Douglas L. Van Bossuyt

Risk attitudes in risk-based design: Considering risk attitude using utility theory in risk-based design

Abstract Engineering 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 decision-based 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.

Modeling of function failure propagation across uncoupled systems

The design of modern complex engineered systems must rapidly and accurately be developed to satisfy customer needs while accomplishing required functions with a minimum number of failures. Failure analysis in the conceptual stage of design, including the propagation of failures, has expanded in recent years to account for failures in functional modeling. However, function failure propagation across uncoupled functions and subsystems has not been fully addressed; failures are known to cross these boundaries in complex systems. To address this research gap, a functional model based geometric method of predicting and mitigating functional failure propagation across systems, which are uncoupled during nominal use cases, is presented. Geometric relationships including function location and physical properties are established between uncoupled functions to serve as failure propagation flow paths. Mitigation options are developed based upon the geometric relationships and a path toward physical functional layout is provided to limit failure propagation across uncoupled subsystems. The model-based geometric method of predicting and mitigating functional failure propagation across uncoupled engineered systems guides designers toward improved protection and isolation of cross-subsystem failure propagation. The proposed method is validated using the case study of a pressurized water nuclear reactor modeled using APROS, a first principal simulator. Results identified that the top 10 failures exceeded those of PRA in importance based on the probability of failure.

Toward an Automated Model-Based Geometric Method of Representing Function Failure Propagation Across Uncoupled Systems

The complex engineered systems being designed today must rapidly and accurately be developed to satisfy customer needs while accomplishing required functions with a minimum number of failures. Failure analysis in the conceptual stage of design has expanded in recent years to account for failures in functional modeling. However, function failure propagation across normally uncoupled functions and subsystems has not been fully addressed. A functional model-based geometric method of predicting and mitigating functional failure propagation across systems, which are uncoupled during nominal use cases, is presented. Geometric relationships between uncoupled functions are established to serve as failure propagation flow paths. Mitigation options are developed based upon the geometric relationships and a path toward physical functional layout is provided to limit failure propagation across uncoupled subsystems. The model-based geometric method of predicting and mitigating functional failure propagation across uncoupled engineered systems guides designers toward improved protection and isolation of cross-subsystem failure propagation.Copyright

Toward Understanding Collaborative Design Center Trade Study Software Upgrade and Migration Risks

Collaborative design centers often employ software tools to conduct trade studies. Commonly, this takes the form of a software program to aggregate and pass data between multiple computer workstations. This allows multiple people to concurrently create a conceptual design. Trade study software continues to evolve to meet the demands of modern collaborative design centers. However, the risks associated with moving from one trade study software tool to another are not well understood. Additionally, little is known about the software preferences of Collaborative Design Center (CDC) staff. This paper determines software preferences of two user groups consisting of graduate and undergraduate mechanical engineering students. This paper then explores the risks in deploying new trade study software in a collaborative design center. A method for estimating and mitigating risks with changing trade study software is presented. Recommendations for a smooth transition between software packages are given. The risk model developed in this paper offers a quick way of estimating and mitigating conversion risk for collaborative design centers.© 2010 ASME

Cable routing modeling in early system design to prevent cable failure propagation events

In the early engineering design phases of complex systems and facilities with significant cable routing requirements, the protection of critical cabling infrastructure and separation of redundant cables is often not taken into account. Cable routing and management happens later in the design process after significant system architectural decisions have been made. Given the nature of cables where energy and signal functions are shared between major subsystems, the potential for failure propagation is significant. We propose the Cable Routing Function Failure Analysis (CRFFA) method of cable routing planning that integrates with functional modeling and function failure analysis of complex systems to be used during the early conceptual stages of design. Through a more complete understanding of power and data cabling requirements during the early phases of design, a system design can be developed that minimizes the potential for critical cable infrastructure to be collocated. Reductions in collocated critical cabling reduce potential failure propagation pathways. The method in this paper relies on functional failure propagation probability calculation methods to identify and avoid potentially high risk cable routing choices. The implementation of this method will help engineering practitioners to design complex systems and facilities that protect against cabling failure propagation events (cable raceway fires, cable bundle severing events, etc.) from the earliest phases of design. Thus, system reliability will increase while system failure probabilities, cost of system design, and design lifecycles will decrease.

