Donna H. Rhodes

Engineering Systems Multiple-Domain Matrix: An organizing framework for modeling large-scale complex systems

The scope and complexity of engineered systems are ever-increasing as burgeoning global markets, unprecedented technological capabilities, rising consumer expectations, and ever-changing social requirements present difficult design challenges that often extend beyond the traditional engineering paradigm. These challenges require engineers and technical managers to treat the technological systems as a part of a larger whole. Existing system modeling frameworks are limited in scope for representing the information about engineering systems. This paper presents a conceptual framework and an improved modeling framework for engineering systems. Its value is that it allows engineers and managers an improved means to visually arrange information and structure discourse in a way that facilitates better systems engineering. It augments the existing literature by providing a clear and concise framework for an engineering system, and provides a methodology for engineers to tag and organize systems information in ways that allow for better collection, storage, processing, and analysis of systems engineering data.

Architecting the system of systems enterprise: Enabling constructs and methods from the field of engineering systems

Engineering systems is a field of scholarship focused on developing fundamental theories and methods to address the challenges of large-scale complex systems in context of their socio-technical environments. The authors describe facets of their recent and ongoing research within the field of engineering systems to develop constructs and methods for architecting enterprises engaged in system-of-systems (SoS) engineering,. The ultimate goal of the research is to develop a framework for characterizing, designing, and evaluating SoS enterprise architectures throughout the system lifespan as various forces result in entering/exiting of constituent systems, changing environment, and shifting enterprise profile. The nature of systems-of-systems demands constructs for multi-dimensional architectural descriptions, as well as methods for design and evaluation that employ dynamic approaches. In this paper, two important elements in an emerging framework are described, including a holistic enterprise architecting framework and an epoch-based analysis method for examining possible futures of the SoS enterprise.

Real Options in Enterprise Architecture: A Holistic Mapping of Mechanisms and Types for Uncertainty Management

Uncertainty management is crucial for achieving high performance in enterprises that develop or operate complex engineering systems. This study focuses on flexibility as a means of managing uncertainties and builds upon real options analysis (ROA) that provides a foundation for quantifying the value of flexibility. ROA has found widespread applications ranging from strategic investments to product design. However, these applications are often isolated to specific domains. Furthermore, ROA is focused on valuation, rather than the identification of real options. In this paper, we introduce a framework for holistic consideration of real options in an enterprise context. First, to enable a holistic approach, we use a generalized enterprise architecture framework that considers eight views: strategy, policy, organization, process, product, service, knowledge, and information technology (IT). This expands upon the classical IT-centric view of enterprise architecture. Second, we characterize a real option as a mechanism and type. This characterization disambiguates among mechanisms that enable flexibility and types of flexibility to manage uncertainties. Third, we propose mapping of mechanisms and types to the enterprise architecture views. We leverage this mapping in an integrated real options framework and demonstrate its benefit over the traditional localized approach to ROA.

Responsive systems comparison method: Dynamic insights into designing a satellite radar system

Often shifts in context, such as changes in budgets, administrations, and warfighter needs, occur more frequently than high-cost space-based system development timelines. In order to ensure the successful development and operation of such systems, designers must balance between anticipating future needs and meeting current constraints and expectations. This paper describes the application of Multi-Epoch Analysis on a previously introduced satellite radar system program case study, quantitatively analyzing the impact of changing contexts and preferences on “best” system designs for the program. Each epoch characterizes a fixed set of context parameters, such as available technology, infrastructure, environment, and mission priorities. For each epoch, several thousand design alternatives are parametrically assessed in terms of their ability to meet imaging, tracking, and programmatic expectations using Multi-Attribute Tradespace Exploration. While insights on tradeoffs are discovered within a particular epoch, further dynamic insights become apparent when comparing tradespaces across multiple epochs. The Multi-Epoch Analysis reveals three key insights: 1) the ability to quantitatively investigate the impact of “requirements” across many systems and contexts, 2) the ability to quantitatively identify value “robust” systems, including both passively robust and changeable systems, and 3) the ability to quantitatively identify key system tradeoffs and compromises across stakeholders and missions.

Responsive Systems Comparison Method: Case Study in Assessing Future Designs in the Presence of Change

In this short paper, the Responsive Systems Comparison (RSC) method is introduced. RSC is a structured method for collecting information and conducting analysis to characterize a wide variety of possible futures in order to enable the comparison of the performance of proposed systems in those futures. A case study uses the RSC to analyze a satellite radar system. The needs and expectations of a user community for such a system, the context it will operate in, and its technical basis are determined both at the present time, and with possible changes over the next 15 years. This information is used to set up an analysis that should be able to highlight systems that will deliver value under a wide variety of future situations. The case study illustrates the practicality of the method, and provides lessons for improvement and implementation.

