaknumpol vasupon.p@rbru.ac.th <p class="Abstracttext"><span style="letter-spacing: -.2pt;">This research investigates of the performance of three popular VPN solutions namely Cloudflare, ZeroTier and WireGuard, by measuring their effect on network performance and server resource usage across multiple metrics such as file upload/download speeds, round-trip time (RTT), web latency, and server CPU usage. The aim is to find the best solution for certain workloads by benchmarking these solutions in a controlled manner. The results of these experiments showed large performance differences. The results were consistent for all tests: WireGuard provided the fastest upload and download speed (19 seconds and 52 seconds, for 1000 MB files, respectively), the lowest web latency (50 milliseconds for 1000 connections), and the most efficient CPU utilization (24% at 1000 connections). For small size of packets (less than 700 bytes), Cloudflare provided competitive RTTs around 10 milliseconds and balanced performance for light workloads. However, it was not scalable indicated by web latency about 200 milliseconds and CPU utilization higher than 32% in high-concurrency scenarios. Conversely with lower workloads, ZeroTier struggled with download of heavy file sizes and lots of connections such as downloading with 1000 MB in size took 84 seconds and up to 62% of CPU utilization. WireGuard emerges as the best-suited high-performance solution for scalable applications. Cloudflare and ZeroTier offer trade-offs helpful to particular use cases, providing perspective on which VPN solution to choose depending on workload requirements and resource constraints.</span></p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260839 Gain Enhancement of a Dual-Band S-Patch Antenna Array for 5G Application 2025-03-17T09:01:52+07:00 Dhanapon Udomratanasiri dhanapon_dh66@live.rmutl.ac.th Supakit Kawdungta supakitting@rmutl.ac.th Rassamitut Pansomboon Rassamitut.pan@nstda.or.th Alongkorn Lang alongkorn_lang@hotmail.com Chuwong Phongcharoenpanich chuwong.ph@kmitl.ac.th <p class="Abstracttext">This paper proposes the dual-band S-patch antenna with gain enhancement by using the planar array configuration and dielectric superstrate. The design of the proposed antenna is focused on the base station antenna in the 5G frequency bands n41 (2.6 GHz) and n78 (3.5 GHz). The dual-band S-patch antenna is arranged in the <br />2 × 6 elements planar array antenna and the FR4 dielectric superstrate is on the top of the array. The simulated results indicated that the operating frequency of 2.55–2.65 GHz and 3.46–3.61 GHz with uni-directional radiation pattern. The antenna gain can be improved with 18.70 dBi at 2.6 GHz and 19.30 dBi at 3.5 GHz. The prototype antenna is fabricated and the measured results are in good agreement. With the simple design of the proposed antenna, it would be useful for the installation of the base station antenna.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260990 Energy Consumption Prediction and Anomaly Detection for Boiler Feed Pump in Power Plant Using Machine Learning and Deep Learning 2025-04-02T07:00:18+07:00 Polawut Khamfoy 66056057@kmitl.ac.th Yuwadee Klomwises yuwadee.kl@kmitl.ac.th Sakuna Srianomai sakuna.sr@kmitl.ac.th <p class="Normalcontent" style="text-indent: 21.3pt;">Enhancing energy efficiency and operational reliability is crucial in power plant management, particularly for high-energy-consuming machines such as boiler feed water pumps (BFPs). These pumps play a vital role in the continuous generation of steam and electricity and must operate 24/7 to maintain power production stability. This study proposes the development of predictive models based on machine learning and deep learning techniques to accurately predict energy consumption and applies best models to detect anomalous behaviors in BFPs, enabling timely and preventive interventions. A dataset comprising 43,082 hourly records over five years, with 18 critical operational features, was analyzed using preprocessing and feature engineering techniques. Various predictive models were trained and evaluated, including Multiple Linear Regression, Regularized Regressions (Ridge, Lasso, ElasticNet), Support Vector Regression (SVR), Decision Tree, Ensemble Methods (Random Forest, XGBoost, CatBoost, LightGBM), and Deep Learning Architectures (DNN, RNN, GRU, LSTM). Among these models, SVR demonstrated the highest accuracy (MSE: 13.5573, R²: 0.9838), followed closely by LightGBM. Feature importance analysis revealed that boiler feed pump discharge pressure and bearing housing vibration levels were the most influential variables in energy consumption prediction. Anomaly detection using the Interquartile Range (IQR) method classified deviations into two warning levels, enabling proactive maintenance strategies. Additionally, a Graphical User Interface (GUI) web application was developed for real-time monitoring, integrating predictive models, anomaly detection, and an automated email alert system to assist operators in responding to abnormal energy consumption events promptly. These results highlight the potential of predictive analytics and real-time monitoring in optimizing power plant operations, providing a foundation for extending predictive capabilities to other critical energy-intensive systems.