Towards proper sampling and statistical modelling of defects

Ali Cetin (Corresponding Author), Andrew Roiko, M. Lind

    Research output: Contribution to journalArticleScientificpeer-review

    2 Citations (Scopus)

    Abstract

    Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.
    Original languageEnglish
    Pages (from-to)1056-1065
    JournalFatigue & Fracture of Engineering Materials & Structures
    Volume38
    Issue number9
    DOIs
    Publication statusPublished - 2015
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Sampling
    Defects
    Inspection

    Keywords

    • comprehensive method
    • standard practices
    • statistical modelling
    • statistics of extremes
    • steel cleanness

    Cite this

    @article{66496f6e196f455ba857f517df696402,
    title = "Towards proper sampling and statistical modelling of defects",
    abstract = "Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.",
    keywords = "comprehensive method, standard practices, statistical modelling, statistics of extremes, steel cleanness",
    author = "Ali Cetin and Andrew Roiko and M. Lind",
    year = "2015",
    doi = "10.1111/ffe.12317",
    language = "English",
    volume = "38",
    pages = "1056--1065",
    journal = "Fatigue & Fracture of Engineering Materials & Structures",
    issn = "8756-758X",
    number = "9",

    }

    Towards proper sampling and statistical modelling of defects. / Cetin, Ali (Corresponding Author); Roiko, Andrew; Lind, M.

    In: Fatigue & Fracture of Engineering Materials & Structures, Vol. 38, No. 9, 2015, p. 1056-1065.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Towards proper sampling and statistical modelling of defects

    AU - Cetin, Ali

    AU - Roiko, Andrew

    AU - Lind, M.

    PY - 2015

    Y1 - 2015

    N2 - Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.

    AB - Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.

    KW - comprehensive method

    KW - standard practices

    KW - statistical modelling

    KW - statistics of extremes

    KW - steel cleanness

    U2 - 10.1111/ffe.12317

    DO - 10.1111/ffe.12317

    M3 - Article

    VL - 38

    SP - 1056

    EP - 1065

    JO - Fatigue & Fracture of Engineering Materials & Structures

    JF - Fatigue & Fracture of Engineering Materials & Structures

    SN - 8756-758X

    IS - 9

    ER -