Predictive Maintenance for Ventilator Using LSTM Algorithm

YUSUF HAMZAH RUHIYAT

Informasi Dasar

134 kali
23.04.1556
006.31
Karya Ilmiah - Skripsi (S1) - Reference

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%.

Keywords : Predictive Maintenance, Ventilator, Condition-Based Predictive Maintenance, LSTM Algorithm

Subjek

Machine Learning
Maintenance - transmission - communication engineering,

Katalog

Predictive Maintenance for Ventilator Using LSTM Algorithm
 
 
Inggris

Sirkulasi

Rp. 0
Rp. 0
Tidak

Pengarang

YUSUF HAMZAH RUHIYAT
Perorangan
Sony Sumaryo, Erwin Susanto
 

Penerbit

Universitas Telkom, S1 Teknik Elektro (International Class)
Bandung
2023

Koleksi

Kompetensi

 

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