Program Studi Teknologi Rekayasa Mekatronika 2026

Mahasiswa : Bumi Satriyo, Lee Khee Mahendra

Pembimbing : Y.B. Adyapaka Apatya, M.T.

ABSTRAK/ABSTRACT

Proses compacting 200 Ton merupakan tahap esensial dalam industri powder metallurgy untuk membentuk green part secara konsisten. Pada praktiknya, PT. XYZ masih menggunakan metode pencatatan manual dalam merekam jumlah produksi dan status operasional mesin. Metode manual ini rentan terhadap human error, keterlambatan data, serta tidak akuratnya perekaman alasan downtime, yang pada akhirnya menghambat perhitungan Overall Equipment Effectiveness (OEE). Tugas Akhir ini bertujuan untuk merancang dan membangun purwarupa sistem monitoring produksi secara real-time berbasis Internet of Things (IoT) untuk menggantikan sistem pencatatan manual. Sistem ini menggunakan ESP32 DevKit dan sensor relay berlogika Active-HIGH Pull-up untuk merekam output (Good dan No-Good) langsung dari mesin. Transmisi data dilakukan menggunakan protokol WebSocket, dengan Redis sebagai pengelola memori (state management) untuk mencegah kehilangan data (data loss). Visualisasi data disajikan melalui dashboard interaktif bergaya Glassmorphism dengan pembagian akses antara operator dan manajer. Hasil pengujian menunjukkan bahwa sistem berhasil mencatat dan menampilkan siklus produksi dengan tingkat akurasi mencapai 99,8%. Implementasi monitoring digital ini secara efektif meminimalisasi keterlambatan pelaporan, menyediakan visibilitas real-time terhadap performa mesin, dan memberikan landasan data yang valid bagi manajemen untuk melakukan perbaikan proses berkelanjutan.

Kata Kunci : Compacting, Dashboard, IoT, Monitoring, OEE, WebSocket,

The 200 Ton compacting process is an essential stage in the powder metallurgy industry for consistently forming green parts. In practice, PT. XYZ still utilizes manual recording methods to log production quantities and machine operational status. This manual approach is susceptible to human error, data latency, and inaccurate recording of downtime reasons, which ultimately hinders the calculation of Overall Equipment Effectiveness (OEE). This final project aims to design and develop a prototype of a real-time production monitoring system based on the Internet of Things (IoT) to replace the conventional manual recording system. The system utilizes an ESP32 DevKit and relay sensors with Active-HIGH Pull-up logic to record outputs (Good and No-Good) directly from the machine. Data transmission is executed using the WebSocket protocol, with Redis acting as memory management (state management) to prevent data loss. Data visualization is presented through an interactive Glassmorphism-styled dashboard featuring role-based access for operators and managers. Testing results demonstrate that the system successfully records and displays production cycles with an accuracy rate of 99,8%. The implementation of this digital monitoring effectively minimizes reporting delays, provides instant visibility into machine performance, and offers a valid data foundation for management to pursue continuous process improvements.

Keywords : Compacting, Dashboard, IoT, Monitoring, OEE, WebSocket,

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