System Engineering

As systems become more complex, the systems engineering community must find new and more efficient ways of dealing with complexity throughout the system's lifecycle. Model-Based Systems Engineering (MBSE) has proven to be effective at managing complexity through the development of systems in a virtual environment. Several languages have been developed in the spirit of MBSE; however, these languages often do not include the full spectrum of information needed for holistic system solutions. The Lifecycle Modeling Language (LML) has been developed to provide extensible language that contains both visualization models and an ontology. When LML is coupled with the Systems Modeling Language (SysML), the result is a modeling constructs that better supports systems engineering processes across the entire spectrum of lifecycle concerns. This coupling will not only be beneficial today, but could serve as a catalyst for a future MBSE environment.

In the twenty-first century, mission success will require unprecedented interoperability among disparate constituent systems resulting in a System of Systems (SoS). Unlike traditional systems engineering where systems are created based on a set of user needs, a SoS is composed of multiple constituent systems, at various stages within their lifecycles (i.e. new start systems, systems in-development, legacy systems), to satisfy needed mission capabilities. System of Systems Engineering has been exploring appropriate methods and processes for almost two decades. This paper takes the discussion further by introducing a System of Systems Engineering and Integration (SOSE&I) methodology. SoSE&I is the planning, analyzing, and integrating of constituent systems into an SoS capability greater than the sum of those individual systems. The SoSE&I "Vee" process model is introduced and discusses how it is used to engineer the SoS throughout its lifecycle to increase systems integration and interoperability, and directly impact the operational success.

Engineering managers are typically concerned with the assessment and improvement of system performance. In the literature, analytical approaches have been proposed not only for the purpose of computing and estimating performance measures, but also for linking these performance measures to performance improvement strategies. In reality, organizational and/or system efficiency performance is dynamic, nonlinear in its relationship to key production drivers, and a function of multiple/complex interactions and feedback mechanisms. This paper introduces a methodological approach that combines the system dynamics (SDs) modeling paradigm with the concepts taken from the measurement of productive efficiency so as to evaluate dynamical systems. In this research, the SD paradigm is coupled with the fundamental assumptions of production theory in order to evaluate productive efficiency performance. As a result, a structure within the SD model is introduced that computes efficiency performance scores based on a hill-climbing optimization procedure. The structure is illustrated using an electric utility example described by Kopp, 1981, where constrained optimization results are not only replicated but also the path to achieve optimal dynamic system performance is found. An example is provided as to how this structure can be used to facilitate policy decisions within a technology management environment where investments are made in new technologies. Index Terms-Dynamic efficiency performance, electric power generation, hill-climbing optimization, introduction of new technologies, system dynamics (SDs). I. BACKGROUND E NGINEERING managers are typicallyconcerned with the assessment and improvement of system performance. In the literature, analytical approaches have been proposed [3] not only for the purpose of computing and estimating performance measures, but also to link these performance measures to performance improvement strategies. Within this context, this research has been motivated to account for two fundamental yet interrelated issues. First, managers usually attempt to optimize specific technical, financial, and societal performance goals. These may include but are not limited to maximizing throughput, minimizing production costs, maximizing customer satisfaction, maximizing effectiveness, minimizing noise and pollution levels, etc. Second, in a dynamic environment, optimizing over time requires the implementation of interventions, where the system ideally reaches an optimum performance level once a disturbance (e.g., a new technology is introduced, a process improvement program Manuscript

Realistically, organizational and/or system performance is dynamic and non-linear. However, in the efficiency literature, system performance is frequently evaluated considering linear combinations of the input/output variables and without explicitly taking into account the causes of efficiency behavior nor the dynamic behavior of systems. Policy decisions based on these results may be sub-optimized because the non-linear relationships among variables, causal relationships, and feedback mechanisms are ignored. This research takes the initial step of evaluating system performance in a dynamic environment, by relating the factors that effect system performance to the policies that govern it. To accomplish this, this paper extends the concepts of the static production axioms into a dynamic realm, where inputs are not instantaneously converted into outputs. The relationships of these new dynamic production axioms to the basic behaviors associated with system dynamics structures are explored.

