FIRDAUS, ADE (2022) ANALISA ALAT ANGIOGRAPHY MENGGUNAKAN FAILURE MODE AND EFFECTS ANALYSIS (FMEA) BERBASIS FUZZY LOGIC. S2 thesis, Universitas Mercu Buana Jakarta-Menteng.
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Abstract
Failure Mode and Effects Analysis (FMEA) adalah metode yang banyak digunakan dalam aplikasi teknik untuk identifikasi dan penilaian kemungkinan kegagalan. Secara umum atau tradisional, penilaian risiko mode kegagalan dilakukan dengan menggunakan nomor prioritas risiko yang dihitung berdasarkan tingkat kejadian, tingkat keparahan dan deteksi mode kegagalan. Mode kegagalan dengan peringkat tertinggi kemudian di analisis dan dianggap sebagai yang paling umum terjadi, paling parah dan sering terdeteksi oleh perangkat Angiography. Tapi nomor prioritas mungkin tidak secara akurat mencerminkan kegagalan karena sifatnya bervariasi dan kompleks dari proses evaluasi sebelumnya. Untuk mengatasi batasan ini maka dilakukan konfigurasi string fuzzy dengan sistem inferensi fuzzy berbasis pengetahuan. Metode ini memperkenalkan adanya indeks kesamaan yang memperhitungkan data yang bersifat kompleks dengan ketidakpastian. Penelitian ini berbentuk studi analisa, yang bertujuan untuk menerapkan FMEA dan Fuzzy untuk manajemen risiko pada alat Angiography yang digunakan di rumah sakit. Terdapat dua puluh tuju mode kegagalan potensial yang telah diidentifikasi dengan dua alat yang berbeda merk maupun spesifikasi. Kemudian mode kegagalan tersebut diprioritaskan berdasarkan system interference fuzzy. Hasil penelitiannya adalah didapatkan data prioritas risiko kegagalan pada metode Fuzzy-FMEA dan dapat dijadikan pertimbangan untuk mengembangkan pencegahan yang sesuai dengan langkah-langkah yang tepat agar dapat mengurangi kegagalan alat Angiography di masa depan. Kata Kunci : Angiography, Fuzzy Logic, FMEA. Failure Mode and Effects Analysis (FMEA) is a method that is widely used in engineering applications for the identification and assessment of the possibility of failure. In general or traditional, failure mode risk assessment is carried out using a risk priority number which is calculated based on the occurrence, severity and detection of the failure mode. The failure mode with the highest rating after this Analysis is considered the most common, severe and detected by the device, in general. But priority numbers may not accurately reflect failures due to the varied and complex nature of the evaluation process. To overcome this limitation, fuzzy string matching with knowledge-based fuzzy inference system is used. This method introduces similarity indexing which takes into account complex service data with great uncertainty. This research is in the form of a case study, which aims to apply FMEA and fuzzy FMEA for risk management on Angiography tools used in hospitals. There are twenty seven potential failure modes which have been identified among them in two different tools where the failure mode occurs in Angiography and is prioritized based on the fuzzy interference system. Finally, the priority of this failure risk in the FMEA-Fuzzy method can be considered to develop appropriate prevention measures to reduce future failures that can be used by users. Keywords: Angiography, Fuzzy Logic, FMEA
| Item Type: | Thesis (S2) |
|---|---|
| NIM/NIDN Creators: | 55418120008 |
| Uncontrolled Keywords: | Angiography, Fuzzy Logic, FMEA, Angiography, Fuzzy Logic, FMEA |
| Subjects: | 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 621 Applied Physics/Fisika terapan |
| Divisions: | Pascasarjana > Magister Teknik Elektro |
| Depositing User: | ORYZA LUVITA |
| Date Deposited: | 14 Apr 2022 03:37 |
| Last Modified: | 14 Apr 2022 03:49 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/59880 |
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