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JENTIK : Jurnal Pendidikan Teknologi Informasi dan KomunikasiJENTIK : Jurnal Pendidikan Teknologi Informasi dan Komunikasi

The development of the food and beverage industry demands innovation in efficient and reliable packaging processes. Conventional cup sealing machines often face limitations in speed and precision, necessitating technology-based solutions. This study aims to design and implement an automated cup sealer system based on the Internet of Things (IoT), using the NodeMCU ESP32, capable of performing sealing and real-time monitoring. The system integrates a flowmeter sensor to detect the presence of cups, a stepper motor for the sealing process, and an LCD display along with WiFi connectivity for monitoring production data. The methodology involves hardware design, control system programming, and performance testing of the device under various temperature and motor speed parameters. The results show that the system can increase production efficiency by up to six times compared to the manual method, with a capacity of 300 cups per hour and a sealing success rate of 95% at an optimal temperature of 100°C and a motor speed of 10 RPM. Synchronization among components was enhanced through sensor calibration and algorithm development. In conclusion, this automated system not only improves efficiency and accuracy but also offers flexibility and IoT-based control, making it highly relevant for small and medium-sized industries.

In conclusion, this automated system improves efficiency and accuracy, offering flexibility and IoT-based control, making it relevant for small and medium-sized industries.The system successfully integrates a flowmeter sensor, stepper motor, and NodeMCU ESP32 for precise cup sealing and real-time monitoring.Challenges in sensor synchronization were overcome through calibration and algorithm development, resulting in a sixfold increase in production efficiency compared to manual methods.

Future research should focus on conducting field tests in real industrial settings to assess the systems durability and reliability under actual operating conditions. Expanding material compatibility by testing with various cup materials and dynamically adjusting sealing parameters would broaden the systems applicability. Furthermore, developing a mobile application for remote access and control, coupled with the integration of machine learning algorithms for automatic fault detection, would significantly enhance the systems overall performance and usability, paving the way for wider adoption in the manufacturing sector and contributing to the ongoing digital transformation of industries.

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