Engineering Headway Vol. 38

Abstract: Energy is a fundamental necessity that underpins numerous aspects of life for Indonesian society and, indeed, worldwide. The global energy crisis underscores the urgency of finding environmentally friendly, cost-effective, and sustainable alternative energy sources to replace the reliance on fossil fuels. Fossil fuels account for 80% of global energy needs, yet they pose environmental impacts and are a finite resource. One promising renewable energy source with the potential for development due to its environmental friendliness is the fuel cell. However, a drawback of fuel cells lies in the use of precious metals (platinum) as membranes, which are expensive and have limited availability on Earth. This research aims to determine the characteristics of the best activated carbon derived from the pyrolysis of corn cobs and cassava stems as carbon for membrane fuel cell catalysts. Through physical activation via slow pyrolysis in a fixed bed reactor, the utilisation of this biomass waste is expected to be an innovative solution to reduce the production costs of membrane fuel cells while also promoting the development of more affordable clean energy. This research employs an experimental method by conducting pyrolysis of cassava stem and corn cob biomass with variations in temperature and residence time. The temperature variations for corn cob pyrolysis were 400°C, 450°C, and 500°C, with residence times of 30 minutes and 60 minutes, while for cassava stem pyrolysis, the temperature variations were 300°C, 400°C, and 500°C, with residence times of 15 minutes and 30 minutes. The resulting carbon was then subjected to proximate analysis to determine its fixed carbon content. Based on the proximate analysis results for corn cob waste, the temperature variation of 500°C with a residence time of 60 minutes yielded the highest fixed carbon content at 74.35%, whereas for cassava stems, the best variation was obtained at a temperature of 400°C and a residence time of 30 minutes, producing the highest fixed carbon content 72.94%, thus showing potential as a support material for fuel cell catalysts.

Abstract: The design of flow field geometry plays a crucial role in determining the performance and efficiency of Proton Exchange Membrane Fuel Cells (PEMFC), particularly in optimizing hydrogen distribution and minimizing pressure losses. This study presents a comprehensive comparative evaluation of three flow field configurations of serpentine, parallel, and pin-type using computational fluid dynamics (CFD) simulations and experimental validation under identical boundary conditions. The flow behavior, pressure, and hydrogen distribution were numerically analyzed, while voltage retention time was measured experimentally to assess fuel cell performance. Results indicate that the serpentine configuration achieved the highest uniformity index (UI = 0.92), due to its continuous and tortuous flow path, which promoted complete hydrogen coverage and minimized stagnation zones. The parallel and pin-type configurations exhibited lower UI values (0.75 and 0.83) and non-uniform gas distribution, leading to early voltage decay. Experimentally, the serpentine flow field sustained a voltage above 0.2 V for 3.00 minutes, significantly longer than the parallel (1.00 minute) and pin-type (0.43 minute) designs. Statistical analysis using one-way ANOVA confirmed the significance of these differences (p < 0.001). The strong correlation between simulation and experimental findings reinforces the importance of flow field optimization in PEMFC systems. This study highlights the superiority of the serpentine configuration in enhancing hydrogen utilization and operational stability, offering validated insights for developing high-performance PEMFCs in future hydrogen energy applications.

Abstract: Accurate vehicle-type classification is pivotal in intelligent transportation systems (ITS) for traffic monitoring, adaptive signal control, and automated tolling. We present a machine-learning approach that predicts vehicle categories from magnetic induction loop signal signatures, with a specific emphasis on early heavy-vehicle identification to help mitigate road-infrastructure degradation due to overloading. Motivated by Indonesia’s urgent needs in road safety and ODOL (overloading) enforcement, we develop a physics-guided synthetic data generator that simulates loop responses across representative classes under varying speeds, lateral offsets, and noise. We benchmark two models: model A InceptionTime (a strong 1D-CNN baseline) and model B a Physics-Informed TSMixer (PI-TSMixer) that mixes time/channel tokens while injecting physically meaningful cues (distance-domain normalization and axle-pattern hints). On synthetic, stress-tested scenarios, Model B achieves higher macro-F1 and better out-of-distribution robustness than InceptionTime (≈+1.5 pp in-distribution; ≈+4.0 pp OOD), suggesting that lightweight, physics-aware architectures generalize better for loop-based vehicle classification and integrate well with Weigh-in-Motion (WIM) pipelines for Indonesian corridors.

