Statistical Failure Theory

Statistical Failure Theory is a formal analytical framework within the domain of failure theories that employs statistical methods to quantify and predict the probability of material or system failure under uncertain or variable conditions.

195

Publications

13.9K

Citations

430

Authors

235

Institutions

Publications per year

2017–2026

29

Authors

430

  1. BW
    B. W. Rosen

    General Electric (Czechia), Czechia

    3 publications · 385 citations

    3

    h-index

  2. ND
    Nozer D. Singpurwalla

    George Washington University, United States

    3 publications · 1.7K citations

    3

    h-index

  3. RR
    Robert R. Seghi

    The Ohio State University, United States

    3 publications · 61 citations

    3

    h-index

  4. NK
    N. Katsube

    The Ohio State University, United States

    3 publications · 61 citations

    3

    h-index

  5. ES
    E. Suhir

    AT&T (United States), United States

    3 publications · 57 citations

    3

    h-index

1–5 of 430

Venues

  1. IEEE Transactions on Reliability

    14 publications · 487 citations

    12

    h-index

  2. Journal of the American Statistical Association

    10 publications · 2.7K citations

    10

    h-index

  3. Technometrics

    8 publications · 360 citations

    8

    h-index

  4. Reliability Engineering & System Safety

    5 publications · 315 citations

    5

    h-index

  5. International Journal of Fracture

    5 publications · 122 citations

    5

    h-index

1–5