Home > Research > Publications & Outputs > Exploring Equipment Electrocardiogram Mechanism...

Electronic data

  • 09088122

    Rights statement: ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Accepted author manuscript, 4.27 MB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Links

Text available via DOI:

View graph of relations

Exploring Equipment Electrocardiogram Mechanism for Performance Degradation Monitoring in Smart Manufacturing

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
Close
<mark>Journal publication date</mark>1/10/2020
<mark>Journal</mark>IEEE/ASME Transactions on Mechatronics
Issue number5
Volume25
Number of pages11
Pages (from-to)2276-2286
Publication StatusPublished
Early online date6/05/20
<mark>Original language</mark>English

Abstract

Similar to the use of electrocardiogram (ECG) for monitoring heartbeat, this article proposes an equipment electrocardiogram (EECG) mechanism based on fine-grained collection of data during the entire operating duration of the manufacturing equipment, with the purpose of the EECG to reveal the equipment performance degradation in smart manufacturing. First, the system architecture of EECG in smart manufacturing is constructed, and the EECG mechanism is explored, including the granular division of the duration of the production process, the matching strategy for process sequences, and several important working characteristics (e.g., baseline, tolerance, and hotspot). Next, the automatic production line EECG (APL-EECG) is deployed, to optimize the cycle time of the production process and to monitor the performance decay of the equipment online. Finally, the performance of the APL-EECG was validated using a laboratory production line. The experimental results have shown that the APL-EECG can monitor the performance degradation of the equipment in real-time and can improve the production efficiency of the production line. Compared with a previous factory information system, the APL-EECG has shown more accurate and more comprehensive understanding in terms of data for the production process. The EECG mechanism contributes to both equipment fault tracking and optimization of production process. In the long run, APL-EECG can identify potential failures and provide assistance in for preventive maintenance of the equipment.

Bibliographic note

©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.