Learning from major accidents to improve system design
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- 作者：Raphael Mouraa ; b ; rmoura@liverpool.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Michael Beera ; b ; mbeer@liverpool.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Edoardo Patellia ; b ; epatelli@liverpool.a.uk" class="auth_mail" title="E-mail the corresponding author ; John Lewisa ; b ; johnlewis010452@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Franz Knollc ; d ; franz.knoll@nck.ca" class="auth_mail" title="E-mail the corresponding author
- 关键词：Accident analysis ; MATA-D ; Human factors ; Human reliability analysis ; Risk & safety in design ; CREAM
- 刊名：Safety Science
- 出版年：2016
- 出版时间：April 2016
- 年：2016
- 卷：84
- 期：Complete
- 页码：37-45
- 全文大小：843 K
文摘
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The Multi-Attribute Technological Accidents Dataset (MATA-D) is introduced.
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238 major accidents from several high-technology industries are analysed.
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Discloses interfaces between man, technology and organisation in major accidents.
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“Design failure” is the most frequent contributing cause for major accidents.
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A new method to apply lessons learned from past accidents to design reviews.