Using Pareto Trace to determine system passive value robustness

An important role of system designers is to effectively explore the tradespace of alternatives when making design decisions during concept phase. As systems become more complex, formal methods to enable good design decisions are essential; this can be empowered through a tradespace exploration paradigm. This paper demonstrates the use of the Pareto Trace and associated metrics to identify system alternatives across tradespaces with high degrees of passive value robustness—alternatives that continue to deliver value to stakeholders in spite of changes in needs (attributes) or context. A value-driven tradespace approach is used to represent the baseline performance versus cost of a large number of system alternatives. The classical notion of Pareto Set is extended to identify alternatives and their characteristics that lead to their inclusion in Pareto Sets across changing contexts. Using a low-earth orbiting satellite case example, five types of context changes are used to demonstrate this method: 1) addition or subtraction of attributes; 2) change in the priorities of attributes; 3) change in single attribute utility function shapes; 4) change in multi-attribute utility aggregation function; and 5) addition of new decision maker. This approach demonstrates the ability for system designers to pose questions about assessment of alternatives during early conceptual design. Suggestions for application of Pareto Trace beyond the case example are discussed and presented, including application of a “fuzziness” factor and statistical measures. In particular, distinctions from traditional sensitivity analysis are made, as well as linkages to dynamic analysis for discovery of generalized value robust alternatives.

Scenario planning in dynamic multi-attribute tradespace exploration

The long time scales associated with complex system design and operation necessitate front-end systems engineering methodologies that enable consideration of alternative futures. This paper advances scenario planning techniques through a parameterization and ordering of potential future contexts and stakeholder expectations (e.g., articulated system attributes, available technology, funding levels, and supporting infrastructures). After surveying existing approaches for scenario planning, a methodology for specifying and analyzing large numbers of alternative system timelines is presented. A satellite radar case study is used to motivate and illustrate the value of this approach. Benefits of the methodology include: (1) broader and more rigorous consideration of alternative future needs, contexts, and timelines, (2) identification of gaps in traditionally-derived scenario sets, (3) identification of passively value-robust system alternatives, and (4) providing a basis for evaluating system evolution strategies that enable sustainment of value delivery across potential timelines.

Aligning Perspectives and Methods for Value-Driven Design

Recent years have seen a push to use explicit consideration of “value” in order to drive design. This paper conveys the need to explicitly align perspectives on “value” with the method used to quantify “value.” Various concepts of value are introduced in the context of its evolution within economics in order to propose a holistic definition of value. Operationalization of value is discussed, including possible assumption violations in the aerospace domain. A series of prominent Value-Centric Design Methodologies for valuation are introduced, including Net Present Value, Multi-Attribute Utility Theory, and CostBenefit Analysis. These methods are compared in terms of the assumptions they make with regard to operationalizing value. It is shown that no method is fully complete in capturing the definition of value, but selecting the most appropriate one involves matching the particular system application being valued with acceptable assumptions for valuation. Two case studies, a telecommunications mission and a deep-space observation mission, are used to illustrate application of the three prior mentioned valuation methods. The results of the studies show that depending on method used for valuation, very different conclusions and insights will be derived, therefore an explicit consideration of the appropriate definition of value is necessary in order to align a chosen method with desired valuation insights.

Systems Thinking as an Emergent Team Property: Ongoing research into the enablers and barriers to team-level systems thinking

This paper describes ongoing research exploring systems thinking at the team level. Termed collaborative systems thinking by the authors, the concept of higher level systems thinking is envisioned as a means both to build workforce competency and to explicitly deal with system complexity at a higher level within an organization. This paper introduces the key research questions, an initial definition of collaborative systems thinking, demographic and technical motivators, and summarizes the research progress to date and plan for completion. The results of this research will inform the design of technical processes and provide empirical knowledge to support workforce development interventions aimed at developing systems thinking within engineering teams. The role of organizational culture is also considered as a factor in enabling collaborative systems thinking.

A Logical Approach to Real Options Identification With Application to UAV Systems

Complex systems are subject to uncertainties that may lead to suboptimal performance or even catastrophic failure if unmanaged. Uncertainties may be managed through real options that provide a decision maker with the right, but not the obligation, to exercise actions in the future. While real options analysis has traditionally been used to quantify the value of such flexibility, this paper is motivated by the need for a structured approach to identify where real options are or can be embedded for uncertainty management. We introduce a logical model-based approach to identification of real option mechanisms and types, where the mechanism is the enabler of the option, while the type refers to the flexibility provided by the option. First, we extend the classical design structure matrix and the more general multiple-domain matrix (MDM), commonly used in modeling and analyzing interdependencies in complex socio-technical systems, to the more expressive Logical-MDM that supports the representation of flexibility. Second, we show that, in addition to flexibility, two new properties, namely, optionability and realizability, are relevant to the identification of real options. We use the Logical-MDM to estimate flexibility, optionability, and realizability metrics. Finally, we introduce the Real Options Identification (ROI) method based on these metrics, where the identified options are valued using standard real options valuation methods to support decision making under uncertainty. The expressivity of the logic combined with the structure of the dependency model allows the effective representation and identification of mechanisms and types of real options across multiple domains and lifecycle phases of a system. We demonstrate this approach through a series of unmanned air vehicle scenarios.