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In recent years there has been an increased need for resilience in complex military and civilian systems due to evolving adversarial and environmental threats. Engineered Resilient Systems (ERS) is a Department of Defense (DoD) program focusing on the effective and efficient design and development of complex engineered systems. These complex system...
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Context 1
... an ility, resilience is a factor of interest to the DoD that may be disaggregated to provide additional insights into resilient system alternatives. In the ERS program, a resilient engineered system can be defined as "a system that is able to successfully complete its planned mission(s) in the face of a disruption (environmental or adversarial), and has capabilities allowing it to successfully complete future missions with evolving threats 8 ." Two quantifiable types of resilience are proposed in this definition; mission resilience and platform resilience which contribute to the short and long-term capability of the system. The illustration in the paper will incorporate mission resilience; defined as the expected performance maintained and recovered by the system in the face of potential performance loss the system suffers under a threat. The contribution and interaction of mission and platform resilience within the resilience ility may be seen in Figure 2. The focus of this paper is primarily set-based design with integrated mission resilience, platform resilience is reserved for future work. Figure 3 illustrates system performance in a single objective at various system states with respect to mission resilience. The calculation of expected performance given a threat may be seen in equation (1) as the formulaic addition of resilience into the mission chain and is a modification of Specking et al 8 . In a time period which allows for a recovery action, the expected performance with resilience is within the value measures of the MODA value model. Fig. 3: System performance at sequential states of time given a threat ...
Context 2
... illustration in the paper will incorporate mission resilience; defined as the expected performance maintained and recovered by the system in the face of potential performance loss the system suffers under a threat. The contribution and interaction of mission and platform resilience within the resilience ility may be seen in Figure 2. The focus of this paper is primarily set-based design with integrated mission resilience, platform resilience is reserved for future work. ...
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Citations
... The case studies of [27], [8] and [22], demonstrated the usefulness of integrating decision analysis and life cycle cost models within a Model Based Engineering framework to inform stakeholder decisions. However, a SBD state-of-practice survey identified knowledge and methodology gaps for complex system design management. ...
... Just as striking was the limited number of SBD methodologies using techniques such as MBSE and multiresolution modeling in system design. Our case study question is how can we combine and adapt the best practices and methods first described by [27] with other techniques like multiresolution modeling and information theory to enable program management decisions, and ultimately deliver higher value to the system stakeholders? While the original tradespace analytics tool provided an excellent example of the functionality required in Model Based Engineering applications, it lacked certain features and capabilities required for our case study. ...
... The original tradespace analytics tool developed by [27] is an Excel based tool containing nine modules for the parametric, MODA, and life cycle models, a random number generator, and a user interface, known as the control panel. The tool enables analysis of multiple alternatives by propagating many design solutions through the integrated parametric physics, MODA, and life cycle cost models to create the system tradespace. ...
... 25 The case study provides a tractable SBD scenario seeking to develop a high-value and affordable system given the five discrete and two continuous design decisions seen in Table 4. 26 We base our integrated UAV model structure on an integrated trade-off analytics framework, originally developed for engineering resilient systems. 27 The integrated model uses 11 modules to generate, test, and assess design options. The modular construction enables efficient integration of new HR models and simulations as we proceed through design maturation. ...
Increasing system complexity requires that engineers, systems analysts, and program managers use comprehensive design methodologies to deliver affordable and resilient designs. One method is set-based design (SBD), a product development and managerial process distinctly suited for developing complex systems under uncertainty. SBD simultaneously develops, analyzes, and matures numerous potential design sets, enabling the identification of high-value, affordable, and resilient designs. Published SBD research is a rich source of both qualitative and quantitative methods. This research specifically focuses on quantitative SBD methods to apply a value of information (VOI) methodology enabling design convergence and selection. We build upon previous SBD research to enable design maturation and uncertainty reduction. Our methodology integrates design maturation and multiobjective VOI analysis into a comprehensive quantitative SBD process to guide system development from initial design concepts to the pre-production design decision. In doing so, we also provide refinements and process improvements to existing quantitative SBD methods. We demonstrate our methodology with a model-based UAV design case study using an integrated suite of system, value, and cost models. Our case study specifically focuses on the design maturation and model selection decisions enabling design space convergence. We compare our current results with those from a previous UAV case study, achieving a 41% reduction in required computation time for design space convergence. These results highlight the methodology's ability to reduce program risk and potential to improve SBD convergence efficiency.
... Furthermore, traditional security measures stand to be inapplicable in the context of HIoT. The complex and interconnected nature of the HIoT systems requires such systems to be resilient to cyberattacks and threats throughout their lifecycle [44]. ...
