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.
CITATIONS(11):
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Advances in Manufacturing IV Paula Kolbusz, Katarzyna Antosz
Innovations in Mechanical Engineering III Szymon Wojciechowski, Justyna Trojanowska, Dariusz Bartkowski, Grzegorz M. Królczyk, Jolanta B. Królczyk, Radosław W. Maruda, Vitalii Ivanov
Evaluation and Comparison of Selected Machine Learning Methods for Improving Maintenance Processes Katarzyna Antosz, Monika Kulisz, Jozef Husar IFAC-PapersOnLine
The use of decision trees to identify the causes of failures in a medical enterprise - a case study Izabela Rojek, Małgorzata Jasiulewicz-Kaczmarek, Mariusz Piechowski, Dariusz Mikołajewski IFAC-PapersOnLine
Improving the efficiency of greasing operations with the lubrication management support system - a case study Mariusz Piechowski, Ryszard Wyczółkowski, Waldemar Paszkowski, Artur Meller IFAC-PapersOnLine
PCA Analysis of Resource Availability as One of the Inputs in the Process of Estimating the Length of Assembly Time for Complex Products Jolanta Brzozowska, Monika Kulisz, Arkadiusz Gola IFAC-PapersOnLine
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