A data-informed PIF hierarchy for model-based Human Reliability Analysis

This paper addresses three problems associated with the use of Performance Shaping Factors in Human Reliability Analysis. (1) There are more than a dozen Human Reliability Analysis (HRA) methods that use Performance Influencing Factors (PlFs) or Performance Shaping Factors (PSFs) to model human performance, but there is not a standard set of PlFs used among the methods, nor is there a framework available to compare the PlFs used in various methods. (2) The PlFs currently in use are not defined specifically enough to ensure consistent interpretation of similar PlFs across methods. (3) There are few rules governing the creation, definition, and usage of PIF sets. This paper introduces a hierarchical set of PlFs that can be used for both qualitative and quantitative HRA. The proposed PIF set is arranged in a hierarchy that can be collapsed or expanded to meet multiple objectives. The PIF hierarchy has been developed with respect to a set fundamental principles necessary for PIF sets, which are also introduced in this paper. This paper includes definitions of the PlFs to allow analysts to map the proposed PlFs onto current and future HRA methods. The standardized PIF hierarchy will allow analysts to combine different types of data and will therefore make the best use of the limited data in HRA. The collapsible hierarchy provides the structure necessary to combine multiple types of information without reducing the quality of the information. (c) 2012 Elsevier Ltd. All rights reserved.