FRamework Assessing Notorious Contributing Influences for Error (FRANCIE).

Abstract

FRamework Assessing Notorious Contributing Influences for Error (FRANCIE) is a framework and methodology for the systematic analysis, characterization, and prediction of human error. It was developed in a NASA Advanced Concepts Project by Idaho National Engineering and Environmental Laboratory, NASA Ames Research Center, Boeing, and America West Airlines, with input from United Airlines and Idaho State University. It was hypothesized that development of a comprehensive taxonomy of error-type and contributing-influences, in a framework and methodology addressing issues important for error analysis, would result in a useful tool for human error analysis. The development method included capturing expertise of human factors and domain experts in the framework, and ensuring that the approach addressed issues important for future human error analysis. This development resulted in creation of a FRANCIE taxonomy for airline maintenance, and a FRANCIE framework and approach that addresses important issues: proactive and reactive, comprehensive error-type and contributing-influences taxonomy, meaningful error reduction strategies, multilevel analyses, multiple user types, compatible with existing methods, applied in design phase or throughout system life cycle, capture of lessons learned, and ease of application. FRANCIE was designed to apply to any domain, given taxonomy refinement. This is demonstrated by its application for an aviation operations scenario for a new precision landing aid. Representative error-types and contributing-influences, two example analyses, and a case study are presented. In conclusion, FRANCIE is useful for analysis of human error, and the taxonomy is a starting point for development of taxonomies allowing application to other domains, such as spacecraft maintenance, operations, medicine, process control, and other transportation industries.