A Markov Perspective on Development Interdependencies in Networks of Systems

Abstract

The development and acquisition of complex systems remain a challenge, especially in the aerospace/defense sector, due to complexities in both program management and engineering design that often are a result of interdependencies. The interdependencies between constituent systems form networks that, while enabling capabilities that are beyond those of individual systems, also increase risk since disruptions in the development of one system may propagate to other directly or indirectly dependent systems. This paper demonstrates an approach to aggregate the network interdependency characteristics and compare alternatives with respect to the time required to arrest the propagation of development delays in a network. Delay propagation is modeled as a Markov chain, where the states are defined as the constituent systems and the transition probabilities as the dependency strengths between systems. A proof-of-concept application shows the approach can distinguish between alternate networks and indicates its applicability for managing risk in design and development of systems with significant interdependencies.