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Application of Principle Component Analysis and logistic regression to support Six Sigma implementation in maintenance
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Rzeszow University of Technology, Poland
Poznan University of Technology, Poland
University of Minho, Portugal
University of Zielona Góra, Poland
Submission date: 2023-08-31
Final revision date: 2023-09-22
Acceptance date: 2023-10-28
Online publication date: 2023-11-01
Publication date: 2023-11-01
Corresponding author
Katarzyna Antosz   

Rzeszow University of Technology, Poland
Eksploatacja i Niezawodność – Maintenance and Reliability 2023;25(4):174603
  • A review of maintenance management’s importance.
  • A review of traditional and advanced analytical tools used in the DMAIC cycle.
  • The literature review related to the improvement of maintenance processes using the Six Sigma approach.
  • A Six Sigma methodology with PCA and logistic regression in maintenance processes.
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.
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