The increasing adoption of IoT technologies in various sectors including health has proven that the benefits and value offered by these systems continue to have an impact. The design of the Health Internet of Things (HIoT) technologies mainly operate in functionalities with limited or lack of resilient security. Although the HIoT continues to transform and empower the healthcare sector, the standard of security in the design of these devices is still debatable. Healthcare is one of the sectors, which has experienced the highest data breaches from sophisticated cyberattacks that aim to compromise healthcare data and render the HIoT systems untrustworthy. Furthermore, such cyberattacks compromise the efforts and aspirations of the healthcare sector’s determination to improve the quality of life through the adoption of HIoT technologies. Thus, these challenges call for a discourse on mechanisms and measures required to increase the security resilience of HIoT systems in the healthcare sector. This paper aims to present an outlook of resilience thinking from various academic disciplines, which could provide philosophical insights to the security by design perspective for the development of HIoT technologies.
... To incorporate ERS objectives, the three steps in red in Figure 2 have been identified as new steps to be added to the current AoA process. 5 Instead of considering a limited number of PBDs, the design space should be expanded by generating a large number of potential alternatives. This in turn could generate alternatives that would be more and less resilient then those generated using the PBD methodology. ...
... To explore the design space, this research has developed an integrated trade-off analytics framework for defining and evaluating complex engineered systems considering multiple missions, scenarios, uncertainties, functions, and measures. 5 Using MBE, this framework incorporates integrated models that simultaneously propagate design decisions into the value and cost models to provide the affordability tradespace. This integrated framework uses the three types of analytics: descriptive, predictive, and prescriptive. ...
The Engineered Resilient Systems research program seeks to improve decision making in the Analysis of Alternatives process by leveraging model-based engineering (MBE) early in the design process to develop more resilient systems. Traditional tradespace exploration using point-based design often converges quickly to an initial baseline design concept with subsequent engineering changes to modify the design. However, this process can lead to significant cost growth if the initial concept is not able to meet requirements or if the revised design is not affordable. Enabled by MBE, set-based design (SBD) considers sets of all possible design concepts and down-selects design concepts to converge to a final design using insights into design trade-off analysis, modeling and simulation, and test data. Using a notional unmanned aerial vehicle case study with low-fidelity physics-based models and an open source Excel® add-in called SIPmath©, this research implements an integrated MBE trade-off analytics framework that simultaneously generates numerous SBDs using parametric performance and cost models and evaluates the designs in the value and cost tradespace. In addition, this research explores incorporating resilience quantification and uncertainty into SBD trade-off analysis. Future research is needed to validate the use of SBD with low-fidelity models for tradespace exploration in early system design.
... To better describe the relevancy of decisions and uncertainties leading to affordability and the types of analytics performed at each stage of analysis, we have developed a framework for integrated AoA from these principles. This framework, illustrated in Figure 1, depicts three types of analytics and uses conditional notation to reduce the visual complexity of the diagram (Small et al., 2018). ...
... Current AoA best practices support the ultimate objective of an AoA, which is to "enable senior decision makers to debate and assess a potential program's operational capability and affordability" (Office of Aerospace Studies, 2013, p 2). Toward this goal, Small et al. (2018) Explicitly, ERS seeks to enhance AoA best practices by 1) expanding the identified design space beyond a limited number of alternatives and provide resilience options currently unconsidered; 2) extending service lifetime beyond the initial planning horizon through increased and defined resilience values enabling better survival or new use in future threats and new missions; and 3) assessing resilience tradeoffs in addition to capability tradeoffs to improve the ability of the senior decision maker to assess capability and affordability in the face of environmental and adversarial threats (Small et al., 2018). ...
... Current AoA best practices support the ultimate objective of an AoA, which is to "enable senior decision makers to debate and assess a potential program's operational capability and affordability" (Office of Aerospace Studies, 2013, p 2). Toward this goal, Small et al. (2018) Explicitly, ERS seeks to enhance AoA best practices by 1) expanding the identified design space beyond a limited number of alternatives and provide resilience options currently unconsidered; 2) extending service lifetime beyond the initial planning horizon through increased and defined resilience values enabling better survival or new use in future threats and new missions; and 3) assessing resilience tradeoffs in addition to capability tradeoffs to improve the ability of the senior decision maker to assess capability and affordability in the face of environmental and adversarial threats (Small et al., 2018). ...
