Sistem Diagnosis Kondisi Kerusakan Robot Arm Palletizer Fuji Menggunakan Metode Fuzzy Logic Untuk Meminimalisir Downtime Pada Line Pengantongan

Nizam, Bariq Rizqulla (2025) Sistem Diagnosis Kondisi Kerusakan Robot Arm Palletizer Fuji Menggunakan Metode Fuzzy Logic Untuk Meminimalisir Downtime Pada Line Pengantongan. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Proses penataan pupuk oleh Robot Arm Palletizer Fuji di PT. Petrokimia Gresik menjadi salah satu tahap penting dalam menjaga kelancaran dan efisiensi produksi. Namun, tingginya intensitas kerja robot serta kondisi lingkungan pabrik yang korosif sering kali memicu terjadinya gangguan mekanis seperti macetnya piston gripper, perubahan sudut lengan robot, hingga kerusakan pada motor servo. Gangguan tersebut berdampak pada proses kerja dari robot arm dan dapat menghambat proses distribusi pupuk. Untuk mengantisipasi hal ini dirancang sebuah sistem diagnosis kondisi kerusakan dengan metode fuzzy logic yang mampu memantau kondisi robot secara real-time melalui parameter getaran, kemiringan, suhu, dan tekanan. Sistem ini memanfaatkan sensor ADXL345, DS18B20, dan pressure transmitter yang dikendalikan oleh mikrokontroler ESP32-S3. Data yang dikirimkan melalui protokol MQTT diproses menggunakan logika fuzzy Mamdani pada Node-RED. Hasil diagnosis kemudian ditampilkan melalui dashboard monitoring. Berdasarkan hasil pengujian sistem menunjukkan tingkat akurasi diagnosis sebesar 80% menggunakan metode mean average precision (mAP) dan mampu memberikan respon dengan rata-rata waktu delay 814 ms hingga 913 ms. Dengan adanya sistem ini operator dapat memperoleh informasi kondisi robot secara cepat dan akurat sehingga potensi kerusakan dapat dideteksi lebih dini.
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The fertilizer bagging process at PT. Petrokimia Gresik relies heavily on the Fuji Palletizer Robot Arm to maintain production efficiency and continuity. However, due to the robot's high operational workload and the corrosive factory environment mechanical failures such as gripper malfunctions, arm misalignment, and motor servo damage frequently occur. These issues affect the robot arm’s operation and disrupting the production and distribution process. To address this problem, a damage condition diagnosis system based on fuzzy logic was developed to monitor the robot's condition in real-time by analyzing vibration, tilt, temperature, and pressure parameters. The system integrates ADXL345, DS18B20, and pressure transmitter sensors managed by an ESP32-S3 microcontroller. Sensor data is transmitted using the MQTT protocol and processed with Mamdani fuzzy logic on the Node-RED platform. The diagnostic results displayed through a real-time monitoring dashboard. Test results show that the system achieves an overall diagnosis accuracy of 80% based on the mean average precision (mAP) method with response times averaging between 814 and 913 milliseconds. The implementation of this system provides operators with timely and accurate information regarding the robot's condition enabling early detection of potential failures.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Fuji Palletizer Robot Arm, Fuzzy Logic, Damage Diagnosis, Downtime
Subjects:	Q Science > QA Mathematics > QA336 Artificial Intelligence Q Science > QA Mathematics > QA76.6 Computer programming. Q Science > QA Mathematics > QA9.64 Fuzzy logic
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Bariq Rizqulla Nizam
Date Deposited:	08 Aug 2025 06:01
Last Modified:	08 Aug 2025 06:01
URI:	http://repository.its.ac.id/id/eprint/127996

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