Nuclear Engineering Indicators - PMS

Our work aims to create a framework to analyze the organizational effectiveness of nuclear utilities. From the perspective of operational excellence, effective organizations attain “efficiency” and “reliability.” Efficiency results in increased levels of asset availability, and reliability results in a reduction in variation and disruption experienced by operational and maintenance processes. We assess efficiency and reliability from the “key performance indicators (KPIs) perspective,” critical to operational and maintenance assessment programs in nuclear utilities. KPIs are measurable performance indicators that are specific to a particular objective and are tracked over time. They serve as targets for teams to strive towards, milestones to track progress, and insights that aid decision-making across the organization (Bishop, 2018). We present KPIs from a causative standpoint of “leading” and “lagging” indicators. The former, often related to activities undertaken by employees, can predict the probable outcome of work in progress and help identify if any immediate corrective actions are required. While the latter refers to results indicators gathered only after an event has occurred, such as categories of financial and market-oriented indicators. Two sets of indicators may be connected by cause and effect (leading to pointing out something about lagging), but it does not mean a hierarchy exists; hence a KPI hierarchy was developed, taking into consideration similarities of indicators in order to relate the KPI into levels. The use of a KPI hierarchy in nuclear entities enables decision-makers to comprehend the significance and immediacy of addressing changes in specific KPI levels. Additionally, this study employed Canonical Correlation Analysis (CCA) to determine the quantitative causal relationship between each KPI both within and across different levels, thereby allowing for the identification of the impact of each level and KPI on the INPO Index, a performance reference indicator utilized in nuclear utilities, from a systems perspective. The findings of this analysis were compared with those of a multiple regression analysis (MRA). The advantage of having a systems approach is that the impacts will not be assessed from a single streamlined sequence but seen as a whole. We provide results or developmental updates for each of these steps. The data and information cited in this report are from a nuclear entity that we abbreviate as MNU (Major Nuclear Utility) in this document. Data treatment and a time series analysis were necessary to adjust the provided data and perform further analysis as MRA and CCA.