Methodology for assessing dependencies between factors influencing airline pilot performance reliability: A case of taxiing tasks. (October 2020)

• Record Type: Journal Article
• Authors: Wang, Lijing; Wang, Yanlong; Chen, Yingchun; Pan, Xing; Zhang, Wenjin; Zhu, Yanzhi
• Is Part Of: Journal of air transport management. Volume 89(2020)
• Publication Date: 2020-10
• Subjects: Pilot performance reliability -- Common performance conditions -- State dependency -- Effect dependency -- Fuzzy logic; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2020.101877
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: Pilot performance reliability is critical to civil air transportation safety. Internal and external factors influencing pilot performance reliability are important elements to estimate human error probability. However, dependencies between these factors, including state dependencies and effect dependencies, are always ignored or only partially considered in most human reliability analysis (HRA) method. This paper attempts to develop a methodology incorporating both state and effect dependencies between contributory factors into HRA for airline pilot tasks based on fuzzy logic and the Cognitive Reliability and Error Analysis Method (CREAM). Anchor points were determined for each common performance condition (CPC) state levels through airline pilot elicitation process and then corresponding state and effect fuzzy sets were constructed for each CPC. The CPC dependency fuzzy inference rules were constructed and transformed with reference to the CPC dependency assessing rule in CREAM. And a cognitive failure probability (CFP) calculation method based on the final CPC effect fuzzy sets and the extended CREAM was proposed. To illustrate the use of the proposed methodology, a case study about commercial airline pilot taxiing task was given. The results demonstrate the validity of the proposed methodology and its capability of representing the ambiguity and fuzziness of expert judgement. Highlights: Common performance conditions were anchored for airline pilots. Fuzzy sets and fuzzy rules were constructed for modelling CPC dependencies. A Fuzzy-CREAM method was developed for both CPC state and effect dependencies assessment. Reliabilities of pilot taxiing tasks were analyzed as example.