Abstract:
The continuously developing requirements of the offshore oil and gas Operators are
placing more stringent demands on the designers to produce optimised solutions, with
reduced development schedules, and application of new technologies for extreme
environmental and operational conditions. The compounding uncertainty of service
conditions and in the design capabilities is causing the designer to over-design,
conduct extensive pre-service testing and introduce design redundancy. As such,
designers have been forced to turn to reliability techniques in order to quantify the life
of their designs. This has extended as far as needing to integrate reliability concepts,
tools and methodologies into the design process.
In recent times, the industry has attempted to apply conventional reliability tools within
the design process, in terms of failure identification and reliability quantification.
However, the use of historical reliability data has shown to be a particular downfall. As
such, there has been a drive to predict the reliability of mechanical components based
on their underlying degradation and failure processes and mechanisms.
Consequently, this research is initially concerned with the development of a
methodology, including an assessment of existing methods, that could be used to
more readily understand the underlying failure characteristics of a mechanical
component in terms of material, geometrical, environmental and operational
characteristics. A particular underlying mechanism has been chosen and
mathematical models were developed that simulate its physical behaviour and its
degradation characteristics. Additionally, due to the potential uncertainty in the
models and limited understanding of the characteristics of the underlying mechanism,
the model was simulated within a probabilistic framework, fundamentally by
application of the stress strength interference modelling approach. Finally, the model
and its parameters were assessed to determine how uncertain governing parameters
could appear to lead to variations in the reliability of the actuator.