Abstract: The User Interface (UI) plays a critical role in usability. The usability of an information system focuses on how easy the system is to use and its effectiveness. This study aims to redesign the website interface of the academic information system of Universitas Trunojoyo Madura (SIAKAD-UTM). The cognitive walkthrough and eye-tracking analysis methods are proposed to assess the usability before and after improvement. The activities evaluated included the login page (task-1), course information (task-2), study plan card (task-3), study result card (task-4), and transcript (task-5). Thirty-nine students from the Faculty of Engineering participated. The study, based on McNemar's test, shows no difference in the success rate across the entire task. The error indicator did not show any improvement in tasks 2 to 5; however, there was evidence of progress in task 1. In addition, the Wilcoxon test indicated improvements in login activities (task-1), course information (task-2), and study result cards (task-4), although there was no increase in performance in study plan card activities (task-3) or transcripts (task-5). These results indicate that the redesign of UI SIAKAD UTM was effective.

Abstract: Welding is a crucial assembly or joining stage in manufacturing processes. The welding process often faces issues related to welding defects due to its complexity, which is associated with welding parameters, the type and properties of materials, and the technology used. Additionally, it also relates to a significant number of welding points. Therefore, Non-Destructive Testing (NDT) methods have become the primary choice for evaluating welding quality without damaging the workpiece. With the advancement of technology, NDT testing has undergone significant changes, including the adoption of computer vision and machine learning technologies that enable automated inspection. This research aims to propose a semi-automated inspection system for welding quality using the YOLOv5 network architecture regarding with defects detection. The detection process involves various combinations of YOLO models (small and medium) with a training dataset of 2050 images and different training epochs (50 and 100). The model's performance is then tested using test data to evaluate its real-world performance. The detection results are also manually verified through one-to-one comparisons, revealing that 16 out of the total 21 predictions are correct. This success is used to measure the accuracy of the YOLOv5 detection system, which shows a detection accuracy rate of 76.2%. Meanwhile, the estimation accuracy results in a Mean Absolute Percentage Error (MAPE) value of 16.798%.

Abstract: The growing concern over antibiotic residues in the environment and food chain highlights the need for sensitive detection methods. This study reports a hydrophobic deep eutectic solvent (DES)-based modification for screen-printed carbon electrodes (SPCE) to improve antibiotic detection. The material was prepared by combining magnetic nanoparticles (MNP) with a DES of decanoic acid and 2-pentanol (1:1). This MNP-DES was applied to the SPCE surface by drop-casting. Electrochemical performance was evaluated using cyclic voltammetry (CV) from -0.1 to 0.6 V at 100 mV/s. Comparative analysis of unmodified SPCE, MNP-SPCE, and MNP-DES-SPCE showed that DES greatly enhanced the electrochemical response toward oxytetracycline (OTC) as a model antibiotic. The MNP-DES SPCE demonstrated feasibility for antibiotic detection and provides a basis for optimization to lower the detection limit to regulatory levels. This approach offers a novel strategy by exploiting the synergy of MNPs and DES, contributing to electrochemical sensor development for antibiotics.

Abstract: One of the cement companies in Indonesia has implemented biomass as an alternative fuel in kiln operations. However, the high moisture content of biomass, typically around 30%, often reduces combustion efficiency. This research presents the design of a rotary dryer to reduce biomass moisture content to approximately 10%. The proposed system has a processing capacity of 500 kg/h with main specifications including a drum diameter of 1.26 m, length of 7.56 m, inclination angle of 2.29°, rotational speed of 6 rpm, and a material residence time of around 30 minutes. The total power requirement is estimated at 15 kW with hot air supplied at 150 °C. Heat balance calculations indicated a minimal deviation of 0.00057%, confirming the accuracy of the design. Thermal simulations demonstrated uniform temperature distribution throughout the drum, ensuring effective drying. From an economic perspective, the system provides significant daily operational benefits by reducing coal consumption. The proposed design is therefore technically feasible, economically viable, and environmentally beneficial, supporting the substitution of fossil fuels and the reduction of CO₂ emissions in cement manufacturing.

