Implementasi Sistem Monitoring Overall Equipment Effectiveness (OEE) Pada Pengisian Cat (Pail) Menggunakan Grafana dan Node-RED

Alam, Muhammad Habli Aufa (2026) Implementasi Sistem Monitoring Overall Equipment Effectiveness (OEE) Pada Pengisian Cat (Pail) Menggunakan Grafana dan Node-RED. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Efisiensi operasional mesin merupakan faktor krusial dalam industri manufaktur, khususnya pada lini produksi pengisian cat (paint filling). Penelitian ini bertujuan untuk mengimplementasikan sistem monitoring Overall Equipment Effectiveness (OEE) berbasis Industrial Internet of Things (IIoT) menggunakan Advantech ECU-1251V2, MySQL, Node-RED, dan Grafana. Sistem dirancang untuk mengakuisisi data produksi secara otomatis dari mesin pengisian cat, menghitung parameter Availability, Performance, Quality, dan Overall Equipment Effectiveness (OEE), serta menampilkan hasil perhitungan melalui dashboard Grafana secara real-time. Pengujian sistem dilakukan menggunakan 160 data pengamatan yang diperoleh dari proses produksi. Hasil implementasi menunjukkan bahwa sistem berhasil melakukan akuisisi, pengolahan, penyimpanan, dan visualisasi data secara otomatis. Pengujian komunikasi menunjukkan bahwa latency pengiriman data dari gateway menuju database berada pada rentang 350–821 ms, sedangkan latency hingga data ditampilkan pada dashboard Grafana berada pada rentang 842–1.767 ms, sehingga sistem mampu menyajikan informasi kondisi mesin dengan jeda waktu yang relatif rendah untuk kebutuhan monitoring real-time. Nilai rata-rata parameter OEE yang diperoleh adalah Availability sebesar 95,3%, Performance sebesar 78,5%, Quality sebesar 100%, dan Overall Equipment Effectiveness (OEE) sebesar 74,8%. Hasil validasi menunjukkan bahwa seluruh hasil perhitungan otomatis menggunakan Node-RED identik dengan perhitungan manual, sedangkan dashboard Grafana mampu menyajikan informasi performa mesin secara real-time disertai fitur alarm ketika nilai OEE berada di bawah standar World Class sebesar 85%. Berdasarkan hasil survei pengguna, sistem memperoleh tingkat kepuasan sebesar 94,4%, sehingga sistem dapat mendukung proses monitoring dan pengambilan keputusan berbasis data untuk meningkatkan efektivitas mesin pengisian cat (pail).
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Operational efficiency is a crucial factor in the manufacturing industry, particularly in paint filling production lines. This study aims to implement an Overall Equipment Effectiveness (OEE) monitoring system based on the Industrial Internet of Things (IIoT) using Advantech ECU-1251V2, MySQL, Node-RED, and Grafana. The proposed system is designed to automatically acquire production data from the paint filling machine, calculate the Availability, Performance, Quality, and Overall Equipment Effectiveness (OEE) parameters, and visualize the calculated results through a real-time Grafana dashboard. System testing was conducted using 160 production data samples collected from the paint filling process. The implementation results demonstrate that the system successfully performs automatic data acquisition, processing, storage, and visualization. Communication performance testing indicates that the data transmission latency from the gateway to the database ranges from 350 to 821 ms, while the latency from data acquisition until visualization on the Grafana dashboard ranges from 842 to 1,767 ms, enabling the system to provide near real-time monitoring of machine conditions. The average OEE parameters obtained from the experimental data were 95.3% Availability, 78.5% Performance, 100% Quality, and an overall OEE value of 74.8%. Validation results show that all OEE calculations performed automatically by Node-RED are identical to manual calculations, confirming the accuracy of the implemented calculation algorithm. Furthermore, the Grafana dashboard successfully provides real-time machine performance visualization and generates alerts whenever the OEE value falls below the World-Class standard of 85%. Based on the user satisfaction survey, the proposed system achieved an overall satisfaction score of 94.4%, indicating that it effectively supports machine performance monitoring and facilitates data-driven decision-making to improve the effectiveness of the paint filling (pail) production process.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	OEE, IIoT, Advantech ECU-1251V2, Node-RED, Grafana, Monitoring Real-time
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Muhammad Habli Aufa Alam
Date Deposited:	05 Aug 2026 06:12
Last Modified:	05 Aug 2026 06:12
URI:	http://repository.its.ac.id/id/eprint/144030

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