System Of Systems Level Research Articles

DESIGNING EMERGENCE IN SYSTEMS OF SYSTEMS USING INFORMATION STREAMS

AbstractSystems complexity is increasing, in particular, when systems become systems of systems (SoS). SoS are composed of constituent systems (CS), have unique goals for the CS and the SoS as a whole, and present new SoS-level properties called emergent properties. Emergent properties are unique because they only appear at the system level. Current research has only revealed some tools focusing on simple emergence for engineers aiming to design emergence at the SoS level. However, forming design tools for the creation or modification of strong emergence will enable engineers to create systematic changes in the SoS. This article proposes a connection between emergence and information streams with the latter being a model of the transfer of information between the different CS in the SoS. A methodology for designing SoS information streams is demonstrated, with encouraging results, using a multi-agent simulation of the propagation of the COVID-19 virus through citizens. By testing several information stream configurations, an SoS with a decrease of 47% in sick agents was found. These results show that by changing the information stream better SoS performance is attained, supporting designing in a complex world.

Framework for Complex SoS Emergent Behavior Evolution Using Deep Reinforcement Learning

AbstractAdvances in technology have made it easy to integrate multiple modern systems to form complex system‐of‐systems (SoS) to achieve unparalleled levels of functionality that are otherwise not achievable by the constituent systems in isolation. In fact, with the recent explosion of machine learning techniques to build autonomous systems such as drones and self‐driving cars, there is a pressing need to ensure that they collaboratively and safely operate in an SoS context. However, in general, the characteristic emergent behaviors of complex SoS – that directly impact its operational measures of success or Measures of Effectiveness (MOEs) – is very difficult, if not impossible, to manually explore, anticipate, and arbitrate just from knowledge of its underlying systems. Further, there are multiple scenarios of evolution in such complex SoS, including evolution in the emergent behavior of the SoS. The continuous, continual, and evolving nature of the SoS and constituent system environment's state and possible actions, adds further complexity. In this paper, we present a novel approach that leverages Reinforcement Learning, a machine learning approach, to inculcate adaptable intelligence in constituent systems to adapt their behaviors in tandem with the evolution of emergent behavior at the SoS level. By augmenting the reward mechanism of RL by leveraging SoS‐Constituent System MOE Relationship, that relates and ranks System MOEs vs. SoS MOEs, we inculcate an Intelligent‐Behavior Evolution Agent, with the necessary constraints to learn to maximize the SoS and system‐level MOEs, while adapting itself to the evolution in SoS. We illustrate our approach and demonstrate its feasibility and potential by applying it to a power grid SoS case example. The effectiveness and performance of the approach are quantified.

Analyzing the Environmental Consequences of Production Processes from a System of Systems Perspective: A Case of Gear Manufacturing in the Automotive Industry

Many research studies have been done to investigate different aspects of environmental challenges. In the product development context, there have been attempts to reduce the environmental impacts of associated activities including the production processes themselves. As a result, various technological improvements have been made and new production processes e.g. powder metallurgy technologies have been introduced that may demonstrate a lower environmental footprint compared to conventional processes e.g. cutting machining technologies. However, a production process with a lower environmental impact may lead to reducing the quality/performance attributes of the produced parts (gear) and probably of final products (transmission box). Therefore, the efforts intended to produce more sustainable products by using production processes with less environmental footprints may lead to some unintended consequences such as increased maintenance requirements and/or demand. This is a rebound effect from a system of systems (SoS) perspective. This paper aims to analyze the impacts of more environmentally friendly production processes on the total environmental impact associated with a product given they may have a negative impact on a part/product’s quality and performance or usage. This paper introduces a methodological approach to analyze the environmental sustainability of a production process at a SoS level. This is done by including the entire supply chain of a product-system and its interacting systems by using the results of the attributional/consequential life cycle assessment (LCA) method. The approach validity approach is demonstrated in the case of gear manufacturing in the automotive industry.

