Reasons to Model

Abstract

Mojan and Fred discuss the strategic shift from modeling as a checkbox exercise to using RAM (Reliability, Availability, and Maintainability) models as a driver for proactive decision-making. They explore how modeling forces teams to confront “the weakest link” and align resources where they can have the most impact early in a program

Key Points

Join Mojan and Fred as they discuss why modeling is a critical engineering activity rather than just a requirement for a specification.

Topics include:

The Purpose of the Model: Modeling for its own sake is a waste of time; its true value lies in providing a structure for proactive maintenance, guiding vendor data discussions, and forcing teams to identify what is likely to fail.
Exposing the “Weakest Link”: Models act as a spotlight for Program Managers to identify the system’s weakest components. This creates accountability, keeping those areas “on the hook” until they are no longer the primary risk to the program.
Strategic Resource Allocation: By modeling early, teams can focus their limited time and budget on the “vital few” failures that count the most, rather than spreading resources thin across the entire design.
Bridging Data Gaps: A model provides a rigorous framework to compare vendor claims against early-life failure data—which are often ignored in standard models—and helps determine where to add necessary margins or buffers.
Design Feedback and Testing: Modeling provides immediate feedback to design teams, highlighting what we don’t know yet and defining exactly what needs to be tested to validate performance.
A Living Structure: Beyond the design phase, models provide a baseline to compare test results and field data. When field failures differ from the model, it provides a clear path to improve the model and your future decision-making.

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