Risk Priority Assessment Using the FMEA Method in Level 3 and Level 4 Autonomous Vehicles

Elif Tuğba Güngör; Mustafa Kurt

Makale detayları

Risk Priority Assessment Using the FMEA Method in Level 3 and Level 4 Autonomous Vehicles

Yazarlar:

Elif Tuğba Güngör | Mustafa Kurt

Yayıncı:

Gazi University

Ana Başlıklar:

Otonom Araç Sistemleri | Otomotiv Mekatronik ve Otonom Sistemler | Çok Ölçütlü Karar Verme | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji Vol.13 Issue 2, pp.665-679

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001289890

pISSN:

2147-9526

Anahtar kelimeler:

Özet:

 Failure Mode and Effects Analysis FMEA is a technique that allows the identification of potential errors in the process by estimating the possible errors that may occur in an observed system, and the assessment of their possible effects, and then taking specific precautions for errors in certain areas and determining the necessary precautions. In FMEA application, scales with different evaluation criteria are created according to the parameters of probability P, severity S and detectability D and each of the error factors to be examined is subject to a value assignment to these parametric scales. By multiplying the values in question, the Risk Priority Number RPN is calculated for each error factor and the error factors are prioritized and ranked in order of importance in proportion to the RPNs. In this study, 614 accident report files kept by the U.S. NHTSA agency for vehicles with level 3 and level 4 autonomous driving systems ADS were used. Using the qualitative analysis approach on the cases recorded in the file, open coding information that was meaningful in terms of risk analysis was obtained. Then, these open codes were reviewed and the predictive codings I, S and T, which are the basic parameters of the FMEA analysis method, were created with axial coding and selective coding approaches, respectively. Afterwards, the statistics of the codes were calculated for each case. As a result of the qualitative analysis, it is seen that the risk factors are collected in three main dimensions according to the accident reports. The study analyzed the risk factors in these three main dimensions and sub-dimensions.

 Failure Mode and Effects Analysis FMEA is a technique that allows the identification of potential errors in the process by estimating the possible errors that may occur in an observed system, and the assessment of their possible effects, and then taking specific precautions for errors in certain areas and determining the necessary precautions. In FMEA application, scales with different evaluation criteria are created according to the parameters of probability P, severity S and detectability D and each of the error factors to be examined is subject to a value assignment to these parametric scales. By multiplying the values in question, the Risk Priority Number RPN is calculated for each error factor and the error factors are prioritized and ranked in order of importance in proportion to the RPNs. In this study, 614 accident report files kept by the U.S. NHTSA agency for vehicles with level 3 and level 4 autonomous driving systems ADS were used. Using the qualitative analysis approach on the cases recorded in the file, open coding information that was meaningful in terms of risk analysis was obtained. Then, these open codes were reviewed and the predictive codings I, S and T, which are the basic parameters of the FMEA analysis method, were created with axial coding and selective coding approaches, respectively. Afterwards, the statistics of the codes were calculated for each case. As a result of the qualitative analysis, it is seen that the risk factors are collected in three main dimensions according to the accident reports. The study analyzed the risk factors in these three main dimensions and sub-dimensions.

 Failure Mode and Effects Analysis FMEA is a technique that allows the identification of potential errors in the process by estimating the possible errors that may occur in an observed system, and the assessment of their possible effects, and then taking specific precautions for errors in certain areas and determining the necessary precautions. In FMEA application, scales with different evaluation criteria are created according to the parameters of probability P, severity S and detectability D and each of the error factors to be examined is subject to a value assignment to these parametric scales. By multiplying the values in question, the Risk Priority Number RPN is calculated for each error factor and the error factors are prioritized and ranked in order of importance in proportion to the RPNs. In this study, 614 accident report files kept by the U.S. NHTSA agency for vehicles with level 3 and level 4 autonomous driving systems ADS were used. Using the qualitative analysis approach on the cases recorded in the file, open coding information that was meaningful in terms of risk analysis was obtained. Then, these open codes were reviewed and the predictive codings I, S and T, which are the basic parameters of the FMEA analysis method, were created with axial coding and selective coding approaches, respectively. Afterwards, the statistics of the codes were calculated for each case. As a result of the qualitative analysis, it is seen that the risk factors are collected in three main dimensions according to the accident reports. The study analyzed the risk factors in these three main dimensions and sub-dimensions.

