A collaborative model for predictive maintenance of after-sales equipment based on digital twin

Xiao Li, Hongfei Liang, Yuchen Chen, Yuanpeng Ruan and Lei Wang

European Journal of Industrial Engineering, 2023, vol. 17, issue 5, 795-831

Abstract: In response to the demands of users for prompting fault diagnosis and maintenance, equipment manufacturers require more advanced maintenance technologies for real-time monitoring, prediction, and remote guidance. Based on digital twin, this paper puts forward a seven-dimensional model of collaborative maintenance and a collaborative model for after sales maintenance service, which enables manufacturers to provide more effective and timely service and support to their customers. Taking a bottled water capping process as an example, it constructs a digital twin-driven model for predicting the remaining effective life of devices, a digital twin service platform with a maintenance knowledge database. Based on the forward variable combining the current state and state duration from hidden semi-Markov chain, and the improved formula for calculating the remaining effective life of equipment state, the feasibility of the proposed seven-dimensional collaborative maintenance model and the collaborative model for after sales maintenance service are verified. [Submitted: 20 July 2021; Accepted: 8 August 2022]

Keywords: digital twin; predictive maintenance; collaborative maintenance; hidden semi-Markov chain model; after-sales equipment. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=133174 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:eujine:v:17:y:2023:i:5:p:795-831

Access Statistics for this article

More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().