Multidisciplinary and Multifidelity Framework for Evaluating System-of-Systems Capabilities of Unmanned Aircraft

The operational environment of aerospace products can have a big impact on their performance, and therefore it is an aspect that should be considered as early as possible in their development process. In this light, this paper presents an analysis and optimization framework that can be used in the development of unmanned aerial vehicles (UAV) in order to efficiently explore the design space when considering system-of-systems (SoS) formulations. In this work, the problem is decomposed with a multilevel architecture, and it is divided into three parts, which enable a multifidelity evaluation of the SoS, constituent systems (CS), and subsystems (SS) levels. To be able to capture the collaboration between different assets at an SoS level the framework includes an in-house tool for performing agent-based simulations, whereas the specifications of each CS are analyzed through a set of basic aeronautical disciplines and a number of SS models. The framework is tested against two surveillance scenarios by considering existing as well as new UAV designs, and overall it is shown that the exploration of SoS enables to identify better capabilities; that the operational environment poses different requirements on all system levels; and that fleet tactics have a profound effect on mission performance.

Architecting systems‐of‐systems and their constituents: A case study applying Industry 4.0 in the construction domain

AbstractThe development of system‐of‐systems (SoS) requires a continuous interplay between design decisions on the SoS level and those on the level of its constituent systems (CS), which often preexist and need to be adapted as the SoS evolves. This involves not only preparing the CS to participate in a particular SoS, but also designing the CS architecture to make it easily adaptable to a future SoS context. The problem is in part addressed in an emerging SoS framework in the manufacturing domain called Industry 4.0. It focuses on connected and digitalized production with the ambition of increasing flexibility and efficiency. This paper investigates how Industry 4.0 standards can be used in an SoS context to make CS more flexible and adaptive, and evaluates their usefulness outside manufacturing. The study is based on a case from the construction domain, for which a generic SoS architecture is developed. Several extensions and adaptations of Industry 4.0 are suggested, including specifications of ontologies for missions and workflows.

Using MBSE to Evaluate and Protect the Electrical Grid as a System of Systems

AbstractA System of Systems (SoS) is a large complex system, with varying degrees of operational independence, managerial independence, evolutionary development, geographical distribution and lifecycle independence. Critical Infrastructure such as the electrical grid contains all the aspects of a SoS. Due to the ever‐increasing complexity of the grid, a single model encompassing all aspects of the grid would be impossible. Hence, we need to abstract the problem into a SoS set of aspects and examine the system both at the SoS level, as well as the detailed level. This will require the use of standardized systems modeling tools such as the Systems Modeling Language (SysML), and the Unified Architecture Framework (UAF) to define the overall goals, strategies, capabilities, interactions, standards, operational and system architecture, system patterns and so forth. This paper will examine the electrical grid as a SoS, define common characteristics, identify issues and vulnerabilities and MBSE strategies for addressing them.

USING MBSE TO EVALUATE AND PROTECT THE ELECTRICAL GRID AS A SYSTEM OF SYSTEMS

ABSTRACTA system of systems (SoS) is a large complex system, with varying degrees of operational independence, managerial independence, evolutionary development, geographical distribution, and lifecycle independence. Critical infrastructure such as the electrical grid contains all the aspects of a SoS. Models are routinely used throughout the complete lifecycle of the grid during analysis, definition, construction, operation, maintenance, and more. Due to the ever‐increasing complexity of the grid, a single model encompassing all aspects of the grid would be impossible. Typical projects I have worked on encompassed millions of telemetered points just to operate a small portion of the overall grid. When the detailed mechanics of the individual equipment as well as cyber security, connection to the Internet, the Internet of things (IoT), power trading components, co‐generation, and other aspects are added, the problems quickly become too complex to analyze. Hence, we need to abstract the problem into a SoS set of aspects and examine the systems both at the SoS level, as well as the detailed level. This will require the use of standardized systems modeling tools such as the systems modeling language (SysML), and the unified architecture framework (UAF) to define the overall goals, strategies, capabilities, interactions, standards, operational and systems architecture, systems patterns, and so forth. Analysis using these standard methods can help identify potential problems that can be analyzed by specialty tools and the results fed back into the SoS model. This paper will examine the electrical grid as a SoS, define common characteristics, identify issues and vulnerabilities, and model‐based systems engineering (MBSE) strategies for addressing them.