Abstract: Drying is a well-established method for preserving food, extending shelf life, maintaining quality, and reducing post-harvest losses, yet many conventional systems remain energy-intensive and weather-dependent, particularly in regions with limited electricity supply. This review examines recent developments in food drying technologies, from traditional systems to innovative concepts integrating artificial intelligence, hybrid configurations, and renewable energy sources. A systematic literature review was conducted using Scopus, Web of Science, and Google Scholar for publications from January 2020 to May 2025, applying defined inclusion–exclusion criteria and multi-stage screening, resulting in 95 relevant articles covering methods, innovations, optimization approaches, and implementation challenges. The findings show significant progress in the use of hybrid solar dryers, AI-assisted modeling, and optimization of process parameters to improve energy efficiency and product quality, with portable and hybrid solar dryers emerging as promising options for farmers and SMEs in low-electrification areas. However, high investment costs, limited scalability, and the need for robust real-time control still hinder wider adoption in resource-constrained settings. This review provides an integrated overview of state-of-the-art drying technologies, highlights knowledge gaps, and outlines research priorities for developing energy-efficient drying systems capable of producing high-quality products and accessible across diverse operating contexts.

Abstract: The strategic integration of natural dehumidifiers in agricultural drying systems offers significant potential for enhancing energy efficiency while maintaining product quality. This study comprehensively evaluated the energy performance of natural dehumidifier placement in a multi-rack turmeric drying cabinet by comparing three configurations: without dehumidifier (baseline), dehumidifier positioned at the top, and dehumidifier positioned at the bottom of the drying chamber. The experimental setup utilized a multi-rack cabinet dryer with six trays, processing 350 grams of fresh turmeric per tray (2.1 kg total batch) over 300 minutes operation time. Energy performance parameters were calculated based on actual initial and final weights of turmeric samples, providing accurate moisture removal quantification for each configuration. Energy performance was assessed through multiple metrics including Specific Moisture Extraction Rate (SMER), Specific Energy Consumption (SEC), weight reduction percentage, final moisture content, and actual energy consumption measurements. Results demonstrated that the top-positioned dehumidifier configuration achieved superior energy performance with SMER of 0.519 kg/kWh, representing a 22.7% improvement over baseline (0.423 kg/kWh), while energy consumption decreased by 15.9% (from 3.78 to 3.18 kWh). The SEC showed remarkable improvement, reducing from 2.37 to 1.93 kWh/kg H₂O (18.5% reduction). Total moisture removal increased by 3.3% (from 1.598 to 1.650 kg), achieving 78.6% weight reduction compared to 76.1% baseline. Most significantly, the top configuration achieved a final moisture content of 6.6% wet basis, meeting commercial standards (<10%), while baseline and bottom configurations resulted in 16.3% and 13.0% respectively, both failing to meet commercial requirements. In contrast, the bottom-positioned dehumidifier showed moderate performance with SMER of 0.474 kg/kWh (12.2% improvement over baseline) and energy consumption of 3.41 kWh (9.8% reduction), achieving SEC of 2.11 kWh/kg H₂O (10.8% improvement) and 77.0% weight reduction. These findings demonstrate that natural dehumidifier placement significantly influences both energy performance and final product quality, with top positioning being the only configuration capable of achieving commercial moisture standards while delivering optimal energy efficiency in small to medium-scale turmeric drying operations.

Abstract: Wind energy has developed rapidly with various efforts aimed at improving its performance. The Darrieus wind turbine will study its performance by adding fins to the surface of the Darrieus turbine. The turbine shape in this study utilizes NACA 0018 symmetry by adding one fin on the mid-span side and the fin is varied against the fin height. The method used is a numerical study with a CFD approach that varies the fin height to determine the value of the torque coefficient, power coefficient, and tip speed ratio. This study uses a Darrieus turbine with a diameter of 40 cm and a rotor height of 50 cm, and varies the fin height by 1.5 cm, 2.5 cm, and 3.5 cm. The results show that the turbine performance increases by 45.23% at a fin height of 2.5 cm.