This research is driven by some of the most egregious examples of engineering failures that have arisen from the emergence of unanticipated system behaviors; these failures have resulted in unfortunate casualties, damage to or loss of property, and calamitous impacts to the environment. Examples include the Chernobyl nuclear disaster, the Three Mile Island accident, and the Bhopal gas leak, among others. However, despite the lessons learned and the continued refinement to system engineering operational protocols and procedures, these preventable engineering failures continue to amass. Each of these particular highlighted examples resulted from a set of unintended and emergent operating behaviors, in many cases arising from unforeseen fluctuations in operating environments or operating conditions. This proposed research provides an approach to embed the concepts of resiliency and complexity intelligently and early in the design process, making them fundamental pillars of the design process management.
Intellectual Merit: The objective of this research is to identify best practices for the design and operation of resilient engineered systems. The best practices and the concept of resilience are related to the complexity of a system. This linkage to complexity provides a scalable approach for the design of resilient systems. By offering best practices that scale to quantifiable complexity criteria, an implementable approach is provided for improving system resiliency while maximally preserving time to market strategies for engineering designers. The key research goal is the formalization of this approach. In order to achieve the research objective, foundational research from the domain of fitness landscapes is adapted to relate design complexity to the number of functional design elements and their interconnectedness. This approach utilizes design matrices to enable the generation of fitness-landscapes relevant to design. These resulting design performance landscapes relate the fitness of design concepts to all possible combinations of design parameters and functional requirements within a design approach responsible for its underlying technical complexity. By considering this approach in a dynamic context, the research team is able to incorporate and investigate the role of resiliency in engineering design. Complexity as a source for risk and uncertainty in design decision-making is examined. As part of this investigation optimal resiliency factors under various degrees of complexity are identified. The research recognizes design as an on-going activity between the designer, artefact, and user (DAU), which is treated as a complex adaptive socio-technical eco-system. The mechanisms that can best incentivize and improve the ability of this DAU eco-system are examined as a multidisciplinary and diverse collaboration that adapts its search strategies and, in so doing, improves system resiliency.
Broader Impacts: In the short term, the proposed research establishes a framework for representing and analyzing beneficial patterns of design-team decision-making behaviors given the inherent preference differences of design participants and users. The framework offers a foundation for continued research into the broader area of collaborative team dynamics and performance measurement as applied to engineering design. Additionally, the techniques and methods described and established as part of this research have broad applicability across a range of production systems, to include various collaborations of design (e.g. resiliency of health-systems, resiliency of power systems, etc.). Wherever possible these recommendations will be tied back to the terminology and schedule constructs associated with large-scale government engineering projects, such as those in the National Aeronautics and Space Administration (NASA) and the Department of Defense (DOD), to make their future implementations more accessible for design practitioners. The results of this research will be incorporated into the existing systems engineering courses. Additionally, the researchers will supervise undergraduate industrial and systems engineering student capstone projects where students will be introduced to the nuances of engineering design, team dynamics and performance measurement. The intent would be to recruit undergraduate students especially minorities and under-represented groups to pursue graduate engineering education.
Menu