Process-Specific Adoption of Predictive Maintenance: A Qualitative Comparative Analysis in Manufacturing
- Authors
- Kim, Youngja; Choi, Gyunghyun
- Issue Date
- Dec-2023
- Publisher
- Success Culture Press
- Keywords
- failure analysis; intelligent manufacturing; maintenance system; predictive maintenance; preventive maintenance
- Citation
- Journal of System and Management Sciences, v.14, no.1, pp 502 - 514
- Pages
- 13
- Indexed
- SCOPUS
- Journal Title
- Journal of System and Management Sciences
- Volume
- 14
- Number
- 1
- Start Page
- 502
- End Page
- 514
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/204033
- DOI
- 10.33168/JSMS.2024.0129
- ISSN
- 1816-6075
1818-0523
- Abstract
- Predictive maintenance systems offer manufacturing enterprises opportunities to reduce costs and maximize productivity through data-driven insights into equipment failures. This study analyzes the adoption of predictive maintenance across six equipment assembly processes through an in-depth, multi-case methodology. Semi-structured interviews with maintenance managers elucidated nuances across processes contingent on vendor ownership models, facility lifecycles, and technical intricacy. Although processes evidenced expansions in predictive oversight through amplified data flows, persistent constraints arose regarding component lifespans, data limitations, and developing capable talent. Proactive management was partial rather than comprehensive. Strategic integration of robust failure mode analytics upgraded monitoring infrastructure, and bolstered personnel competencies will actualize the potential of predictive maintenance.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 기술경영전문대학원 > 서울 기술경영학과 > 1. Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.