Net-centricity is forcing the evolution of system of systems (SoS). One aspect of SoS that has been essentially ignored is SoS governance. Governance is the set of rules, policies, and decision-making criteria that will guide the SoS to achieving its goals and objectives. In this paper, we join the attributes of governance practices found in the IT community with known SoS types and characteristics to develop a criteria-based framework for SoS governance.

Warren K. Vaneman U.S. military history, during the 50 years prior to the passage of the Goldwater-Nichols Department of Defense Reorganization Act of 1986, is filled with examples of operational problems, often caused by different doctrine of the services, lack of compatibility of communications and weapons systems, and in some cases inter-service rivalries. To address these deficiencies, Senator Barry Goldwater (D-AZ) and Rep. William Flynt Nichols (D-AL) proposed wide sweeping reforms to the Department of Defense (DoD). These changes were designed to: centralize the military advice to the President of the United State through the Chairman of the Joints Chiefs; defined new roles of the services, and enhanced the roles of the combatant commanders; specified the sharing of new technologies among the services to gain efficiencies through shared procurements; and changed the personnel management of military officers.

In the modern operational environment, multiple systems forming a System of Systems (SoS) are required to satisfy the spectrum of capabilities needed to satisfy the mission. Accomplishing the mission has always been a SoS endeavor, where integrating multiple systems into a SoS has been left to small communities of "hero engineers," or to the operators responsible for the mission. The acquisition and management of these mission capabilities across the SoS lifecycle requires the complex integration of interdependent new and legacy systems from the lowest component level to the highest enterprise level. In 2008, Congress directed government organizations to adopt a Lead System Integration (LSI) process to address the issues with the acquisition, development, and integration of a SoS. This paper introduces an LSI Enterprise Framework that identifies the various levels of interaction, organizational functions, and the universal resources to ensure the enterprise provides a SoS that delivers the required capabilities.

Ron Carlson-served 26 years in naval aviation as a pilot, seven years of which were at NAVAIR where he led NAVAIR Systems Engineers through several years of systems engineering revitalization. He joined the NPS SE department 10 years ago. He has a Master of Philosophy in Systems Engineering from Stevens Institute of Technology, master's degrees in strategic studies and national policy from the Naval War College and business administration-aviation from Embry Riddle Aeronautical University, and his Bachelor of Science in nuclear engineering from the University of Michigan.

In the modern operational environment, multiple systems forming System of Systems (SoS) are required to satisfy the spectrum of capabilities needed to satisfy the mission. Accomplishing the mission has always been a SoS endeavor, where integrating multiple systems into a SoS has been left to small communities of "hero engineers," or to the operators responsible for the mission. The acquisition and management of these mission capabilities across the SoS life cycle requires the complex integration of interdependent new and legacy systems from the lowest component level to the highest enterprise level. In 2008, Congress directed government organizations to adopt a Lead System Integration (LSI) process to address the issues with the acquisition, development, and integration of a SoS. The purpose of this paper is twofold: (1) the results of our early exploration of LSI are presented with the definition and development of the LSI Enterprise Framework; (2) it provides an update to our ongoing research that is using a model-based approach to explore the correlation between other frameworks and processes used to engineer and manage SoS employed by Navy Systems Commands.

Dr. Warren Vaneman, Prof. Joseph Sweeney, Dr. Gary Langford, Mr. Gary Parker, Mr. Chris Wolfgeher, LCDR Willima HarleyThis research examines new methods to assess and improve Physical Protection Systems (PPS), paying specific attention to a Navy Level 3 Restricted Areas, a special type of industrial and refit zone that normally handles high value units such as aircraft carriers and ballistic missile submarines, utilizing Model Based Systems Engineering (MBSE) and System of Systems (SoS) theory to create a framework which couples architectural level PPS design with detailed discrete event security assessment and prediction techniques in order to provide decision makers and acquisition authorities a more quantitative and effective method to holistically understand a PPS and the PPS�s internal and external interactions, allowing for improved capability and vulnerability analysis and the formulation of sound acquisition decisions.Naval Research ProgramPrepared for: Navy Strategic System...