Browsing by Author "Stanton, Neville A."
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Item Open Access Human error prevention: using the human error template to analyze errors in a large transport aircraft for human factors considerations(2009-10-01T00:00:00Z) Li, Wen-Chin; Harris, Don; Stanton, Neville A.; Hsu, Yueh-Ling; Chang, Danny; Wang, Thomas; Young, Hong-TsuFlight crews make positive contributions to the safety of aviation operations. Pilots have to assess continuously changing situations, evaluate potential risks and make quick decisions. However, even well trained and experienced pilots make errors. Accident investigations have identified that pilots’ performance is influenced significantly by the design of the flight deck interface. This research applies Hierarchical Task Analysis (HTA) and utilizes the - Human Error Template (HET) taxonomy - to collect error data from pilots during flight operations when performing a go-around in a large commercial transport aircraft. HET was originally developed in response to a requirement for formal methods to assess compliance with the new human factors certification rule for large civil aircraft introduced to reduce the incidence of design-induced error on the flight deck (EASA Certification Specification 25.1302). The HET taxonomy was applied to each bottom level task step in an HTA of the flight task in question. A total of 67 pilots participated in this research including 12 instructor pilots, 18 ground training instructor, and 37 pilots. Initial results found that participants identified 17 operational steps with between two and eight different operational errors being identified in each step by answering to the questions based either on his/her own experience or their knowledge of the same mistakes made previously by others. Sixty-five different errors were identified. The data gathered from this research will help to improve safety when performing a go-around by identifying potential errors on a step-by-step basis and allowing early remedial actions in procedures and crew coordination to be made.Item Open Access Predicting design induced pilot error using HET (human error template) - a new formal human error identification method for flight decks(Royal Aeronautical Society, 2006-02-01T00:00:00Z) Stanton, Neville A.; Harris, Don; Salmon, Paul M.; Demagalski, Jason M.; Marshall, Andrew; Young, Mark S.; Dekker, S. W. A.; Waldmann, T.Human factors certification criteria are being developed for large civil aircraft with the objective of reducing the incidence of designinduced error on the flight deck. Many formal error identification techniques currently exist which have been developed in nonaviation contexts but none have been validated for use to this end. This paper describes a new human error identification technique (HET - human error template) designed specifically as a diagnostic tool for the identification of design-induced error on the flight deck. HET is benchmarked against three existing techniques (SHERPA - systematic human error reduction and prediction approach; human error HAZOP - hazard and operability study; and HEIST - human error In systems tool). HET outperforms all three existing techniques in a validation study comparing predicted errors to actual errors reported during an approach and landing task in a modern, highly automated commercial aircraft. It is concluded that HET should provide a useful tool as a adjunct to the proposed hliman factors certification process.Item Open Access Using SHERPA to predict design-induced error on the flight deck.(Elsevier, 2005-09) Harris, Don; Stanton, Neville A.; Marshall, Andrew; Young, Mark S.; Demagalski, Jason M.; Salmon, Paul M.Human factors certification criteria are being developed for large civil aircraft. The objective is to reduce the incidence of design induced error on the flight deck. Many formal error identification techniques currently exist, however none of these have been validated for their use in an aviation context. This paper evaluates SHERPA (Systematic Human Error Reduction and Prediction Approach) as a means for predicting design induced pilot error. Since SHERPA was developed for predicting human error in the petrochemical and nuclear industries, a series of validation studies have suggested that it is amongst the best human error prediction tools available. This study provides some evidence for the reliability and validity of SHERPA in a flight deck context and concludes that it may form the basis for a successful human error identification tool.