Reliability plays a critical role for all complex technical products. It refers to the probability that functions are executable over a defined time under stated conditions. Verification of functions and validation of reliability dominates the product development effort. Reliability engineering is in essence statistics applied to model failure risk over time. This provides methods for assessment of product verification and validation.
Optimisation of Design Verification and Design Validation of mechatronic systems requires in addition cross-technology expertise in failure risks. However, as technical risk assessment methods are rather qualitative, the potential of statistical methods is not fully exploited by standard procedures.
Under strict time and budgetary limitations, the major task of reliability engineering is to achieve the best allocation of development effort. This requires not only efficient tests but also a reliability process to combine all the efforts from all development partners into a single, synergistic process.
Lifetime is often far longer than the time interval available for reliability testing. Thus, the reliability can only be feasibly be demonstrated over the warranty period, and results are typically lower than desired.
In particular the nowadays common co-development of product variants for various operation modes and boundary conditions is challenging. A further aggravation comes with hybrid systems as their component loads are no longer a simple function of the system load due to several possible operation strategies.
When disruptive technologies are developed not only test procedures but also the validation process have to be modified or re-designed.
Uptime Engineering has developed a Design Verification process to accompany the product development. Transparency of activities and event history is the focus during functional verification. This helps to avoid time-consuming searches for data and results and delivers a sound basis for decision making.
The Design Validation process is based on a comprehensive risk assessment. Physics of Failure damage models deliver a basis for quantative comparison of tests with customer duty cycles. This approach is failure mode specific, and allows the aggregate contribution of various types of test to be correctly considered. As a result, the hierarchy and sequence of test activities, as well as the distribution across development partners can be optimised with respect to risk reduction.
The high level of risk investigation and system characterisation generates a sound basis also for system monitoring and supervision data analytics. These results are used for automatic diagnosis and prognosis to adapt product development and for condition based maintenance.