Predictive Maintenance for Ventilator Using LSTM Algorithm
YUSUF HAMZAH RUHIYAT
Informasi Umum
Kode
23.04.1556
Klasifikasi
006.31 - Machine Learning
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Machine Learning, Maintenance - Transmission - Communication Engineering,
Dilihat
299 kali
Informasi Lainnya
Abstraksi
<p>A ventilator is a device or machine that functions to support or assist breathing. Ventilators are needed by patients who have respiratory problems, either due to an illness or due to injury. The ventilator will pump air in a few seconds to deliver oxygen to the patient's lungs. In this study, it is intended to apply the LSTM method on the ventilator system as a maintenance prediction to simplify and predict the failure that will occur on the ventilator. By using Predictive Maintenance, maintenance can be carried out at the right time before equipment failure occurs. Long Short Term Memory is one of the algorithms that can be used to predict the treatment on the ventilator that needs to be done in the future. The highest result obtained in this study is the probability of failure in 50 cycles is 98.4% with an accuracy of 82%.</p>
<p><strong>Keywords </strong><strong>:</strong><em> Predictive Maintenance</em><em>, </em><em>Ventilator</em><em>, C</em><em>ondition-</em><em>B</em><em>ased </em><em>P</em><em>redictive </em><em>M</em><em>aintenance</em><em>, LSTM Algorithm</em></p>
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | YUSUF HAMZAH RUHIYAT |
| Jenis | Perorangan |
| Penyunting | Sony Sumaryo, Erwin Susanto |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Teknik Elektro (International Class) |
| Kota | Bandung |
| Tahun | 2023 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
