Abstract
With the shift of manufacture to mainland China, the utility and building services industries in Hong Kong have become dominant. To ensure adherence to proper routine operations and the provision of quality services, the equipment of these sectors must be maintained in good condition. The results of a recently conducted survey indicate that equipment failure-driven and time-based maintenance are most commonly used in Hong Kong. Only a few companies use condition-based preventive maintenance. This paper presents an overview of maintenance practice in Hong Kong, and introduces the novel concept of intelligent predictive maintenance. In this maintenance system, the seriousness of the damage that is caused by faults in equipment can be determined, and the remnant life of the defective equipment can be predicted. Moreover, the system can automatically schedule maintenance activities in an efficient manner. With such abilities in equipment prognosis and automatic maintenance scheduling, the "fire-fighting" situations that often occur in failure-driven and time-based maintenance can be avoided. Hence, any waste of resources and loss of production that are due to the mismanagement of maintenance can be substantially reduced.
| Original language | English |
|---|---|
| Pages (from-to) | 369-380 |
| Journal | Journal of Quality in Maintenance Engineering |
| Volume | 8 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2002 |
Research Keywords
- Equipment
- Hong Kong
- Maintenance
- Neural networks
- Scheduling
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