Managing Operational Risk and Performance Drift as a Function of the “Nuclear Work Model” Open Access
Downloadable ContentDownload PDF View PDF in Browser Report an accessibility issue with this item
High Reliability Organizations are organizations that have fewer than the average number of high-consequence accidents. “Heinrich’s Law” states that the industrial average of the ratio of high-consequence accidents to total recordable accidents is 1:330. This represents an average of one high-consequence accident for every 330 recordable accidents. Therefore, to meet the criteria to be considered a High Reliability Organization, failure rate must be less than the industrial average presented in Heinrich’s ratio. “Mean Time Between Failures” is a system reliability metric representing the period a system remains operable before experiencing a system failure. (Blanchard, 2004) “Mean Accident Cycles Between Failures” (MABF) is a variation on MTBF and represents the number of accident cycles that occur between inherent system failures. It is expressed in units of “accident cycles” or the average interval of time between the occurrences of one recorded accident until the occurrence of the next recorded accident. The historical operational performance data collected over a two-year period for one real-world High Reliability Organization, based upon Admiral Hyman G. Rickover’s “Nuclear Work Model”, revealed the following four real-world problems:PROBLEM #1: Management is ineffective in the early detection of performance trends.PROBLEM #2: Management fails to investigate accidents thoroughly and provide in-depth causal analysis of identified performance trends. PROBLEM #3: No quantitative predictive model is utilized to estimate the optimal solution to correct identified performance trends. PROBLEM #4: Opportunities to prevent high-consequence accidents were missed because no quantitative predictive model was utilized to evaluate or trend performance “drift” within the organization. To evaluate and provide solutions to the problems above, two separate Monte Carlo Simulations were created to assess risk using Microsoft Excel™ SOLVER and Kaplan’s risk formula based upon “Operational Logs, Technical & Organizational Performance Data” (Si), Accident Frequency (λi), and Accident Severity (Xi). The establishment of metrics such as “Organizational Reliability Factor” (ORF), a ratio comparing organizational MABF to Heinrich’s industrial average, and the ratio of high-consequence accidents to recordable accidents are discussed as additional management indicators to evaluate organizational reliability. These metrics provide useful engineering management tools to evaluate the balance of Training, Procedures, and Supervision, which are the principal components of Rickover’s “Nuclear Work Model”. First Line Manager “span of control” and field assessments are used to evaluate the Supervision component of the “Nuclear Work Model”. However, for the purposes of this study, the “Training” and “Procedure” components of the model will be assumed constant and will not be considered.
Notice to Authors
If you are the author of this work and you have any questions about the information on this page, please use the Contact form to get in touch with us.