---
_id: '11348'
abstract:
- lang: eng
  text: Lifetime is an important feature defining the reliability of electrical connectors.
    In general practice, the lifetime tests required for reliability estimation are
    time and labor intensive. In our previous work, a data driven method using a statistical
    process, with an application of probability distributions such as standard normal
    distribution and generalized extreme value (GEV) distribution with negative skewness
    to predict degradation paths, was introduced for estimation of the lifetime and
    FIT rate with the help of electrical contact resistance data collected from short
    term tests. The proposed method proved its significance by showing the possibility
    of drastic reduction in the lifetime test duration required for reliability determination.
    In this work, a non-parametric distribution free method using percentiles of actual
    measured contact resistances is used for determining the lifetime as against the
    percentiles of probability distribution used in previous work, thereby simplifying
    the process further and leading to an even more precise estimation. The lifetimes
    calculated from parametric and non-parametric methods are compared to highlight
    the significance of distribution free method in reliability estimation.
article_number: '115216'
article_type: original
author:
- first_name: Abhay Rammurti
  full_name: Shukla, Abhay Rammurti
  id: '74188'
  last_name: Shukla
- first_name: Robert
  full_name: Martin, Robert
  last_name: Martin
- first_name: Roman
  full_name: Probst, Roman
  id: '69156'
  last_name: Probst
- first_name: Jian
  full_name: Song, Jian
  id: '5297'
  last_name: Song
citation:
  ama: Shukla AR, Martin R, Probst R, Song J. Comparison of different statistical
    methods for prediction of lifetime of electrical connectors with short term tests.
    <i>Microelectronics Reliability</i>. 2023;150. doi:<a href="https://doi.org/10.1016/j.microrel.2023.115216">10.1016/j.microrel.2023.115216</a>
  apa: Shukla, A. R., Martin, R., Probst, R., &#38; Song, J. (2023). Comparison of
    different statistical methods for prediction of lifetime of electrical connectors
    with short term tests. <i>Microelectronics Reliability</i>, <i>150</i>, Article
    115216. <a href="https://doi.org/10.1016/j.microrel.2023.115216">https://doi.org/10.1016/j.microrel.2023.115216</a>
  bjps: <b>Shukla AR <i>et al.</i></b> (2023) Comparison of Different Statistical
    Methods for Prediction of Lifetime of Electrical Connectors with Short Term Tests.
    <i>Microelectronics Reliability</i> <b>150</b>.
  chicago: Shukla, Abhay Rammurti, Robert Martin, Roman Probst, and Jian Song. “Comparison
    of Different Statistical Methods for Prediction of Lifetime of Electrical Connectors
    with Short Term Tests.” <i>Microelectronics Reliability</i> 150 (2023). <a href="https://doi.org/10.1016/j.microrel.2023.115216">https://doi.org/10.1016/j.microrel.2023.115216</a>.
  chicago-de: Shukla, Abhay Rammurti, Robert Martin, Roman Probst und Jian Song. 2023.
    Comparison of different statistical methods for prediction of lifetime of electrical
    connectors with short term tests. <i>Microelectronics Reliability</i> 150. doi:<a
    href="https://doi.org/10.1016/j.microrel.2023.115216">10.1016/j.microrel.2023.115216</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Shukla, Abhay Rammurti</span>
    ; <span style="font-variant:small-caps;">Martin, Robert</span> ; <span style="font-variant:small-caps;">Probst,
    Roman</span> ; <span style="font-variant:small-caps;">Song, Jian</span>: Comparison
    of different statistical methods for prediction of lifetime of electrical connectors
    with short term tests. In: <i>Microelectronics Reliability</i> Bd. 150. Amsterdam,
    Elsevier  (2023)'
  havard: A.R. Shukla, R. Martin, R. Probst, J. Song, Comparison of different statistical
    methods for prediction of lifetime of electrical connectors with short term tests,
    Microelectronics Reliability. 150 (2023).
  ieee: 'A. R. Shukla, R. Martin, R. Probst, and J. Song, “Comparison of different
    statistical methods for prediction of lifetime of electrical connectors with short
    term tests,” <i>Microelectronics Reliability</i>, vol. 150, Art. no. 115216, 2023,
    doi: <a href="https://doi.org/10.1016/j.microrel.2023.115216">10.1016/j.microrel.2023.115216</a>.'
  mla: Shukla, Abhay Rammurti, et al. “Comparison of Different Statistical Methods
    for Prediction of Lifetime of Electrical Connectors with Short Term Tests.” <i>Microelectronics
    Reliability</i>, vol. 150, 115216, 2023, <a href="https://doi.org/10.1016/j.microrel.2023.115216">https://doi.org/10.1016/j.microrel.2023.115216</a>.
  short: A.R. Shukla, R. Martin, R. Probst, J. Song, Microelectronics Reliability
    150 (2023).
  ufg: '<b>Shukla, Abhay Rammurti u. a.</b>: Comparison of different statistical methods
    for prediction of lifetime of electrical connectors with short term tests, in:
    <i>Microelectronics Reliability</i> 150 (2023).'
  van: Shukla AR, Martin R, Probst R, Song J. Comparison of different statistical
    methods for prediction of lifetime of electrical connectors with short term tests.
    Microelectronics Reliability. 2023;150.
date_created: 2024-04-18T08:55:38Z
date_updated: 2025-06-26T07:51:25Z
department:
- _id: DEP6012
doi: 10.1016/j.microrel.2023.115216
external_id:
  isi:
  - '001106942700001'
has_accepted_license: '1'
intvolume: '       150'
isi: '1'
keyword:
- Electrical and Electronic Engineering
- Surfaces
- Coatings and Films
- Safety
- Risk
- Reliability and Quality
- Condensed Matter Physics
- Atomic and Molecular Physics
- and Optics
- Electronic
- Optical and Magnetic Materials
language:
- iso: eng
place: Amsterdam
publication: Microelectronics Reliability
publication_identifier:
  issn:
  - 0026-2714
  unknown:
  - 1872-941X
publication_status: published
publisher: 'Elsevier '
status: public
title: Comparison of different statistical methods for prediction of lifetime of electrical
  connectors with short term tests
type: scientific_journal_article
user_id: '83781'
volume: 150
year: '2023'
...