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Abstract
An escalator's refurbishment is usually linked with its design life as recommended by the manufacturer. However, the actual useful life of an escalator should be determined by its operating condition, which is affected by the runtime, workload, maintenance quality and vibration, rather than age only. The objective of this project is to develop a comprehensive health condition analytic system for quality management of escalators to support refurbishment decisions. This quality management system consists of the following four parts: (1) online data gathering and processing; (2) a dashboard for condition monitoring; (3) a health index model and (4) remaining useful life (RUL) prediction. The results can be used for (a) predicting the RUL of the escalators, in order to support asset replacement planning and (b) monitoring the real-time condition of escalators; including alerts when vibration exceeds the threshold and signal diagnosis, giving an indication of possible root cause (components) of the alert signal. © 2025 The Author(s).
| Original language | English |
|---|---|
| Pages (from-to) | 3746-3758 |
| Journal | Quality and Reliability Engineering International |
| Volume | 41 |
| Issue number | 8 |
| Online published | 3 Sept 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Funding
The work in this paper was supported by a grant from the Innovation and Technology Fund (ref: PRP-008-20FX) and MTR Corporation Limited. This work is related to Hong Kong Short-Term Patent Application No.32023068734.7.
Research Keywords
- condition-based maintenance
- data-driven quality
- escalator
- quality management
- remaining useful life
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
Fingerprint
Dive into the research topics of 'Remaining Useful Life Modelling With an Escalator Health Condition Analytic System'. Together they form a unique fingerprint.Projects
- 1 Finished
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ITF: Escalator Health Condition Analytic Model
ZWETSLOOT, I. (Principal Investigator / Project Coordinator) & TSUI, K. L. (Co-Investigator)
1/11/20 → 31/07/23
Project: Research
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