Room: HR N137
Tel.: +31(0) 53 489 3390
Position: PDEng student
Decision Support Tool for Determination of Failure Mechanism
It is crucial for companies to reduce the amount of downtime of their machines. Proper maintenance policy is the way to achieve that. However, in order to develop a maintenance plan it is crucial to know what brakes down the machines. Operators and technicians are the first people to deal with a failure of a machine. An accurate report of a failure by them can save valuable time, money and enhance maintenance planning. Although, most of the times this is not possible and their report ends to be a simple “I don’t know”. They are lacking of the technical knowledge needed to identify the physical processes of the underlying failure mechanism.
This situation is raising the need to develop a tool that will assist these people in an efficient way. In this project, a decision support app will be developed to support failure mechanism identification. The user will be able to describe the failure characteristics and the operating environment of the failed component and the tool will provide a possible solution.
Such an app benefits companies in two ways:
- Reduction of time needed to perform analysis by an expert.
- Archiving dominant failure mechanisms and linking them with the components.