A novel "resilience viewpoint" to aid in engineering resilience in systems of systems (SoS)

Designing evolutionary systems to meet stakeholder expectations on safety, reliability and overall resilience is of great importance in an age of interconnectivity and high dependency systems. With incidents and disruptions becoming more frequent in recent years, the requirement for systems to demonstrate high levels of resilience given the economic, political and temporal dimensions of complexity, resilience is of great significance today. Systemic resilience is of high importance at the global level. Therefore, the role of the system engineer and architect is becoming more demanding due to the need to consider requirements from a broader range of stakeholders and to implement them into early conceptual designs. The early modeling process of all systems is common ground for most engineering projects, creating an architecture to both understand a system and to design future iterations by applying model-based processes has become the norm. With the concept of systems-ofsystems (SoS) becoming common language across multiple engineering domains, model-based systems engineering techniques are evolving hand-in-hand to provide a paradigm to better analyse current and future SoS. The intrinsic characteristics of the constituent systems that make up the SoS make the challenge of designing and maintaining the reliability and resilience of a systems extremely difficult. This paper proposes a novel viewpoint, within an architecture framework (based around DoDAF, MoDAF and UPDM) to aid systems architects explore and design resilient SoS. This is known as the Resilience Viewpoint. Much of the research in the area is focussed on critical infrastructure (CI), looking at telecommunication networks, electric grid, supply networks etc, and little has been done on a generalizable tool for SoS architecture analysis, especially using existing modeling languages. Here, the application of the ‘Resilience Viewpoint’ is demonstrated using a case study from an integrated water supply system of systems, to portray its potential analytical capabilities

A resilience measure to guide system design and management

This paper presents a measure of resilience which can guide system design and management. Systems design must incorporate resilience to provide stakeholders with the most appropriate solution for their life-cycle needs. Design of resilient systems demands a measure of the resilience afforded by a system proposal which can be used to compare design proposals. The measurement method should balance the interest in resilience with all other proposal evaluation criteria, and incorporate the effect of the sequence of unknown future events affecting the system. Ideally, the resilience measure should also be useful to guide management decisions re maintenance or upgrade during the system life. This paper presents a method to measure system resilience which can be applied to engineered systems in general, not just a specific class of systems, is threat type agnostic, and does not presuppose any ‘desirable’ outcome allowing a system specific determination of ‘desirable’ outcomes

Using the Delphi method to develop the social-ecological resilience indicators of organic rice production in Thailand

This paper illustrates the application of the Delphi method, which assists in the production of social-ecological resilience indicators, and which are suitable for building the resilience of organic rice production in the central portion of Northeastern Thailand. Forty-seven adept farmers were purposively selected as participants, and the Delphi method was utilized as a tool by which the participants could reveal their different opinions and ideas. They were surveyed in order to visualize an organic rice system called the ‘desirable system.’ Nevertheless, such a system must be built simultaneously with certain components, the attributes of which can enable the system to withstand all kinds of change that can take place across spatial and temporal scales. The resilience literature, which is related to agro-ecological systems, had been published online during the seven previous years, and was applied to formulate questions, which were specifically aimed at establishing components that were focused upon coping and adaptive strategies. It was discovered that the inclusion of a group discussion, which had taken place with two rounds of the Delphi method, had provided a valuable means for exchanging information and responding with feedback. Given that the processes had been entirely conducted through group discussions, the voices of a few participants were, however, lost. They were dominated by the innate power expressed by other members within the group, especially the leaders. Despite this, the Delphi method was able to achieve an adequate degree of consensus among participants and was able to lead in the direction of building resilience with a significant level of confidence, which was capable of overcoming the social-ecological complexities of organic rice production. This was evidenced by the discovery of 21 social-ecological resilience indicators, which had been constructed by the engagement. Moreover, the indicators had indeed been reliable. With the support of the consensus of the participants’ judgements, which were based on their actual contexts of organic rice production in the central portion of Northeastern Thailand, the indicators were able to be validated by statistical analyses, consisting of arithmetic means (x), standard deviations (sd), and interquartile ranges (R)

Measurement of resilience and the time value of resilience

In prior work, a measure of resilience for use in systems design and management was presented. The measure has the form of a time integral of the system performance level. This form generates the research question: Is the time value of resilience a meaningful concept, like the time value of money in engineering economics. This article presents four scenarios to explore the relationship between time and the value of resilience of a product or system. The scenarios are: perishable commodity packaging, the value of resilience rapidly diminishes after the contents’ expiry; a consumer durable product for use in an evolving environment and interface requirement, where the value of resilience is related to the expiry of platform resilience capability; a national infrastructure asset, where usage increases during the system life; and a factory, where the value of resilience depends on the obsolescence of the product. In the first two and last cases, the value of resilience is high for a finite interval and then low or zero. In the third, the value of resilience increases as the asset age

Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

Learner-focussed methodology for improving the resilience of training organisations in complex environments

Organisations are increasingly relying on resilience to adapt to uncertain and evolving operational environments, whilst continuing to achieve their requirements, and addressing pathologies in their organisational design and operations. The challenge is exacerbated by the growing organisational complexity, competing priorities and unintended consequences from various system modifications and trade-off decisions. To address the organisational resilience challenges, a comprehensive approach to organisational resilience is required. Despite the proliferation of resilience research in the academic literature, organisational resilience practitioners do not have a holistic practical methodology on how to design and maintain resilience in continuously operating and mature organisations. The research reports its comprehensive approach to ensuring desired organisational performance and resilience characteristics. The key aspects of resilience and organisation are determined in the extensive literature review and key stakeholder engagements, followed by the establishment of the current ‘as is’ state of a Defence training organisation. It is characterised by a mature design, complexity, and the need for uninterrupted delivery of its functions in continuous operations. The research combines resilience conceptualisation and organisational design review outcomes to formulate its approach to the organisational transition from the current ‘as is’ to the future ‘to-be’ state to secure a long-term delivery of the required outputs under diverse stressors. The approach is based on an original resilience framework and architecture; new resilience measures introduced via the survey instrument; and non-traditional application of various system thinking and modelling and simulation methodologies to review and modify a mature and fully operational training organisation targeting resilience. The approach was applied in more than 20 Defence training establishments at different levels of aggregation over three years and reported indicative results and real benefits to the participating organisations, as well as research limitations, contributions, and continuous improvement strategies. Although a Defence training organisation context is used in this paper, the principles of the research approach may be applied to any organisation. Future research directions concern further quantification of organisational resilience aspects such as their interrelationships effect on organisational performance and organisational importance ratings; expanding the scope of organisational context from training to include other organisational types; and developing automation approaches for the resilience survey data analysis and reporting

System of Systems Stakeholder Planning in a Multi-Stakeholder, Multi-Objective, and Uncertain Environment

The United States defense planning process is currently conducted in a partially consolidated manner driven by the Joint Capabilities Integration and Development System (JCIDS) process. Decisions to invest in technology, develop systems, and acquire assets are made by individual services with coordination at the higher joint level. These individual service’s decisions are made in an environment where resource allocation and need are influenced by external stakeholders (e.g. shared system development costs, additional levied requirements, and complementary system development). The future outcome of any given decision is subject to a high degree of uncertainty stemming from both the stakeholder execution of a decision and the environment in which that execution will take place. Uncertainty in execution stems from TRL advancement, development timelines, acquisition timelines, and final deployed performance. Environmental uncertainty factors include future stakeholder resource availability, the future threat environment, cooperative stakeholder decisions, and mirrored adversary decisions. The defense planning problem can be described as an acknowledged System of Systems (SoS) planning problem. Today, methodologies exist that individually address SoS Engineering processes, the evaluation of SoS performance, and SoS system deterministic evolution. However, few approaches holistically address the SoS planning and evolution problem at the level needed to assist individual defense stakeholders in strategic planning. Current approaches do not address the impact of multiple-stakeholder decisions, multiple goals for each stakeholder, the uncertainty of decision outcomes, and the temporal component to strategic decision making. This thesis develops and tests a methodology to address defense stakeholder planning in a multi-stakeholder, multi-objective, and uncertain environment. First, a decision space is populated and captured via sampling a game framework that represents multiple stakeholder decisions as well as decision outcomes over time. A compressed Markov Decision Process (MDP) based meta-model is constructed using state-space consolidation techniques. The meta-model is evaluated using a risk-based policy development algorithm derived from combining traditional Reinforcement Learning (RL) techniques with mean-variance portfolio theory. Policy sensitivity to stakeholder risk-tolerance levels is used to develop state-based risk-tolerance sensitivity profiles and identify Pareto efficient actions. The risk-tolerance sensitivity profiles are used to evaluate both state spaces and decision spaces to provide stakeholders with risk-based insights, or rule sets, to support immediate decision making and risk-based stakeholder playbook development. The capability of the risk-based policy algorithm is tested using both elementary and complex scenarios. It is demonstrated that the algorithm can be used to extract Pareto efficient decisions as a function of risk-tolerance. The state space compression is tested via the comparison of the loss of information between the risk-based policy solutions for uncompressed and compressed state space. The full methodology is then demonstrated using a full-complexity scenario based on the joint development by France, Germany, and Spain of the SoS based Future Combat Air System (FCAS). The full complexity scenario is used to baseline the risk-based methodology against current optimal policy solution techniques. A significant increase in resulting derived insights relative to optimal policy solutions in a high uncertainty scenario is demonstrated.Ph.D