TY - GEN
T1 - Human factors principles in information dashboard design
AU - Hugo, Jacques V.
AU - St Germain, Shawn
N1 - Publisher Copyright:
© 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Refueling outages remain one of the largest opportunities for improving capacity factor and reducing costs available to commercial nuclear power plants. Although the nuclear industry has made steady improvement in outage optimization, each day of a refueling outage still represents an opportunity to save millions of dollars and each day an outage extends past its planned end date represents millions of dollars that may have been spent unnecessarily. Reducing planned outage duration or preventing outage extensions requires careful management of the outage schedule as well as constant oversight and monitoring of work completion during the outage execution. During a typical outage, there are typically more than 10,000 activities on the schedule that, if not managed efficiently, may cause expensive outage delays. Management of outages currently relies largely on paper-based resources and general-purpose office software. A typical method currently used to monitor work performance is a burn-down curve, where total remaining activities are plotted against the baseline schedule to track bulk work completion progress. While methods like this are useful, there is still considerable uncertainty during a typical outage whether bulk work progress is adequate and therefore a lot of management time is spent analyzing the situation on a daily basis. This paper is a case study of how new technology, in combination with established human-factors and user-centered design knowledge, can be used to support Outage Control Center (OCC) personnel decision making. In particular, we describe recent advances made in developing a framework for the design of visual outage information presentation, as well as an overview of the human factors principles that informed the development of the visualizations. To test the utility of advanced visual outage information presentation, an outage management dashboard software application was created as part of the Department of Energy's Advanced Outage Control Center project (AOCC). This dashboard is intended to present all the critical information an outage manager would need to understand the current status of a refueling outage. The dashboard presents the critical path, bulk work performance, key performance indicators, outage milestones and metrics relating current performance to historical performance. Additionally, the dashboard includes data analysis tools to allow outage managers to drill down into the underlying data to understand the drivers of the indicators.
AB - Refueling outages remain one of the largest opportunities for improving capacity factor and reducing costs available to commercial nuclear power plants. Although the nuclear industry has made steady improvement in outage optimization, each day of a refueling outage still represents an opportunity to save millions of dollars and each day an outage extends past its planned end date represents millions of dollars that may have been spent unnecessarily. Reducing planned outage duration or preventing outage extensions requires careful management of the outage schedule as well as constant oversight and monitoring of work completion during the outage execution. During a typical outage, there are typically more than 10,000 activities on the schedule that, if not managed efficiently, may cause expensive outage delays. Management of outages currently relies largely on paper-based resources and general-purpose office software. A typical method currently used to monitor work performance is a burn-down curve, where total remaining activities are plotted against the baseline schedule to track bulk work completion progress. While methods like this are useful, there is still considerable uncertainty during a typical outage whether bulk work progress is adequate and therefore a lot of management time is spent analyzing the situation on a daily basis. This paper is a case study of how new technology, in combination with established human-factors and user-centered design knowledge, can be used to support Outage Control Center (OCC) personnel decision making. In particular, we describe recent advances made in developing a framework for the design of visual outage information presentation, as well as an overview of the human factors principles that informed the development of the visualizations. To test the utility of advanced visual outage information presentation, an outage management dashboard software application was created as part of the Department of Energy's Advanced Outage Control Center project (AOCC). This dashboard is intended to present all the critical information an outage manager would need to understand the current status of a refueling outage. The dashboard presents the critical path, bulk work performance, key performance indicators, outage milestones and metrics relating current performance to historical performance. Additionally, the dashboard includes data analysis tools to allow outage managers to drill down into the underlying data to understand the drivers of the indicators.
KW - Dashboard
KW - Human factors engineering
KW - Human-system interface
KW - Nuclear power plant
KW - Outage control center
KW - Visual communication
UR - https://www.scopus.com/pages/publications/85047796338
M3 - Conference contribution
AN - SCOPUS:85047796338
T3 - 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
SP - 1315
EP - 1328
BT - 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
PB - American Nuclear Society
T2 - 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
Y2 - 11 June 2017 through 15 June 2017
ER -