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260757 Improving Heavy Maintenance Management Efficiency under Limited Depot Resources: A Case Study of MRT Pink Line 2025-03-27T08:41:34+07:00 Rattiyakorn Tuangmaneetowong t.rattiyakorn@gmail.com Ackchai Sirikijpanichkul fengacs@ku.ac.th <p>This research focuses on optimizing the heavy maintenance scheduling of the Pink Line MRT using two models: a non-flexible model (fixed at 120,000 km) and a flexible model, which allows a ±10% adjustment in the accumulated mileage (108,000 - 132,000 km). The study employs Mixed-Integer Linear Programming (MILP) and a two-year simulation to analyze the effects of key constraints, including depot capacity, repair duration, and flexibility levels. The results indicate that a 10% flexibility reduces unused accumulated mileage by 55.97% and increases utilized mileage by 10%, without requiring additional resources. However, increasing the flexibility to 15% yields diminishing returns, leading to higher operational costs and potential safety risks. Conversely, reducing flexibility to 5% helps control costs but increases maintenance frequency, affecting operational stability. Additionally, sensitivity analysis reveals that a depot capacity of C = 2 (2 maintenance tracks per day) with a 5-day repair duration is optimal, balancing efficiency and resource allocation. C = 1 leads to maintenance congestion and reduced operational efficiency, whereas C = 2 effectively distributes maintenance workload without delays. Although C = 3 shortens repair time, it offers only marginal benefits compared to the increased costs. The findings highlight the importance of strategic flexibility management and optimized depot capacity to reduce maintenance frequency, enhance resource utilization, and improve overall train operation management. This research provides valuable insights for railway maintenance planning, contributing to cost reduction and long-term operational efficiency.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260633 Analysis of Rear Differential Component Clustering in Transmission Systems Using Hierarchical Cluster Analysis with and without Procurement Strategy Matrix Variables 2025-04-23T08:02:10+07:00 Saowalak Sombunsook 66016109@kmill.ac Kittiwat Sirikasemsuk kittiwat.sirikasemsuk@gmail.com Kanogkan Leerojanaprapa kanogkan.le@kmitl.ac.th <p>The automotive industry has faced significant challenges due to the large number of Tier 2 suppliers for Rear Differential components, with 17 suppliers providing 32 different parts. This situation has resulted in increased production costs and more complex supply chain management. This study aimed to analyze the clustering of Rear Differential components in transmission systems using Hierarchical Cluster Analysis, with the goal of supporting cost reduction in the automotive industry. Two clustering models were compared: Model 1, which excluded procurement strategy matrix variables (Special Requirements, Raw Material Grade, Raw Material Type, Manufacturing Process, Tier 2 Supplier Information, and Company Location), and Model 2, which incorporated an additional variable related to the Procurement Strategy Matrix. The decision criteria for determining the optimal number of clusters were based on four key factors: 1) Product design, 2) Characteristics, 3) Materials, and 4) Manufacturing. The clustering results for both models revealed the same optimal number of 13 clusters; however, the similarity matrix between the clusters differed. Furthermore, the number of members within each cluster varied. Based on the criteria for determining the optimal number of clusters, Model 2, which included the Procurement Strategy Matrix variable, demonstrated superior clustering efficiency compared to Model 1. Ultimately, this research identified 13 optimal clusters, reducing the number of Tier 2 suppliers from 17 to 13, representing a 23.53% reduction.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang https://ph01.tci-thaijo.org/index.php/lej/article/view/260764 Development of an Image Processing System for Defect Detection in Nam Dok Mai Golden Mangoes 2025-03-21T12:07:30+07:00 Phimthanarat Mungkan phimthanarat.mun@dome.tu.ac.th Warinthorn Kiadtikornthaweeyot Evans kwarinth@engr.tu.ac.th <p>This study proposes an image processing-based approach for detecting surface defects in Nam Dok Mai mangoes. Each fruit was photographed from two sides to capture comprehensive defect characteristics. The images were subsequently converted into the HSV color space to highlight darker defect regions, such as brown or black, followed by morphological dilation to refine defect boundaries and facilitate accurate area measurement.<strong> </strong>Detected defects were quantified in square centimeters and categorized into four quality classes: Extra Class, Class I, and Class II, according to the Thai Agricultural Standard TAS 5-2567. Additionally, a fourth class, Bad Quality, was introduced to represent defects exceeding the Class II size threshold. The annotated dataset was prepared using Roboflow, where labeling and data augmentation were conducted to enhance sample diversity. The dataset was partitioned into a training set (80%) and a testing set (20%). While image processing techniques were employed for initial dataset preparation, the primary objective was to develop a Mask R-CNN model capable of autonomously detecting defects directly from raw images, thereby eliminating the reliance on manual preprocessing. Following the training phase, the Mask R-CNN model was evaluated for its ability to detect and classify mango defects. Experimental results demonstrated high Precision and F1-Score values, particularly in the Extra Class and Bad Quality groups. The model achieved an overall accuracy of 70.71%, reflecting its strong potential for real-world application. It is anticipated that this system could significantly improve the accuracy and efficiency of mango sorting processes in the agricultural sector, contributing to standardized and reliable quality control.</p> 2025-06-25T00:00:00+07:00 Copyright (c) 2025 School of Engineering, King Mongkut’s Institute of Technology Ladkrabang