The Journal of Reliability Engineering Association of Japan

Online ISSN : 2424-2543
Print ISSN : 0919-2697
ISSN-L : 0919-2697

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Volume 41, Issue 2

Verification of Safety

Displaying 1-7 of 7 articles from this issue

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Safety Assurance for Artificial Intelligence System

Naoki ISHIHAMA, Masafumi KATAHIRA

2019 Volume 41 Issue 2 Pages 82-88
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_82

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On the Utilitiy of Combined Application of STAMP/STPA and Model Checking to Single Track Railroad Crossing

Kozo OKANO, Keishi OKAMOTO, Shinpei OGATA

2019 Volume 41 Issue 2 Pages 89-95
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_89

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Application of STAMP/STPA in Safety Analysis of Railway Signalling System

Takashi KAWANO

2019 Volume 41 Issue 2 Pages 96-102
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_96

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Increasing Safety for Future Systems

Yuko FUKUSHIMA, Yuji INOUE

2019 Volume 41 Issue 2 Pages 103-110
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_103

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Application of “Formal Method” for Railroad Signaling Products

Takeo IKEDA, Masami IWAMURA, Kenta KONAGAYA, Yoshijiro KONO

2019 Volume 41 Issue 2 Pages 111-115
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_111

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Life cycle costing in the Past 15/25/50 Years and Next Stages

Takeshi NATSUME

2019 Volume 41 Issue 2 Pages 116-125
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_116

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A structural analysis of emergent faults based on the visualization of automobile recall information using functional resonance analysis method

Shinji YOKOGAWA

2019 Volume 41 Issue 2 Pages 135-147
Published: 2019
Released on J-STAGE: February 03, 2022

DOIhttps://doi.org/10.11348/reajshinrai.41.2_135

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For systems that have complicated structures, the system faults depending on the emergence are frequently observed. This system fault by emergence is getting harder to describe and evaluate by using conventional risk analysis tools; e.g., FMEA and FTA. In this paper, automotive re-call information was investigated to evaluate the structure and characteristics of the system faults by emergence. Characteristics of the system faults are discussed based on visualization and quantification of the function resonances. The graphical modeling and the clustering analysis are used to investigate the structure of the system fault. The causes of the system fault are investigated by using the nominal logistic regression analysis to propose design strategies to suppress the system fault.

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