Journal of Engineering, Technology, and Applied Science (JETAS)

Optimization of Roll Die Cutting Machine Utilization in the Production Fold Carton Packaging

2026-05-10T15:20:07+00:00

Folded carton packaging is commonly used in various industries due to its lightweight, flexible, and environmentally friendly properties. Roll die cutting machines are the primary technology used in mass production because they can achieve cutting Accuracy of up to 99% with only 1,2% material waste at optimal parameters (pressure of 5 bar, speed of 20 m/min, blade sharpness of 0.1 µm). Therefore, this study uses an experimental method to optimize cutting parameters by varying pressure (3-7 bar), speed (10-30 m/min), and blade sharpness (0.1-0.5 µm). The research results show that the use of a blunt blade (0.5 µm) at high pressure (7 bar) can reduce Accuracy by up to 85% and increase Waste by up to 10%. Comparison with flatbed cutting machines reveals the superiority of roll die cutting in terms of production speed (three times faster) and precision (four % higher), despite requiring 50% higher maintenance expenses. The implementation of these optimal parameters in industry is projected to increase productivity by up to 30% while reducing material waste by up to 40%, provided that routine blade maintenance is performed every 5,000 cutting cycles. These findings offer significant technical recommendations for improving the efficiency of folding carton packaging production.

Development of an Arduino-Based Water Level Indicator with Audio-Visual Alert Mechanisms

2026-05-11T01:22:28+00:00

Monitoring water levels in tanks and reservoirs is essential to prevent overflow, dry running of pumps, and inefficient water usage. This study presents the design and implementation of a low-cost water level indicator and alert system based on Arduino, integrating a water level sensor, RGB LED indicators, and an audible buzzer. The proposed system detects discrete water levels using conductive probes or a resistive water level sensor placed at different heights inside a container. The Arduino microcontroller processes the sensor signals and provides real-time visual feedback through an RGB LED, where different colors represent low, medium, and high water levels. In addition, a buzzer is activated when the water reaches a critical threshold, serving as an audible warning to prevent overflow or system damage. The system architecture is simple, modular, and easy to implement, making it suitable for domestic water tanks, laboratories, and small-scale industrial applications. Experimental testing demonstrates that the system responds reliably to changes in water level, with minimal latency and stable operation under repeated trials. Compared to conventional mechanical float-based indicators, the proposed design offers improved flexibility, ease of maintenance, and expandability, such as integration with wireless modules or IoT platforms. The results show that combining visual (RGB LED) and audio (buzzer) indicators enhances user awareness and system usability. Overall, this Arduino-based water level indicator provides an effective, economical, and scalable solution for real-time water level monitoring and alerting, supporting efficient water management and resource conservation.

Smart Grid Design and Simulation for Goma TMK Substation Regulation

2026-05-11T01:01:29+00:00

Power distribution networks in places like Goma, Democratic Republic of Congo, face the challenges of voltage control, energy loss, and power quality because they depend mainly on manual control provided at substations such as TMK. This study proposes a smart grid solution for automated voltage regulation through On-Load Tap Changer (OLTC) control for inefficiencies stemming from the above challenges using a Programmable Logic Controller (PLC). The system utilizes real-time electrical parameters monitoring, thereby employing dynamic adjustment processes to ensure voltage levels are kept at their optimum, as well as limiting overcurrent and improving thermal stability. The hybrid simulation approach uses Siemens TIA Portal for PLC logic and MATLAB Simulink to check the system's dynamic analysis under varied loads and faults. The results proved to enhance voltage stability and operational efficiency, and robustness while minimizing human intervention. The architecture is amenable to SCADA integration and distributed energy resources for future incorporation, thus providing a scalable solution to aging grids in resource-poor settings.

Integration of Weather API and IoT in an Automatic Irrigation System Based on Soil Moisture for Sugarcane Farming

2026-05-11T01:14:19+00:00

National sugarcane productivity in Indonesia faces significant challenges due to climate change and a reliance on rain-fed lands, as is the case in Banjarejo Village, Grobogan Regency. Prolonged drought conditions frequently lead to unstable crop growth and diminished harvest yields. This study aims to design and implement an adaptive, Internet of Things (IoT)-based automated irrigation system by integrating soil moisture sensors with weather forecast data obtained via the OpenWeatherMap Application Programming Interface (API). The system utilizes an ESP32 microcontroller as its central control unit and solar panels as its primary energy source to support sustainable agriculture. The research methodology encompasses hardware design, employing Capacitive v1.2 soil moisture sensors, a 200 Wp solar module, and a 100 Ah battery; as well as software development utilizing JSON deserialization methods on the Blynk platform. Testing results demonstrate that the sensors exhibit a remarkably high level of accuracy, with an average error rate of merely 0.528%. The integration of weather data enables the system to make more intelligent irrigation decisions; the pump activates only when soil moisture levels fall below 40% and no rainfall is forecast. Over a one-month testing period, the system achieved a 100% success rate in executing its control logic and maintaining real-time data synchronization. The use of solar panels also proved effective, generating a peak power output of 87.4 Watts under bright, sunny conditions. In conclusion, this integration of IoT technology, real-time weather data, and renewable energy successfully enhances water-use efficiency and remote monitoring effectiveness, offering an innovative solution for sugarcane farmers as they navigate dynamic environmental conditions.