"We could not have done this project without the support and dedication of the ALE team. We are excited about the opportunities that are in front of us and look forward to building our partnership with ALE and continuing to work together in the future."
-Project Eng. Manager, Aviation
Acquisition Logistics Engineering (ALE) was instrumental in supporting the shipbuilder, Northrop Grumman Ship Systems (NGSS), in total logistics support for a new class of ships, the National Security Cutter (NSC). The NSC is a modern ship that is an integral part of the U.S. Coast Guard's Deepwater Program. ALE orchestrated that effort by concentrating in three major areas: Process Definition, Skill Development, and Analysis Completion.
Regarding the first area, Process Definition, we established the rationale and methodology for revising the Mission Criticality Codes (MCCs) for the ship systems. Next, we created the parameters and provided the effort to enhance the ship's Mean Time Between Failure (MTBF) values, thus assisting in the development of a sparing tool to determine repair parts and spares to be purchased for sailaway ship support. Subsequent to that effort, ALE developed the model to calculate and display Operational Availability (Ao) values for each of the 14 NSC mission profiles matrixed to both the 11 critical systems and the total ship systems. And finally, within the area of Process Definition, we devised the rationale, assumptions and mathematical calculations to assign Mean Logistics Delay Time (MLDT) values to the A equation.
In the second major area of Skill Development, we increased the skill level and capabilities of the NGSS Reliability, Maintainability and Supportability (RMS) team by providing ALE-instructed Relex training at our Gautier facility. In addition, we provided reinforcement to the ALE RMS team on the use of the Relex Reliability Prediction model. Lastly, we instructed NGSS personnel in the logic, rationale, and operation of the ALE-devised Ao modeling tool.
For the third major area, Analysis Completion, we analyzed the data developed during the program to determine reliability drivers. Then we completed the analysis of MLDT impacts to influence the Ao calculation. Then some of the original MTBF values were revised as a result of analysis of sustainment outcomes.
In summary, the ALE-developed Ao model brought visibility and allowed the analysis of key logistics parameters such as: