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Application of Principle Component Analysis and logistic regression to support Six Sigma implementation in maintenance


[ 1 ] Instytut Inżynierii Bezpieczeństwa i Jakości, Wydział Inżynierii Zarządzania, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[6.6] Management and quality studies

Year of publication


Published in

Eksploatacja i Niezawodność – Maintenance and Reliability

Journal year: 2023 | Journal volume: vol. 25 | Journal number: no. 4

Article type

scientific article

Publication language


  • maintenance management
  • Six Sigma generation
  • PCA
  • logistic regression

EN Improving the efficiency of maintenance processes is one of the goals of companies. Improvement activities in this area require not only an appropriate maintenance strategy but also the use of a new approach to increase the efficiency of the process. This article focuses on using Six Sigma (SS) to improve maintenance processes. As an introduction, the generations of SS development are identified, and traditional and advanced analytical tools that can be useful in SS projects are reviewed. As part of the research, an example of the implementation of the SS project in the maintenance process using the DMAIC and selected advanced analytical methods, such as PCA and logistic regression, was presented. The PCA results showed that it was enough to have seven main components to keep about 84% of the information on variability. In developed logistic regression explained the impact of the individual factors affecting the availability of the machines. The identified factors and their interactions made it possible to define maintenance activities requiring improvements.

Pages (from - to)

174603-1 - 174603-20





Article number: 174603

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Full text of article

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Ministry points / journal


Impact Factor

2,5 [List 2022]

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