- Reclamation
- R&D
- Research Projects
- Predictive Maintenance Program – Research and development of a system to transfer and store secured data in support of a Reclamation-wide Predictive Maintenance Management program for power production assets
Predictive Maintenance Program – Research and development of a system to transfer and store secured data in support of a Reclamation-wide Predictive Maintenance Management program for power production assets
Project ID: 20108
Principal Investigator: Jim DeHaan
Research Topic: Improved Power Generation
Funded Fiscal Years:
2020,
2021 and
2022
Keywords: None
Research Question
The research goal is to support the development of a predictive maintenance management program for power assets
with an initial focus on secured data transfer and storage. Initial tasks to accomplish this goal are to demonstrate the
business case of implementing a predictive maintenance management program, assist in defining the broad scope
and components of the predictive maintenance program within Reclamation by identifying the data collection, transfer,
and storage system needed to support predictive maintenance and identify IT infrastructure and security requirements
for this system.
Need and Benefit
The development of a predictive maintenance program within Reclamation will provide the tools necessary to optimize
operation and maintenance activities within Reclamation. The predictive maintenance approach benefit over
Reclamation's current preventive maintenance program is that only maintenance tasks that are warranted based on
measured conditions are performed. A predictive maintenance program uses various data processing methods to
analyze data collected at powerplants to discover data trends. These data sets consist of condition-based data
collected across Reclamation including periodic monitored data, periodic testing results, and condition monitoring
data. Within Reclamation online condition monitoring data is very limited. While supervisory control and data
acquisition (SCADA) systems provide some of this function, its focus is plant control and not condition monitoring. The
inclusion of condition monitoring information will help provide the additional predictive monitoring data needed to begin
implementing predictive operation and maintenance practices.
Contributing Partners
Contact the Principal Investigator for information about partners.
Research Products
Please contact research@usbr.gov about research products related to this project.
