Methods of data collection for online monitoring

In an effort to improve the economic viability of nuclear power plants, utilities must reduce the cost of preventive maintenance. Any change to the preventive maintenance strategy comes with some risk that equipment reliability could be negatively impacted. There are opportunities to reduce the risk of equipment failures through improved condition monitoring. Improved condition monitoring could be achieved through either (or both) increasing the amount and type of data collected or taking advantage of improved analytical techniques to extract better insights from the data. The goal is to minimize the total cost of maintenance by having a good understanding of and balance between the savings harvested by a reduction in preventive maintenance and the cost of increased equipment failures and the increased cost of additional monitoring. Idaho National Laboratory (INL) is working on a technology roadmap to assist plants in improving their monitoring capability. The objectives of this roadmap are to outline the steps that should be taken to ensure a utility has the necessary information and tools to properly assess the potential savings, costs, and risks associated with maintenance optimization efforts. One of the keys to the roadmap for setting up an optimized system includes an understanding of the data needed, how it is collected, stored, and made available for analysis. This paper outlines at a high level the typical data sources that will be used to make value-based maintenance decisions. For each of these data sources, there likely exists a current state of practice for collecting the data, an existing but more efficient method of collecting data, and a new but not yet developed method for collecting data. This paper will try and identify for each data source where these potential improvements are so utilities can decide where to apply resources to minimize the total cost of maintenance. Potential data sources to support condition monitoring that provide an opportunity to streamline the data collection or data storage to facilitate the collation of data to support improved analytics include; maintenance work orders, surveillance procedures, Operator logs, plant computer process parameters, vendor provided data, system engineers notebooks and corrective action program databases. This paper will discuss areas for improved data handling for several data sources.