 Hata Türü ve Etkileri Analizi FMEA, gözlemlenen bir sistemde gerçekleşmesi muhtemel hataların tahmin edilerek, süreçteki potansiyel hataların tanımlanması ile bunların muhtemel etkilerinin değerlendirilmesine müteakip belirli alanlarda hataya özgün önlem alınmasını ve gerekli tedbirlerin belirlenmesini sağlayan bir tekniktir. FMEA uygulamasında, ihtimal İ, şiddet düzeyi Ş ve tespit edilebilirlik T parametrelerine göre farklı değerlendirme kriterlerine sahip ölçekler oluşturulmakta ve incelenecek hata faktörlerinin her biri bu parametrik ölçeklere bir değer atamasına tabi tutulmaktadır. Söz konusu değerlerin çarpılmasıyla he bir hata faktörü için Risk Öncelik Değeri RÖD hesaplanmakta ve hata faktörleri RÖDler nispetinde öncelik ve önem sırasına sokulmaktadır. Bu çalışmada seviye 3 ve seviye 4 otonom sürüş sistemlerine ADS sahip araçlar için A.B.D.ye bağlı NHTSA kurumu tarafınca tutulmuş 614 kaza raporu dosyası kullanılmıştır. Dosyada kayıtlı olan vakalar nitel analiz yaklaşımı kullanılarak risk analizi bakımından anlamlı olan açık kodlama bilgileri elde edilmiştir. Daha sonra bu açık kodlar tekrar gözden geçirilerek sırasıyla eksensel kodlama ve seçici kodlama yaklaşımları ile FMEA analizi yönteminin temel parametreleri olan İ, Ş ve T tahmini kodlamaları oluşturulmuştur. Sonrasında da her bir vaka için kodların istatistiği hesaplanmıştır. Yapılan nitel analiz sonucunda kaza raporlarına göre risk faktörlerinin üç ana boyutta toplandığı görülmektedir. Çalışma ile bu üç ana boyut ve alt boyuttaki risk faktörlerinin analizi yapılmıştır.

Makale detayları

Risk Priority Assessment Using the FMEA Method in Level 3 and Level 4 Autonomous Vehicles

Yazarlar:

Elif Tuğba Güngör | Mustafa Kurt

Yayıncı:

Gazi University

Ana Başlıklar:

Otonom Araç Sistemleri | Otomotiv Mekatronik ve Otonom Sistemler | Çok Ölçütlü Karar Verme | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji Vol.13 Issue 2, pp.665-679

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001289890

pISSN:

2147-9526

Autonomous vehicles

Risk analysis

Failure mode and effects analysis (FMEA)

Autonomy levels

NHTSA.Otonom araçlar

Risk analizi

Hata türü ve etkileri analizi (FMEA)

Otonomi seviyeleri

NHTSA.

Sayı

Makale detayları

Yazarlar: Elif Tuğba Güngör | Mustafa Kurt

Yayıncı: Gazi University

Ana Başlıklar: Otonom Araç Sistemleri | Otomotiv Mekatronik ve Otonom Sistemler | Çok Ölçütlü Karar Verme | Endüstri Mühendisliği

Dergi: Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji Vol.13 Issue 2, pp.665-679

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001289890

pISSN: 2147-9526

Sayı

Yazarlar:

Elif Tuğba Güngör | Mustafa Kurt

Yayıncı:

Gazi University

Ana Başlıklar:

Otonom Araç Sistemleri | Otomotiv Mekatronik ve Otonom Sistemler | Çok Ölçütlü Karar Verme | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji Vol.13 Issue 2, pp.665-679

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001289890

pISSN:

2147-9526