Abstract
Power distribution system (PDS) of data center has designed for high reliability and fault tolerance by deploying a redundant topology. Optimal data center reliability requires 4 principals which consist of topology design by standard; reliable components or mean time between failures (MTBF); real-time monitoring by data center infrastructure management (DCIM); and preventive maintenance through data center operations. However, data center needs more proper operations and maintenance approach to avoid planned and unplanned downtime. The best practice for data center operations management should be applied predictive maintenance or condition-based maintenance (CBM) to monitoring of critical components and systems. These processes will ensure that the system parameters will perform on their functions, and estimate remaining useful life of components for critical mission. Time-based maintenance (TBM) (preventive maintenance) has been applies for supplementary PDS components that define as not mission critical systems. This research proposes a model of preventive and predictive maintenance (PPM) for PDS of data center, which has been verified to improve maintenance efficiency and reduce operating costs of repair time and inventory. How to identify potential problems in early state before component and system failures are the key to prevent planed and unplanned downtime.
Highlights
Any system fault of data center is decreasing in total system performance when consider with the minimum requirements of system specification
All data collection had recorded through Data Center Infrastructure Management (DCIM) system for define set-point or condition-based maintenance (CBM) of each critical device and system to prevent potential failure or P-F Curve
System uptime is momentous for the success of mission crucial for data center business
Summary
Any system fault of data center is decreasing in total system performance when consider with the minimum requirements of system specification. It is a useful mechanism of strategic approach for preventive maintenance that collaborates with monitoring and controlling conditions of critical devices and equipment parameters. This process will operate in order to predict device failure, to assess the RUL, and to avoid system risks, which could be happened if minimum conditions are exceeded. This strategy demonstrates the economical savings over observation of lessons or timebased preventive maintenance, because exertion will execute only when guaranteed.
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