Analyzing Ballistic Missile Defense System Effectiveness Based on Functional Dependency Network Analysis

Recent engineering experiences highlight the Ballistic Missile Defense System (BMDS) as a System of Sys- tems (SoS), and traditional probability models were limited in capturing the complex interactions between component sys- tems. A novel approach was proposed to evaluate the effectiveness of the whole BMDS from the aspect of functional in- teractions, rather than the functions of components. First, Functional Dependency Network Analysis (FDNA) was intro- duced to build the analysis model through integrating the component systems in multi-layered kill chains of BMDS. The key metrics were proposed to measure the effectiveness from both probability of raid annihilation and system response time. Finally, the application of this method was demonstrated through a case study, and the result shown the holistic characters of BMDS at SoS level. The case shown that FDNA was a promising way to analyze SoS at high level.

An Interactive Portfolio Decision Analysis Approach for System-of-Systems Architecting Using the Graph Model for Conflict Resolution

A novel approach based on the graph model for conflict resolution (GMCR) methodology is proposed to address the problem of multistakeholder system portfolio decision analysis encountered in architecting a system of systems (SoS) with desired capabilities. More specifically, a flexible four-process framework for capability-based SoS architecting containing interactive portfolio decision analysis to promote multistakeholder design negotiations on system portfolio selections is presented. By taking full advantage of the inherent realistic and flexible design of the GMCR paradigm, an interactive portfolio decision analysis approach is designed to facilitate the systematic modeling and analysis of system portfolio decisions at the SoS level in order to achieve potential compromises among all key stakeholders having disparate preferences and interacting according to different conflict behavior patterns. This approach permits the prediction of possible mutually agreeable system portfolios for SoS architecture development. Last, the feasibility of the proposed approach is demonstrated using an illustrative example.

An Analytic Workbench Perspective to Evolution of System of Systems Architectures

The development of a large group of interdependently operating systems, or ‘System of Systems (SoS)’, presents significant challenges across technical, operational and programmatic dimensions. Trades between cost, schedule, performance, and associated spectrum of risks, are essential during analysis of alternatives for both individual systems and the SoS architecture as a whole. The large number of decision variables involved, ubiquitous uncertainty and complex interactions that exist between systems creates analysis problems that go well beyond the immediate mental faculties of decision-makers. Often times, the decisions made focus on localized development at the systems level with little consideration for cascading effects on the bigger SoS picture. Hence, the process of evolving SoS architectures requires tools that provides the SoS practitioner with meaningful analytical quantifications of the SoS tradespace. In the defense arena, existing tools for such trades, have been guided by policies set forth in the Defense Acquisitions Guidebook (DAG) (5000 series) and the System Engineering Guide for System of Systems (SoS-SE), but are lacking an analytic perspective towards more informed decision-making. This paper discusses a multidisciplinary effort, funded by the DoD's Systems Engineering research Center (SERC), to establish an analytic workbench of computational tools to facilitate better-informed decision-making on SoS architectures. The work is motivated by the idea that SoS practitioners possess relevant information and archetypal questions that reflect desired outcomes at the SoS level. These archetypal, technically -driven queries are mapped to relevant methods that can provide analytical outputs to directly support SoS acquisition and architectural decisions. The applicability and respective value-added of each method in addressing various archetypal measures are presented.

