Utah Engineers Journal 2021 Issue

19 But I’m Sustaining Something Old! I’ve been interested in model-based engineering at a design level and model-based systems engineering processes at a higher level for over 20 years because I saw how useful it was to have a digital twin when managing a program like the Airborne Laser. Model-based systems engineering processes and their digital engineering infrastructure can apply to wherever you are in a product lifecycle. When you design, build, manufacture, sustain or update something, you either have an object in hand to operate and maintain or requirements for the work to be done. There is a great benefit to capturing information about your work early as you design and acquire a product. For example: • Captured data allows you to test and evaluate so you know if an object will work when it is manufactured. • If the object has already been built, you can make good decisions about updating or scrapping it. • Models help you do performance simulations and run cost analyses. They help you manage the cost, schedule, and performance of any item designed, built or sustained. One of the breakthroughs on the airborne laser project I worked on involved the required modifications to the Boeing 747 aircraft chosen to carry the system. We had to transition the paper-based design to a three-dimensional computational model because we took a 747 off the assembly line, basically took it apart, and rebuilt it in a highly modified way around the laser component. The work involved was massive, but we did the digital parts first. We had data about pipes, conduits, chemical tanks, and electronics, and we made it all fit. We tracked cost, the weight of the airplane’s modifications, and performance assessments. We wanted to know whether the 747 testbed could generate enough energy to propagate a laser as far as the Air Force wanted it to, with the required accuracy. The “digital twin” helped plan and execute this work to eventually reach a successful missile shoot-down test. But I’m Not a Systems Engineer I used the same picture here as on the previous section because all engineering disciplines can benefit from organizing data into models and aligning models against analytical tools. The tools change faster than the models, so engineers can use models to organize and analyze their data, then change the model content if the analytics dictate it. The models also enable improved integration with other engineering disciplines, keeping all subject matter experts referencing the same source of technical truth.