Intelligent Predictive Maintenance (IPdM) for Elevator Service- Through CPS, IOT&S and Data Mining
Authors
Kesheng Wang, Guohong Dai, Lanzhong Guo
Corresponding Author
Kesheng Wang
Available Online November 2016.
- DOI
- https://doi.org/10.2991/iwama-16.2016.1How to use a DOI?
- Keywords
- Industry 4.0; CPS; IOT&S; Big data/ Data Mining; Elevator service; Smart elevator
- Abstract
- With the rapid economic growth and urbanization development, most of elevator production and service companies have completely changed their service policy opting to eliminate the standard preventive service policy. They now provide some form of predictive service policy and emphasize that they utilize remote monitoring of elevators to detect faults and estimate when components may need to be maintained due to actual usage. However, most of them are not true predictive maintenance policy. They merely a preventive, slightly enhanced, usage-based program. What is the future of elevator production and service companies? This paper will challenge the word "predictive maintenance" and present the framework of intelligent predictive maintenance system for smart elevator service based on industry 4.0 concepts.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Kesheng Wang AU - Guohong Dai AU - Lanzhong Guo PY - 2016/11 DA - 2016/11 TI - Intelligent Predictive Maintenance (IPdM) for Elevator Service- Through CPS, IOT&S and Data Mining BT - 6th International Workshop of Advanced Manufacturing and Automation PB - Atlantis Press SN - 2352-5428 UR - https://doi.org/10.2991/iwama-16.2016.1 DO - https://doi.org/10.2991/iwama-16.2016.1 ID - Wang2016/11 ER -