PreprintArticleVersion 1This version is not peer-reviewed
Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks
Version 1
: Received: 10 August 2024 / Approved: 12 August 2024 / Online: 12 August 2024 (12:33:57 CEST)
How to cite:
ichsan, M. M. Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks. Preprints2024, 2024080808. https://doi.org/10.20944/preprints202408.0808.v1
ichsan, M. M. Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks. Preprints 2024, 2024080808. https://doi.org/10.20944/preprints202408.0808.v1
ichsan, M. M. Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks. Preprints2024, 2024080808. https://doi.org/10.20944/preprints202408.0808.v1
APA Style
ichsan, M. M. (2024). Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks. Preprints. https://doi.org/10.20944/preprints202408.0808.v1
Chicago/Turabian Style
ichsan, M. M. 2024 "Optimizing Baseline Interval Maintenance Strategies for Centrifugal Compressors with Electrical Motor Drivers Using Weibull Analysis Approach, Rank Regression, Fisher Matrix, and Median Ranks" Preprints. https://doi.org/10.20944/preprints202408.0808.v1
Abstract
This paper investigates optimal maintenance strategies for centrifugal compressors with electrical motor drivers using a Weibull analysis approach combined with rank regression, Fisher matrix, and median ranks. By leveraging data from Oreda 6, the study proposes a methodology to establish baseline intervals for corrective, preventive, predictive, and proactive maintenance in the absence of comprehensive historical data. The analysis reveals key Weibull parameters, including shape and scale factors, and calculates reliability metrics such as the mean time to failure (MTTF) and mean remaining life (MRL). The results suggest effective maintenance intervals and highlight the utility of Weibull analysis in enhancing maintenance strategies. This approach offers a robust framework for optimizing maintenance practices, even with limited historical data.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
