Abstract
As technology shifts from analog to digital in the nuclear power plant (NPP) main control room (MCR), it is important to look into the concept of mutual awareness. As control rooms use teams consisting of at least two reactor operators (ROs) and one senior reactor operator (SRO) to monitor and operate the plant, they depend on efficient teamwork in this collaborative environment. To successfully perform interdependent tasks, achieve their shared goals and high levels of coordination, each crew member has to maintain mutual awareness between each other. Collaboration is more efficient and effective when a high level of mutual awareness is maintained. Being able to evaluate and measure mutual awareness will provide us with the construct for assessing the presence and changes in mutual awareness during the technology shift in NPP MCR. This paper investigates the opportunities to develop a mutual awareness survey based on the mutual awareness model.
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The opinions expressed in this paper are entirely those of the author and do not represent official position. This work of authorship was prepared as an account of work sponsored by Idaho National Laboratory, an agency of the United States Government. Neither the United States Government, nor any agency thereof, nor any of their employees makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately-owned rights. Idaho National Laboratory is a multi-program laboratory operated by Battelle Energy Alliance LLC, for the United States Department of Energy under Contract DE-AC07-05ID14517. This research was funded through the Laboratory Directed Research and Development program at Idaho National Laboratory.
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Savchenko, K., Medema, H., Boring, R., Ulrich, T. (2019). Measuring Mutual Awareness for Digital Human-Machine Interfaces: A Questionnaire for Simulator Studies. In: Boring, R. (eds) Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2018. Advances in Intelligent Systems and Computing, vol 778. Springer, Cham. https://doi.org/10.1007/978-3-319-94391-6_4
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