Faster, cheaper, more accurate method for calculating the most reliable vehicle design
"QinetiQ, Europe's leading science and technology
research organisation which undertakes vehicle reliability assessments
on behalf of the Ministry of Defence, has successfully worked with
Agena to augment its capabilities and is delighted with the results."
Mrs G Hardy, QinetiQ
Problem
- Determining which vehicle to choose, from competing tenders, to meet a new Ministry of Defence (MOD) requirement is difficult, time consuming and error prone
- Traditional solutions used by QinetiQ involved a combination of:
- Extensive track-testing of prototypes supplied by competing manufacturers
- Modeling based on analyzing design specs and using "sum-of-parts" reliability predictions
- This process was hugely expensive and generally led to unsatisfactory predictions because there was no means of combining subjective judgements about likely design and manufacturing process quality
Solution
- AgenaRisk was used to predict vehicle reliability accurately based on information about the architecture and design process
- The risk map was built "dynamically" based on the particular subsystem architecture of a given vehicle spec. For each vehicle, any known information about the subsystem reliability was used. This was combined with information about the particular manufacturer and their design and manufacturing processes
- For each proposed vehicle a prediction of reliability was output from AgenaRisk along with all supporting reports providing a full audit trail of assumptions
Benefits
- AgenaRisk saves time and money because accurate predictions are achieved without the need for track testing
- Predictions made by AgenaRisk are more accurate because QinetiQ can combine subjective data about the process and manufacturer with hard data about component reliability
- AgenaRisk helps identify process improvement opportunities and improve vehicle reliability
- AgenaRisk reduces whole life costs