Hanumanthrao Kannan

Incorporating Value-Driven Design into the Visualization of Design Spaces Using Contextual Self-Organizing Maps: A Case Study of Satellite Design

This paper presents case study of satellite design using a new method to view ndimensional design or optimization data using a contextual self-organizing map. The technique allows n-dimensional data to be trained without dimensionality reduction or other “compression”. A designer can view similar design points in a true n-dimensional manner. Prior work in visual design space exploration using contextual self-organizing maps is extended through the incorporation of designer preferences using techniques founded in value-driven design. Standard techniques of the self-organizing map are used to group the ndimensional design space into discrete clusters of similar characteristics through neural network-based topological ordering. Techniques from prior work are used to present the designer with a visual display encapsulating statistical qualities of value held within the ndimensional design space. A case study involving a satellite design problem is presented and results compared with recent findings in value-driven design and traditional methods of design optimization. Initial results show unique potential of the combined methods to develop an understanding of the design space topology and to select promising areas of a design space for detailed analysis.

Increased System Consistency through Incorporation of Coupling in Value‐Based Systems Engineering

The design of large-scale complex engineered systems involves hundreds to thousands of designers making decisions across different organizations and at different levels of organizational hierarchy. These systems are designed within a systems engineering framework, where requirements are used as proxies for stakeholder preference. Requirements drive the development process and are flowed across organizations and down through the organizational hierarchies. Value-driven design offers a new perspective where the preferences of the stakeholder are communicated directly through a decomposable value function, rather than decomposable requirements, thereby enabling improved consistency in system preference. This paper investigates two key aspects of achieving improved system consistency through a value-based systems engineering approach, using a commercial satellite system as a testbed. The paper first contrasts the diverse systems that result from traditional requirements-based versus preference-based formulations, demonstrating how a value-based approach aids in capturing the true preferences of the stakeholder in problem formulation. The paper demonstrates the importance of using system couplings to enable an improved accuracy for value function decomposition. The paper demonstrates that ensuring system analysis consistency through use of system sensitivities can overcome issues pertaining to: dependencies of attributes; inadequately capturing system interactions; and direct modification of attributes to determine value impact.

Adding Value to Trade Space Exploration When Designing Complex Engineered Systems

Design decision-making involves tradeoffs between many design variables and attributes, which can be difficult to model and capture in complex engineered systems. To choose the best design, the decision maker is often required to analyze many different combinations of these variables and attributes and process the information internally. Trade Space Exploration (TSE) tools, including interactive and multidimensional data visualization, can be used to aid in this process and provide designers with a means to make better decisions, particularly during the design of complex engineered systems that have multiple, competing objectives. In this paper, we investigate the use of TSE tools to support decision makers using a Value-Driven Design (VDD) approach for complex engineered systems. A VDD approach necessitates a rethinking of TSE, and we outline and illustrate four different uses of a VDD approach to TSE. The research leverages existing TSE paradigms and multidimensional data visualization tools to identify optimal designs when using a value function for a system. A satellite design example is used to demonstrate the differences between a VDD approach to design complex engineered systems and a multiobjective approach to capture the Pareto frontier. Ongoing and future work is also discussed.

Value Impact of an Organization Structure in the Context of Value-Driven Design

The design of Large-Scale Complex Engineered Systems (LSCESs) involves large organizations and groups of individuals. The structure of an organization impacts the design process and is therefore an essential component to the design and development of complex engineered systems. Previous work has demonstrated the merits of using Value-Driven Design (VDD) to improve the engineering process to capture true stakeholder preference, particularly when using Multidisciplinary Design Optimization (MDO) frameworks to design these complex systems. Organization Design (OD) has contributed significantly to the understanding of organization structures and their relationships to efficient resource use. The focal point of this paper is the incorporation of organization structures to the value driven approach of designing complex systems. In particular, the impacts of organization structure on the design process and the design product is explored. A commercial communication satellite is used as an example LSCES to show how capturing the impact of change in organization structure (through individual and team interfaces) can affect the value of a system and thereby provide a means for more informed decision making. The satellite system’s design is considered in both certain and uncertain conditions. The value function used incorporates attributes characterizing the system as well as the engineering process (such as time and analysis costs). The paper demonstrates that the organization structure does affect the value of the system and should be considered at the beginning of the design process.

Preference Modeling for Government-Owned Large-Scale Complex Engineered Systems: A Satellite Case Study

The design of large-scale complex engineered systems (LSCES) has been shown to be a distributed decision-making problem involving hundreds or thousands of designers making decisions at different levels of an organizational hierarchy. Traditional systems engineering (SE) approaches use requirements to communicate the preference(s) of stakeholders to drive the decisions of the designers. Requirements, which act as proxies for actual preferences, only state what is not desired of the system rather than what is wanted. This leads to a lack of consistency in the communication of preferences across the subsystems (and even organizations) involved. Also, the current requirements-based SE approaches do not offer any system-level guidance in choosing the best among feasible design alternatives, where all the designs that satisfy requirements are treated equally. Value-driven design (VDD), an alternative SE approach, offers a new perspective on complex system design and emphasizes the importance of capturing true preferences of stakeholders using a meaningful decomposable value function. The formulation of an all-encompassing value function has been proven to be a very tedious process involving a huge overhead, as it requires understanding of the inherent design trades in the system. Past researchers have focused in detail on formulating value functions for commercial endeavors. The primary focus of this paper is to investigate how the formulation of value functions can be approached in a methodical manner using a data-based approach, specifically for a government-based agency (e.g., NASA). More specifically, this paper focuses on formulating a value function for a space telescope mission by identifying and analyzing different aspects involved in capturing preferences.

Understanding the Impact of Uncertainty on the Fidelity of the Value Model

Engineers often deal with design problems that are large, complex and involving multi-level decision analyses. This is particularly true for aerospace systems. To obtain a suitable design, it is necessary to iterate through numerous data sets and often uncertainties inherent in the system complicate the decision making process.In this paper we study the sensitivities of the inherent uncertainties and its effect on the value function. A satellite design example is used to the investigate the effects and sensitivities of the uncertainties.

Calculating Value Gaps Induced by Independent Requirements, Deterministic Modeling, and Fixed Targets

Requirements have traditionally been used in the design of Large-Scale Complex Engineered Systems for distributed decision making and as a form of communicating preferences. Often requirements are due to physical limitations, but quite often, they are also motivated by providing focus to the designers or contractors. While communicating what the stakeholder does not want, the requirements have the harmful impact of restricting the design space available to the designers. More importantly, when requirements are set independently to designers or contractors, without specifying trade-offs among requirements, they can induce sub-optimal designs leading to loss in value. In addition to requirements for individual design variables, overall system targets—even if framed in terms of value—may also result in suboptimal designs and lost value. This paper examines the loss in value that may occur in in the design of large-scale systems in three different instances: the application of independent requirements in the absence of tradeoffs, the use of a deterministic optimization when uncertainty is present, and the application of system value targets. The design of a satellite is used to illustrate how these value gaps are calculated.