The Department of Defense Engineered Resilient Systems (ERS) goes beyond the concept of resilience as a response to a disruption. The ERS project focuses on improving design agility and cost-effectiveness leading to improvements in systems analysis, development, testing, manufacturing, and fielding of mission-effective and adaptable systems. Point-Based Design (PBD) seeks to select a point as a design baseline and proceed into development. Our research uses Set-Based Design (SBD) for early concept evaluation of engineered systems as an alternative to PBD. SBD seeks to eliminate less cost-effective sets (in the value vs. cost tradespace) and focus on one or more remaining sets during early design. Our research develops a technique called Convergent Set-Based Design (SBD), a procedure for mathematical elimination and improvement of sets of designs. We developed Convergent SBD for the ERS program. Our research includes the capability to measure and quantify mission resilience using probability trees for all system performance measures. Convergent SBD uses dominance identification equations to compare statistical means for value and cost. The demonstration illustrates the effect of adding mission resilience in the design tradespace. Convergent SBD provides a foundational mathematical technique for eliminating less promising design sets and identifying the most promising design sets.
... This work found that incorporating various nonfunctional attributes into the design of systems increases the resiliency of the system and that engineers should move beyond the evaluation of a few point solutions to a larger tradespace exploration. 5 Tradespace exploration tools provide a means to evaluate thousands of design alternatives to understand the resiliency of a system's design under uncertainty and provide systems engineers the ability to engineer resiliency into a system. 6 Systems engineers can also leverage modelbased systems engineering to explore the tradespace and determine how the ilities influence a system's resiliency. ...
This article examines how the ilities, or nonfunctional attributes, help to understand the concept of resiliency in engineered systems. For engineered systems, resiliency describes the ability of a system to react to and return to full function after an interruption to system operation. The literature on resiliency of engineered systems defines resiliency in both the context of mission and platform resiliency; however, it leaves an opportunity to research how to understand, manage, and achieve resiliency. This work proposes an application of the systems engineering ilities to resiliency to understand how systems engineers can account for resiliency in the design process and incorporate resiliency into systems. Quality, robustness, and agility assist in understanding the components of resiliency and the ilities of repairability, extensibility, flexibility, adaptability, and versatility provide means for systems to achieve resiliency. This article applies this framework to examine two cases of DoD systems, the B‐52 bomber and the F‐117 stealth fighter. These two examples demonstrate how nonfunctional attributes enable engineered systems to achieve resiliency and help to better understand the concept of resiliency in engineered systems.
... A resilient ecosystem can stay in equilibrium when facing a stressor or can adapt and enter a new stable state; it changes its structure while maintaining its functionality, through this process, the system guarantees its existence. 29 The behavior of organizations in business environments is typical of complex adaptation systems, 30,31 complex and adaptation because of the diversity and interconnections of the elements and their learning and adaptation capabilities. Resilience theory in organizations has under three perspectives, strategic, corporate, and organizational. ...
The global economy is characterized by a progressive complexity, uncertainty, and volatility, which exert intense pressures to organizations and confronts them, with increasing frequency, to disruptive and unexpected events. In such environments, some organizations develop a resilience profile to increase the capacity to anticipate, adapt, and recover equilibrium or even, gain a new advantage position after the disruption. In this research, the factors of organizational resilience (OR) are identified and a structural equations model is developed. The article discusses the theoretical background and the literature of the resilience factors, and proposes their classification, which is used for the development of a questionnaire for the determination of the relative importance of the factors in several industrial sectors. The internal consistency of the questionnaire was validated with the Cronbach’s α coefficient and was applied to a sample of 159 manufacturing companies of the twin plant “maquiladora” industry of Ciudad Juarez, México, using a convenience sampling method. The key driver factors related to the development of OR are identified employing a partial least squares structural equation modeling approach, also is developed a structural model as a predictor of OR and its effectiveness, covering the description of the proposed model. By hypotheses tests, it is verified that resilient leadership explains the role of variables related to the development of OR, having a high influence in the organizational culture and in the capacity to organize and manage operations, being these three contributors, the drivers of the adaptation capacity that has a direct relation to the development of resilience.
Self-driving cars, believed to be on track to become a seven trillion-dollar industry by 2050, are likely to be a popular mode of transportation in the near future, as the technology promises safety and efficiency. Significant advances have been made to achieve these objectives. However, the idea of a self-driving car completing its goals without human intervention in the presence of uncertainties is still posed with challenges. These challenges mostly relate to decision-making under uncertainties that could arise from transient faults or deliberate attempts to disrupt the system in favor of adversarial motives. Traditional schemes of hardening the system against known compromises will not suffice primarily because of the sophistication adversarial attempts have come to achieve and the rate at which new attacks are being devised. The problem demands a solution that is resilient to attacks and that would allow a self-driving vehicle to complete its designated task in the presence of attacks or faults. Several attempts have been made towards achieving resilience in autonomous vehicles. To the best of our knowledge, this is the first work to give a thorough review on the resilient approaches adopted in the context and presents a taxonomy of such approaches. The paper also includes a brief introduction to the architecture of self-driving vehicles and its vulnerabilities in the presented context. This paper also discusses a novel approach using N-version programming for resilience.
