This paper provides an update on an exploration of using empirically-developed equations (“models') to predict power plant performance from diverse antecedent conditions related to human performance. After covering background on the project approach and findings, recent results are discussed. Models in this second phase work were based on over 7 years of historical monthly data for operating and personnel conditions at one power plant, employing predictive lags of at least 4 months. Results were promising for several of the outcome measures studied. Strengths and limitations of the approach, and recommendations for future application, are discussed.
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