2012). Risk attitudes in risk-based design: Considering risk attitude using utility theory in risk-based design. AbstractEngineering risk methods and tools account for and make decisions about risk using an expected-value approach. Psychological research has shown that stakeholders and decision makers hold domain-specific risk attitudes that often vary between individuals and between enterprises. Moreover, certain companies and industries (e.g., the nuclear power industry and aerospace corporations) are very risk-averse whereas other organizations and industrial sectors (e.g., IDEO, located in the innovation and design sector) are risk tolerant and actually thrive by making risky decisions. Engineering risk methods such as failure modes and effects analysis, fault tree analysis, and others are not equipped to help stakeholders make decisions under risk-tolerant or risk-averse decision-making conditions. This article presents a novel method for translating engineering risk data from the expected-value domain into a risk appetite corrected domain using utility functions derived from the psychometric Engineering Domain-Specific Risk-Taking test results under a single-criterion decisionbased design approach. The method is aspirational rather than predictive in nature through the use of a psychometric test rather than lottery methods to generate utility functions. Using this method, decisions can be made based upon risk appetite corrected risk data. We discuss development and application of the method based upon a simplified space mission design in a collaborative design-center environment. The method is shown to change risk-based decisions in certain situations where a risk-averse or risk-tolerant decision maker would likely choose differently than the expected-value approach dictates.

Accurately capturing the future demand for a given product is a hard task in today’s new product development initiatives. As customers become more market-savvy and markets continue fragment, current demand models could greatly benefit from exploiting the rich contextual information that exists in customers’ product usage. As such, we propose a Usage Coverage Model (UCM) as a more thorough means to quantify and capture customer demand by utilizing factors of usage context in order to inform an integrated engineering design and choice modeling approach. We start by presenting the principles of the UCM model: terms, definitions, variable classes and relation classes so as to obtain a common usage language. The usage model exhibits the ability to differentiate between individuals’ product performance experiences. With Discrete Choice Analysis, individuals’ performance with a given product is compared against that of competitive products, capturing individual customers’ choice behavior and thereby creating an effective model of product demand. As a demonstration of our methods, we apply our model in a case study regarding the general task of cutting a wood board with a jigsaw tool. We conclude by presenting the scope of future work for the case study and the contribution of the entire current and future work to the field as a whole.

System verification is one of the most critical tasks into the process of engineered system design. This process is time-consuming and prone with errors when a limited set of scenarios is evaluated to guarantee the correct functionality of the system. Therefore, novel design approaches and tools based on a rigorous framework for analysis, verification, and testing are very much needed. This paper provides such a framework where system properties are verified and modeled with respect to the assumptions on the environment where components and (sub)systems\u27 performances are guaranteed under these assumptions. To validate the proposed approach, this paper provides a case study to demonstrate how the proposed methodology reduces design complexity and presents a formal argument to assess the quality of the design

Integrated Systems Health Management (ISHM) is a desired system engineering capability to detect, assess, and isolate faults in complex aerospace systems to improve safety and reliability. At the conceptual design level, system-level engineers must make decisions regarding the extent of vehicle fault coverage using on-board sensors and the data collection, processing, interpretation, display, and action capabilities for the various subsystems, all considered essential parts of ISHM. In this paper, we propose a CostBenefit Analysis approach to initiate the ISHM design process. The key to this analysis is the formulation of an objective function that explicitly quantifies the cost-

This paper presents a complex network and graph spectral approach to calculate the resiliency of complex engineered systems. Resiliency is a key driver in how systems are developed to operate in an unexpected operating environment, and how systems change and respond to the environments in which they operate. This paper deduces resiliency properties of complex engineered systems based on graph spectra calculated from their adjacency matrix representations, which describes the physical connections between components in a complex engineered systems. In conjunction with the adjacency matrix, the degree and Laplacian matrices also have eigenvalue and eigenspectrum properties that can be used to calculate the resiliency of the complex engineered system. One such property of the Laplacian matrix is the algebraic connectivity. The algebraic connectivity is defined as the second smallest eigenvalue of the Laplacian matrix and is proven to be directly related to the resiliency of a complex network. Our motivation in the present work is to calculate the algebraic connectivity and other graph spectra properties to predict the resiliency of the system under design.