Segmentation of machines with RFM analysis: an evaluation based on maintenance and failure records

Kapalı Erişim

Tarih

2025

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer International Publishing AG

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

This study aims to evaluate the segmentation of machines based on maintenance and failure records using RFM (Recency, Frequency, Monetary) analysis. By analyzing the maintenance and failure data of the machines, the failure history of each machine has been examined. The main objective is to assess machine segmentation using parameters such as Failure Frequency, Total Failure Duration, and Last Failure Time. These parameters are integrated into the RFM analysis to understand the operational health of the machines and to determine the necessary strategies for preventing failures. The results facilitate the segmentation of machines and the development of tailored maintenance and improvement strategies for each segment. This study offers a data-driven approach to more accurately predict machine failure trends, optimize maintenance processes, improve operational efficiency, and reduce costs.

Açıklama

7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 --29-31 July 2025 -- Istanbul

Anahtar Kelimeler

Classification, Data Analysis, Predictive Maintenance, RFM Analysis

Kaynak

7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025

WoS Q Değeri

N/A

Scopus Q Değeri

Q4

Cilt

1531 LNNS

Sayı

Künye