Publication

Systems Engineering (SE)
2016

Modeling the Evolution of a System Over Time

by Matthew Hause

Abstract

Systems change over time. Sometimes this is planned as in the normal maintenance, planned upgrades, refits and modifications to keep a system fit for purpose and ready to deploy. There may also be multiple allowable configurations of a system providing flexibility to meet different operational needs. Sometimes the changes are not planned. This can be due to complete system failure, component failure, accidental or deliberate damage, as well as unforeseen operational needs. Whatever the reason for the change, the “To-Be” configuration of the system needs to be captured, analyzed and evaluated to ensure it will meet the projected operational need. Systems engineering and trade-off analysis also need to be performed to ensure that the best configuration of the system has been specified regarding time, cost, system effectiveness, as well as a host of other criteria. Additionally, it is not sufficient to simply model the system configurations. It is necessary to show how a configuration will evolve over time, how the variations will differ, common components, additional and emergent behavior, how a systems behavior and capabilities change over time, etc. For military vehicles, there is the additional dimension of the configuration of a manufactured set of vehicles. They are traditionally manufactured in this way in order to take advantage of economies of scale, as well as other factors. Over the typical course of a system lifecycle, they are regularly serviced and reconfigured to address operational needs as well as take advantage of technological developments. Mission and usage parameters continually evolve and the vehicle must adapt to suit. These need to be planned in advance, and the multiple configurations of each vehicle or set of vehicles need to be tracked and managed. No two vehicles are the same and arguably no two systems of systems are the same. This paper will show how these configurations can be modeled, managed and analyzed in an effective way.