ABSTRACT
The paper reviews the applicability of human error models, classification schemes and taxonomies to the aircraft maintenance environment. Whilst these models and tools can provide a useful starting point for assessing human error in maintenance and dispatch, they do not specifically capture these type of errors. Human factors initiatives tailored towards maintenance have been developed, such as managing engineering safety health (MESH) at British Airways Engineering. MESH is a confidential proactive system which captures information about potential error-inducing local and organisational factors in the workplace. Reactive safety aircraft maintenance systems which provide data on lapses in maintenance are also in place, such as accident and incident reporting procedures (e.g. maintenance error investigation - MEI). However, a link is required between the proactive systems and reactive safety mechanisms to allow the prediction of error probability and hence prioritisation of specific error reduction mechanisms. This paper describes the basis of an error taxonomy developed specifically to assess and predict error in aircraft maintenance and dispatch.
