Improving System Maturity Assessments by Incorporating a Design Structure Matrix Open Access
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Decision makers utilize qualitative and quantitative metrics/measurements to assess system development and to identify technical and programmatic risks. As systems increase in complexity and the number of interfaces increase, it is vital to develop a comprehensive view of the system development status. In order to help decision makers to assess system level development status, Sauser et al. developed System Readiness Level (SRL) as a system development metric. SRL is a function of Technology Readiness Level (TRL) and Integration Readiness Level (IRL) values for the system elements and interrelations of a specific system. Although the SRL was developed by Sauser et al, it is continuing to be assessed and expend by academia and industry. Although System Readiness Assessment (SRA) methods have been demonstrated to be valuable for understanding the development status of complex systems of developing technologies in the Department of Defense (DoD) and Department of Energy (DoE) applications, current SRA methods present shortcomings when practitioners apply SRA to a larger system in which significant investments are required to assess technologies and integrate them into larger systems. While current SRA approaches may make sense for a single mission or project, it presents drawbacks for use in research and development programs where decision makers need to assess complex integrated systems that include multiple components. Consequently, decision makers need a tool to conduct a SRA for a complex system that includes multiple elements, interfaces and mission. This dissertation evaluates the design structure matrix (DSM) as a new approach for assessing the system readiness level (SRL) of complex systems. A framework to demonstrate how a current SRL calculation method can be incorporated into the DSM tool is presented to demonstrate the benefits of DSMs for improved confidence in system readiness assessments. A cross-comparison of the modeled system readiness results obtained with a current SRL approach with nesting assumptions and the proposed DSM approach suggests that the DSM approach provides similar results with the SRL calculations without nesting. The application of the DSM approach to a real-world example is also presented to demonstrate how a DSM framework facilitates the decision-making process for system readiness assessment by providing a more evidence-based maturity assessment for complex systems. The DSM approach discussed in this research can be easily adopted by program managers and practitioners for a wide range of complex systems and system architectures with multiple subsystem components.