Knowledge-Based Improvement of Machine Downtime Management for IR4.0
Unplanned machine downtime interrupts operations in manufacturing plants leading to loss. Preventive measures can reduce the downtime to as low as reasonably possible thorough planned downtime management. This paper presents a knowledge-based framework to capture and reuse maintenance record for dow...
| Main Authors: | Yew, K.-H., Foong, O.-M., Sivarajan, T.P. |
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| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.23531 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084293649&doi=10.1109%2fICCSCE47578.2019.9068584&partnerID=40&md5=38cb49b30e0a30d567b1f1ba376aaaee http://eprints.utp.edu.my/23531/ |
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| Summary: |
Unplanned machine downtime interrupts operations in manufacturing plants leading to loss. Preventive measures can reduce the downtime to as low as reasonably possible thorough planned downtime management. This paper presents a knowledge-based framework to capture and reuse maintenance record for downtime management. A prototype was developed based on actual scenario and was assessed by experienced operators, technicians and engineers. The result of the evaluation contributes to better understanding of system requirements and design for knowledge driven Computerised Maintenance Management System. © 2019 IEEE. |
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