A hybrid model for learning from failures

作者：Stephen Calvin; Labib Ashraf^*

来源：Expert Systems with Applications, 2018, 93: 212-222.

DOI：10.1016/j.eswa.2017.10.031

• Decision analysis
• Multiple criteria
• Decision making

In this paper we propose the usage of a hybrid of techniques as complementary tools in decision analysis for learning from failures and the reason behind systems failure. We demonstrate the applicability of these tools through an aviation case study, where an accident investigation report was obtained from the Directorate of Accident Investigation in the Ministry of Transport and Communications in Botswana to provide as a basis for the application of the model. The report included all the factual information required to carry out the investigation using the hybrid of FTA, RBD, AHP, HoQ and the DMG tools.
We discuss the steps followed in applying the tools in the process of learning from failure. It also shows the importance of such tools in accident investigations by showing the importance of prioritising the available options in order of their importance to the accident under investigation.
Most of the available research in learning from failure focuses mostly on the direct causal factors of the failure event. Here we provide a holistic approach to learning from failure by focusing on both direct and indirect causes of a failure event through the use of Reliability Engineering tools, Multi Criteria Decision Making tools and House of Quality.

• 出版日期2018-3-1