Plant configuration management is an essential element of nuclear power plant (NPP) design, construction, and operation. In the current operating model of NPPs, plant configuration management is highly dependent on large technical staffs. This dependency is because NPPs have a large number of systems and most operations are manually performed. Work processes tend to be fairly complex due to nuclear quality and documentation requirements. NPPs conduct a substantial number of ongoing surveillance activities to verify that plant components are in their required positions (open/close, on/off, etc.) for current and upcoming plant configuration. This puts nuclear energy at somewhat of a long-term economic disadvantage compared to non-nuclear energy generation sources with rising labor costs. Also, it presents human error opportunities, regulatory compliance impacts, and personnel safety hazards. Furthermore, some of these components are located in radiation control zones and result in dose to the surveillance personnel, thereby creating potential nuclear safety hazards. Technology can play a key role in NPP configuration management in offsetting labor costs by automating manually performed plant activities, such as determining the current state of equipment and process parameters. Alternatively, current NPP instrumentation and control systems are approaching their end-of-life and are facing age-related issues, which presents opportunity to upgrade the systems to reduce dependence on manual activities. This paper presents a proof-of-concept prototype intelligent plant configuration management system using available wireless component position sensors to help reduce operating costs for field-based component position verification activities as well as reduce operational challenges due to component position errors. The work focuses on position sensors for selected manual valve types. The wireless network implemented in this work is based on The Internet of Things network since it enables many different devices to communicate between each other across the same network. The proof-of-concept prototype presented in this paper would benefit the nuclear industry in several ways including reduced labor costs, reduced radiation dose, reduced nuclear and personnel safety challenges, and improved plant and regulatory performance.

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