Toward a Functional Failure Modeling Method of Representing Prognostic Systems During the Early Phases of Design

Current methods of functional failure risk analysis do not facilitate explicit modeling of systems equipped with Prognostics and Health Management (PHM) hardware. As PHM systems continue to grow in application and popularity within major complex systems industries (e.g. aerospace, automotive, civilian nuclear power plants), implementation of PHM modeling within the functional failure modeling methodologies will become useful for the early phases of complex system design and for analysis of existing complex systems. Functional failure modeling methods have been developed in recent years to assess risk in the early phases of complex system design. However, the methods of functional modeling have yet to include an explicit method for analyzing the effects of PHM systems on system failure probabilities. It is common practice within the systems health monitoring industry to design the PHM subsystems during the later stages of system design — typically after most major system architecture decisions have been made. This practice lends itself to the omission of considering PHM effects on the system during the early stages of design. This paper proposes a new method for analyzing PHM subsystems’ contribution to risk reduction in the early stages of complex system design. The Prognostic Systems Variable Configuration Comparison (PSVCC) eight-step method developed here expands upon existing methods of functional failure modeling by explicitly representing PHM subsystems. A generic pressurized water nuclear reactor primary coolant loop system is presented as a case study to illustrate the proposed method. The success of the proposed method promises more accurate modeling of complex systems equipped with PHM subsystems in the early phases of design.Copyright

Toward a Market-Based Lean Startup Product Design Method for the Developing World

The question of how to effectively design products for consumers in the developing world has been widely debated. Several methodologies have been developed to address this issue focusing on human centered and community centered methods, but few methods are rooted in market-centered approaches. Recent advances in market-centered design from lean startup methodologies hold promise for the development of new methods that allow effective product design for consumers in the developing world. This paper contributes a method from which consumer level products can be designed to effectively supply the under-served markets of the developing world with innovative and sustainable solutions. Utilizing an iterative method based on three fundamental hypotheses, the Lean Design for Developing World Method (LDW) seeks to provide products that are economically viable, have strong market growth potential, and have a net positive impact on the customers and their communities.Copyright

Functional Impact Comparison of Common and Innovative Products

Innovation has been touted as a means toward providing sustainability. Innovations in materials, manufacturing, and product design can lead to a reduction of global environmental impacts while helping to realize the goals of a sustainable society. This research aims to explore whether or not product functionality has an effect on environmental impact and if the flow of energy, materials, and signals (EMS) have an effect on product environmental impact. Innovative and common products are identified and life cycle assessment is performed for each product at the component level. Using function impact matrices, the environmental impacts of the product components are propagated back to the functional level, where their impacts are compared. The innovative products of the comparisons conducted appear to be more environmentally impact; more work must be done to understand whether the result is generalizable. The intended use of this research is during the conceptual design phase when little is known about the final form of a product. With approximate impacts of functions known, designers can better utilize their design efforts to reduce overall product environmental impact.Copyright

TOWARD CONSIDERING RISK ATTITUDES IN ENGINEERING ORGANIZATIONS USING UTILITY THEORY

Design projects within large engineering organizations involve numerous uncertainties that can lead to unacceptably high levels of risk. Practicing designers recognize the existence of risk and commonly are aware of events that raise risk levels. However, a disconnect exists between past project performance and current project execution that limits decision-making. This disconnect is primarily due to a lack of quantitative models that can be used for rational decision-making. Methods and tools used to make decisions in risk-informed design generally use an expected value approach. Research in the psychology domain has shown that decision-makers and stakeholders have domainspecific risk attitudes that often have variations between individuals and between companies. Risk methods used in engineering such as Failure Modes and Effects Analysis (FMEA), Fault

Toward a Dedicated Failure Flow Arrestor Function Methodology

Risk analysis in engineering design is of paramount importance when developing complex systems or upgrading existing systems. In many complex systems, new generations of systems are expected to have decreased risk and increased reliability when compared with previous designs. For instance, within the American civilian nuclear power industry, the Nuclear Regulatory Commission (NRC) has progressively increased requirements for reliability and driven down the chance of radiological release beyond the plant site boundary. However, many ongoing complex system design efforts analyze risk after early major architecture decisions have been made. One promising method of bringing risk considerations earlier into the conceptual stages of the complex system design process is functional failure modeling. Function Failure Identification and Propagation (FFIP) and related methods began the push toward assessing risk using the functional modeling taxonomy. This paper advances the Dedicated Failure Flow Arrestor Function (DFFAF) method which incorporates dedicated Arrestor Functions (AFs) whose purpose is to stop failure flows from propagating along uncoupled failure flow pathways, as defined by Uncoupled Failure Flow State Reasoner (UFFSR). By doing this, DFFAF provides a new tool to the functional failure modeling toolbox for complex system engineers. This paper introduces DFFAF and provides an illustrative simplified civilian Pressurized Water Reactor (PWR) nuclear power plant case study.Copyright