RANCANG BANGUN ALAT DETEKSI DINI GEJALA KERUSAKAN MESIN INDUSTRI BERDASARKAN PARAMETER SUHU, GETARAN, DAN SUARA BERBASIS IoT

Sudiaman, Sudiaman (2026) RANCANG BANGUN ALAT DETEKSI DINI GEJALA KERUSAKAN MESIN INDUSTRI BERDASARKAN PARAMETER SUHU, GETARAN, DAN SUARA BERBASIS IoT. Sarjana (S1) thesis, Universitas Muhammadiyah Indonesia.

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Abstract

ABSTRACT

Industrial machine failures generally begin with changes in temperature, vibration, and noise levels. If these changes are not detected at an early stage, they may develop into more serious failures and disrupt production processes. This study aims to design and develop an Internet of Things (IoT)-based device for the early detection of machine fault symptoms by measuring temperature, vibration, and noise level parameters and transmitting the measurement results to a web dashboard for further analysis. This research employed a quantitative approach using the design and development method, which consisted of hardware design, software development, system implementation, testing, and evaluation. The proposed system was developed using an ESP32 microcontroller, a MAX6675 temperature sensor with a K-type thermocouple, an ADXL345 vibration sensor, a MAX9814 sound sensor, an OLED display, Firebase Realtime Database, and a web dashboard for visualizing measurement results. System performance was evaluated by comparing the sensor measurements with reference instruments, namely the Raytek MiniTemp MT4 for temperature, Physics Toolbox Suite for vibration, and the UNI-T UT353 Sound Level Meter for noise level measurements. The experimental results showed that the temperature sensor achieved an accuracy of 98.38%, the vibration sensor 96.15%, and the sound sensor 97.44%. In addition, the system successfully transmitted, stored, and displayed the measurement results through the web dashboard with an average communication latency of approximately one second. The buzzer alarm also functioned properly by providing warnings whenever the measured values exceeded the predefined threshold limits. Based on these results, the developed device is capable of measuring key machine condition parameters and presenting the measurement results through a web dashboard. Therefore, it has the potential to serve as a portable inspection tool that supports condition-based maintenance and preventive maintenance activities for the early detection of industrial machine fault symptoms.

Keywords: Early Detection of Machine Fault Symptoms, IoT, ESP32, Temperature, Vibration, Noise Level

Item Type:	Thesis (TA, Skripsi, Tesis, Disertasi) (Sarjana (S1))
Contributors/Dosen Pembimbing,NIDN Dosen bisa diakses di LINK https://bit.ly/NIDNdosenunismabekasi:	Contribution Contributors / Dosen Pembimbing NIDN UNSPECIFIED Bakri, Muhammad Amin 0425106801 UNSPECIFIED Sujatmiko, Aeri 0431127603
Keywords / Kata Kunci:	Keywords: Early Detection of Machine Fault Symptoms, IoT, ESP32, Temperature, Vibration, Noise Level
Subjects:	Kendali/Kontrol
Faculty:	Fakultas Teknik > Teknik Elektro S1
Depositing User:	Mr. Sudiaman Sudiaman
Date Deposited:	18 Aug 2026 08:07
Last Modified:	18 Aug 2026 08:07
URI:	http://repository.umindonesia.ac.id/id/eprint/10650

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