Proposing Strategies to Prevent the Human Error in Automated Industrial Environments

Authors:
José A. N. Neto;Maria F. Vieira;Charles Santoni;Daniel Scherer
Affiliations:
LIHM ---DEE --- CEEI UFCG, Campina Grande, Brazil;LIHM ---DEE --- CEEI UFCG, Campina Grande, Brazil;LSIS, Université Paul Cézanne (Aix-Marseille III), France;LIHM ---DEE --- CEEI UFCG, Campina Grande, Brazil
Venue:
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
Year:
2009

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Abstract

This paper presents a process to conceive strategies to prevent the human error when operating industrial systems. The process adopts a broader view to error prevention, going beyond the error analysis to consider the user profile, the task and context description. The error classification is done according to a task execution cognitive model. The conceived strategies focus on the human interface component of those systems since it is this work's premise that the human interface design has a strong impact on the human error rate.