An Analytic Portfolio Approach to System of Systems Evolutions

The development of large collections of systems or a ‘System-of-Systems (SoS)’ is challenging due to the large number of systems involved, complex dynamics attributed to interdependencies between systems, and inherent technical and programmatic uncertainties. The sheer number of decision variables involved in SoS development exceeds the mental faculties of the SoS practitioner, prompting the need for effective analytical support frameworks. Current frameworks and guidelines in addressing SoSE challenges lack analytical means of objective SoS level decision-making. Research in this paper adopts computational decision support methods from financial engineering that allows SoS practitioners the means to identify optimal ‘portfolios’ of systems based on dimensions of capability, cost and operational risk. The SoS architecture is represented as a hierarchical collection generic nodes that interact to provide the overarching SoS level set of capabilities based on an archetypal set of inter- nodal behaviors. Our research leverages a Conditional Value-at-Risk (CVaR) perspective to managing risks that can incorporate agent based simulation data in the decision-making process. We demonstrate the method using a LCS inspired Naval Warfare Scenario (NWS) as an illustrative case study.

Managing System of Systems Requirements with a Requirements Screening Group

AbstractFiguring out an effective and efficient way to manage not only your Requirement's Baseline, but also the development of individual requirements during a System of Systems Program's Conceptual and Developmental Life Cycle Stages can be both daunting and difficult. This is especially so when you are dealing with a complex and large System of Systems (SoS) Program with many thousands of SoS Level Requirements as well as an even larger number of System, Subsystem and Configuration Item requirements that need to be managed. This task is made even more difficult when you add in integration of the efforts of multiple requirements development teams (e.g., Integrated Product Teams (IPTs)) and numerous System/Subsystem Design Teams.One solution for tackling this difficult activity on a recent large System of Systems Program was to establish an empowered Requirements Screening Group (RSG). This group is a Team made up of co‐chairs from the Contractor, Customer, and User Stakeholders that are empowered by and accountable to the Program Manager for Requirements Development on the Program. The RSG co‐chairs, with the support of the System of System Requirements Team monitor, make decisions on, and provide guidance on all Requirements Development activities during the Conceptual and Development Life Cycle Stages of the Program. In addition, the RSG establishes and maintains the Requirements Baseline, monitors and enforces requirements traceability across the entire Program, and works with other elements of the Program to ensure integration and coordination.

Managing the interstitials, a System of Systems framework suited for the Ballistic Missile Defense System

AbstractRecent engineering experiences with the Missile Defense Agency (MDA) Ballistic Missile Defense System (BMDS) highlight the need to analyze the BMDS System of Systems (SoS) including the numerous potential interactions between independently developed elements of the system. The term “interstitials” is used to define the domain of interfaces, interoperability, and integration between constituent systems in an SoS. The authors feel that this domain, at an SoS level, has received insufficient attention within systems engineering literature. The BMDS represents a challenging SoS case study as many of its initial elements were assembled from existing programs of record. The elements tend to perform as designed but their performance measures may not be consistent with the higher level SoS requirements. One of the BMDS challenges is interoperability, to focus the independent elements to interact in a number of ways, either subtle or overt, for a predictable and sustainable national capability. New capabilities desired by national leadership may involve modifications to kill chains, Command and Control (C2) constructs, improved coordination, and performance. These capabilities must be realized through modifications to programs of record and integration across elements of the system that have their own independent programmatic momentum. A challenge of SoS Engineering is to objectively evaluate competing solutions and assess the technical viability of tradeoff options. This paper will present a multifaceted technical approach for integrating a complex, adaptive SoS to achieve a functional capability. Architectural frameworks will be explored, a mathematical technique utilizing graph theory will be introduced, adjuncts to more traditional modeling and simulation techniques such as agent based modeling will be explored, and, finally, newly developed technical and managerial metrics to describe design maturity will be introduced. A theater BMDS construct will be used as a representative set of elements together with the interstitials representing the integration domain. Increased attention to the interstitial space of the overarching BMDS SoS construct and applying appropriate technical rigor and engineering due diligence with these added tools should greatly assist the BMDS in realizing its potential. © 2010 Wiley Periodicals, Inc. Syst Eng 14: 87–109, 2011

Combining Attributes for Systems of Systems in Multi‐Attribute Tradespace Exploration

