Applying Data Driven Approach to Cluster Components for Preventive Maintenance

Ping Yu Hsu, Hong Tsuen Lei, Ming Shien Cheng, Tzu Fan Yuan

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

McKone et al. (J Oper Manag 19:39–58, 2001) proposed Total Preventive maintenance (TPM), Just in time (JIT) and Total quality management (TQM) to contribute significantly to manufacturing performance (MP) and TPM could be considered as a part of the manufacturing strategy. The use of preventive maintenance in equipment maintenance could effectively reduce machine occurrence and reduce machine efficiency due to failure (Niu et al. in Reliab Eng Syst Saf 95:786–796, 2010; Panagiotidou and Tagaras in Eur J Oper Res 180:329–353, 2007; Swanson in Int J Prod Econ 70:237–244, 2001). Many studies in the past have applied the concept of total preventive maintenance (TPM) to equipment maintenance to reduce downtime and improve machine efficiency effectively (Panagiotidou and Tagaras in Eur J Oper Res 180:329–353, 2007; Swanson in Int J Prod Econ 70:237–244, 2001). Utilizing preventive maintenance can reduce machine’s shutdown and improve the equipment efficiency. The traditional total preventive maintenance methods focused on maintaining single component. The research, however, strives to maintain a group of components to further reduce the maintenance time. The components were clustered into group according to their distributions of lifespans. The clusters that saved the most maintenance costs are recommended to managers for maintenance scheduling. The methodology was applied to an auto component company for experiments. The results showed that OEE was improved from 81 to 84%.

Original languageEnglish
Title of host publicationLecture Notes in Production Engineering
PublisherSpringer Nature
Pages197-205
Number of pages9
DOIs
StatePublished - 2023

Publication series

NameLecture Notes in Production Engineering
VolumePart F1164
ISSN (Print)2194-0525
ISSN (Electronic)2194-0533

Keywords

  • Data driven methodology
  • Maintenance strategy
  • OEE
  • TPM

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