Faizah, Nova Auliyarul (2024) Penentuan Safety Integrity Level (SIL) pada Safety Instrumented System Air Compressor Berdasarkan Nilai Probability Failure on Demand (PFD) dengan Metode K-Nearest Neighbor. Diploma thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Terdapat adanya resiko berbahaya yang dapat terjadi pada air compressor, sehingga diperlukan adanya suatu sistem pengamanan. Sistem pengamanan ini dibangun untuk diimplementasikan pada air compressor, dimana sistem ini mendapat sinyal dari field berupa push button dan output dari transmitter yang terdiri dari pressure, vibration dan temperature. Kinerja dari Safety Instrumented System (SIS) dapat dilihat dari tingkat integrasi keselamatan atau Safety Integrity Level (SIL) saat menjalankan fungsinya. Parameter untuk mengetahui tingkat SIL yaitu Probability Failure on Demand (PFD) dan Risk Reduction Factor (RRF). Oleh karena itu, pada proyek akhir ini dilakukan perhitungan Safety Integrity Level pada Safety Instrumented System Air Compressor berdasarkan algoritma K-Nearest Neighbor (KNN). Klasifikasi tingkat SIL ini berdasarkan nilai PFD dan RRF yang telah dihitung sebelumnya. KNN akan mengklasifikasikan data berdasarkan ukuran kesamaan atau fungsi jarak. Metode KNN terbukti memiliki akurasi yang tinggi sebesar 100% dalam mengklasifikasikan SIL dengan proporsi perbandingan data training dan data testing sebesar 80%:20%. Dengan nilai k=6, KNN memiliki akurasi tertinggi dibandingkan dengan nilai k lainnya. Evaluasi yang dilakukan dengan membandingkan kinerja KNN dengan metode penentuan SIL lainnya, ditemukan bahwa K-NN memiliki keunggulan dalam hal efisiensi dan akurasi. Sehingga dapat disimpulkan bahwa model KNN menawarkan solusi yang lebih baik dan praktis dalam penentuan tingkat SIL dibandingkan dengan model klasifikasi lainnya.
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A dangerous risk can occur in an air compressor, so a security system is needed. This security system is built to be implemented on an air compressor, where this system gets a signal from the field in the form of a push button and output from a transmitter consisting of pressure, vibration, and temperature. The performance of the Safety Instrumented System (SIS) can be seen from the level of safety integration or Safety Integrity Level (SIL) when carrying out its function. The parameters to determine the SIL level are Probability Failure on Demand (PFD) and Risk Reduction Factor (RRF). Therefore, in this final project, the calculation of the Safety Integrity Level on the Safety Instrumented System Air Compressor based on the K-Nearest Neighbor (KNN) algorithm is carried out. This SIL level classification is based on the PFD and RRF values that have been calculated previously. KNN will classify data based on a similar measure or distance function. The KNN method has been proven to have a high accuracy of 100% in classifying SIL, with a proportion of training data and a testing data ratio of 80%: 20%. With a value of k=6, KNN has the highest accuracy compared to other k values. Evaluation conducted by comparing the performance of KNN with other SIL determination methods found that K-NN has advantages in terms of efficiency and accuracy. So, it can be concluded that the KNN model offers a better and practical solution for SIL determination.
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | K-Nearest Neighbor, Safety Instrumented System, Safety Integrity Level. |
| Subjects: | T Technology > T Technology (General) > T55 Industrial Safety T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T57.8 Nonlinear programming. Support vector machine. Wavelets. Hidden Markov models. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK152.A75 Electrical engineering--Safety measures T Technology > TS Manufactures > TS174 Maintainability (Engineering) . Reliability (Engineering) |
| Divisions: | Faculty of Vocational > 36304-Automation Electronic Engineering |
| Depositing User: | Nova Auliyarul Faizah |
| Date Deposited: | 21 Aug 2024 05:05 |
| Last Modified: | 21 Aug 2024 05:05 |
| URI: | http://repository.its.ac.id/id/eprint/115480 |
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