One of the principal value propositions for the creation of Systems of Systems (SoS) is the ability to generate stakeholder value beyond that which can be delivered by a single system or even a collection of systems. The dynamic interactions among the component systems in a SoS make conceptual design decisions for SoS more complex compared to traditional system design. There are several heuristics and qualitative guidelines for designing SoS in the literature, but there is a lack of practical quantitative methods for SoS concept exploration. Development of quantitative methods for SoS conceptual design will greatly improve the ability of decision makers to select SoS designs in the concept design phase that will be value robust over time, by allowing them to consider a larger and more complete set of possible alternative SoS designs than is possible with qualitative methods alone. Multi-Attribute Tradespace Exploration has been used in the past to compare large numbers of system alternatives on a common cost-utility basis. In this method, the designer elicits the decision maker’s needs and formulates these as quantified attributes. The systems are then analyzed in terms of their ability to achieve the desired levels of attribute metrics. SoS-level attribute calculations must reflect component system interactions and emergent SoS-level value, as well as the added costs and benefits in the SoS as compared to that of the component systems operating alone. This paper introduces techniques for the SoS attribute combination modeling within the Multi-Attribute Tradespace Exploration method when considering SoS with heterogeneous component systems. Combining the attributes for the SoS-level must take into account the nature of the attributes provided by the component systems as well as the concept of operations for SoS. The techniques used for SoS attribute combination are classified according to the level of coordination between the component systems in the SoS. Using the information about the complexity of the method required along with knowledge about the control structure in the SoS, the SoS architect can estimate the added SoS integration costs. The ability to combine attributes contributes an essential constituent for the extension of the tradespace exploration methodology from the single system to the SoS level, allowing for the comparison of many SoS alternatives on a common cost-utility basis.

Systems-of-Systems Analysis of Ballistic Missile Defense Architecture Effectiveness Through Surrogate Modeling and Simulation

Traditionally, the analysis of Ballistic Missile Defense System (BMDS) effectiveness has been limited in fidelity due to the inherent complexity of the subject. Indeed, the BMDS battle management process involves monitoring and controlling the actions of many interacting participants (e.g. radar sensors, communications networks and interceptor missiles) in a process whereby a target moves from launch through sensor detection through intercept kill assessment. Because the actions of each participant may evolve independently, the battle management process functions as a true system-of-systems (SoS). Proper SoS analysis requires architecture level engineering, dealing with component functional allocation and inter-component interaction rather than the internal workings of individual participants. Although prior work has been identified that addresses BMD effectiveness at the SoS level, each method sacrifices analysis fidelity of both process elements and individual participants to enable timely decision making. This paper proposes a modeling and simulation (M&S) framework that supports architecture level analysis of the BMDS. The key innovation is the application of neural network surrogate models, which are representations of other high- or medium-fidelity M&S tools, and can be executed rapidly with negligible loss in fidelity. Surrogate models were created of a BMDS analysis tool that included multisensor target tracking and fusion codes. Results will show the benefit of integrating M&S to architecture level analysis. Specific examples include sensitivity of operational level metrics to formation of an integration tracking picture, and the enabling architecture level decision making.

Dynamic Optimization Of Systems Of Systems Using Value Measurement

Many systems of systems (SoS) occur today through the collaboration of multiple stakeholders, without any clear authority or direction at the SoS level. Examples include a supply chain, an airport, and the Internet. Because of the uncontrolled interactions, such a SoS exhibits complexity behaviors such as reflexivity, emergence, self-organization, and adaptation. This paper presents underlying theory to explain a methodology for dynamic optimization of SoS, in which the stakeholders make changes based on local perceptions of the value of the SoS. Each stakeholder has a different local perception of value, measured against an objective function that may be unique to the stakeholder. As the stakeholder compares perceived value to desired value, the stakeholder attempts to optimize the SoS from its own point of view by making decisions that lead to SoS changes. These changes then affect other stakeholders, resulting in a dynamic architecture and implementation of the SoS. We present the optimizing value proposition of each stakeholder in terms of a quantifiable objective function based on the life-cycle value of the SoS to that stakeholder, and we present the dynamic interaction as a model of self-organization. An example based on supply chain management demonstrates the approach.