@phdthesis{01GSQ1CFEW1HQ7DAMJTANNMHS2,
  abstract     = {{This dissertation investigates explanation in the engineering domains of failure 
analysis and accident causation. Explaining accidents and failures is important 
for learning, preventing, repairing and in some cases figuring out responsibility.
The work presented here aims to clarify some widespread explanatory practices, 
strategies, and formats in these domains, using insights and accounts from
philosophy of science.
A series of case studies are used to highlight the structure and value of 
explanatory practices within engineering science. The crash of Air France 447 is 
used to highlight the way in which different explanations are evaluated when 
unequivocal evidence is missing. Analysing this case highlighted, among other 
things, that in failure analysis an important criterion driving the explanation is 
the ability to provide valuable redesign information. This insight is further 
exemplified in other cases such as malfunctioning Samsung Galaxy 7 mobile 
devices.
Another interesting result stems from analysing how engineers explain the 
breaking of metals and other ductile materials. One key factor in explaining 
these ruptures is the presence of small voids, which when merging together to 
a sufficient extent provoke the disjointing of metal pieces. The explanatory 
strategy employed here is that of a mechanical story, despite voids or holes not 
being the sort of entity that can behave mechanically. An analysis of how these 
explanations work is presented together with a description of the cognitive 
benefits they provide.
In addition to looking at concrete case studies, the dissertation also looks at the 
modelling practices used when analysing the causality of accidents. The way in 
which the causality of accidents is modelled has a direct impact on 
understanding and preventing accidents, as well as on the adjudication of legal 
responsibility. Different modelling strategies encode differing causal 
information, resulting in key differences in applicability, scope, effectiveness, 
and explanatory power. An account of the value of the most important 
modelling practices is put forward, regimented by precise tools from philosophy 
of science which highlight the relevant trade-offs each modelling approach 
offers. This analysis allows to make suggestions as to which modelling strategy 
192
is best suited to achieve specific aims, such as preventing accidents or 
adjudicating legal responsibility. 
Finally, key philosophical and theoretical tools are employed in building a 
procedure which aims at improving the practice of Failure Analysis. This 
procedure structures the information contained in explanations such that it 
enables to find weak points, to compare competing explanations, and to provide 
redesign recommendations. In doing so it becomes a tool for assessing the 
quality of failure explanations. The procedure offers failure analysts a practical 
tool for critical reflection on some areas of their practice while offering a deeper 
understanding of the workings of failure analysis (by framing it as an explanatory 
practice) and redesign. Two case studies from Mechanical and Civil Engineering 
are used to exemplify how the procedure works/is intended to work.}},
  author       = {{Gonzalez Barman, Kristian}},
  language     = {{eng}},
  pages        = {{194}},
  publisher    = {{Ghent University. Faculty of Arts and Philosophy}},
  school       = {{Ghent University}},
  title        = {{Explanation in the engineering sciences : IBE, causal modelling, and (fictional) mechanisms in failure analysis and safety science}},
  year         = {{2023}},
}