The development and testing of SAfER: a resilience-based human factors method

Hassall, Maureen E., Sanderson, Penelope P. and Cameron, Ian T. (2014) The development and testing of SAfER: a resilience-based human factors method. Journal of Cognitive Engineering and Decision Making, 8 2: 162-186. doi:10.1177/1555343414527287

Author Hassall, Maureen E.
Sanderson, Penelope P.
Cameron, Ian T.
Title The development and testing of SAfER: a resilience-based human factors method
Journal name Journal of Cognitive Engineering and Decision Making   Check publisher's open access policy
ISSN 1555-3434
Publication date 2014-06
Year available 2014
Sub-type Article (original research)
DOI 10.1177/1555343414527287
Open Access Status
Volume 8
Issue 2
Start page 162
End page 186
Total pages 25
Place of publication Thousand Oaks, CA, United States
Publisher Sage Publications
Collection year 2015
Language eng
Abstract Major industrial accidents still occur. Recent research suggests that to improve industrial safety we must design work systems that better support operators as they seek to control unexpected and unprecedented situations. A novel human factors technique called SAfER—Strategies Analysis for Enhancing Resilience—has been developed to help practitioners identify the range of strategies that human operators might use to manage expected, unexpected, and unprecedented situations. SAfER also helps practitioners identify design changes that should promote the selection of successful control strategies, as well as design changes that should prevent or tolerate the selection of any potential unsuccessful control strategies. Tests revealed that participants found SAfER to be a useful method capable of helping them identify novel insights and identify design changes that could help operators as they control systems across different operating situations. In future work, the usability of the SAfER method and software will be improved, and they will be tested in further industrial contexts.
Keyword Risk management
Resilience engineering
Cognitive Engineering
human factors
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Chemical Engineering Publications
Official 2015 Collection
Version Filter Type
Citation counts: Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Mon, 14 Apr 2014, 22:05:04 EST by Maureen Hassall on behalf of School of Chemical Engineering