SGER/GOALI: A Flexibility-Based Approach for Collaborative Design

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The objective of this Small Grant for Exploratory Research (SGER)/Grant Opportunity for Academic Liaison with Industry (GOALI) project is to explore how industry and academia can collaborate to investigate the theoretical and practical feasibility of applying flexibility principles to the organization and execution of collaborative design processes. One of the foremost challenges facing product development is the need to distribute design activities across disciplines, organizations, and hierarchical scales while simultaneously managing dependencies and couplings to achieve satisfactory system-level solutions. To facilitate distributed collaboration, a flexibility-based approach is proposed in which collaborating designers exchange approximate models followed by families or Pareto sets of robust solutions that embody a spectrum of achievable tradeoffs between coupled parameters. Flexibility is embodied in the families of robust solutions from which collaborating designers may select an appropriate solution and adjust it within a set of robust bounds for maintaining system feasibility and balancing system-level objectives. The approach offers computational support for collaborative design with reduced iteration between designers, as a direct result of increased coverage of the design space, relative to single point solutions associated with most over-the-wall, MDO (multidisciplinary optimization), and hierarchical optimization methods and intervals associated with robust design approaches. It can potentially avoid extensive centralized, systems-level optimization that requires automated analysis and creates systems-level bottlenecks and computational intractability. Instead, subsystem designers are consistently in the loop, utilizing their expertise to formulate design problems and simulation models and to validate and interpret solutions. Furthermore, the generation of multiple solutions increases the likelihood of design reuse for similar problems in the future'an important practical benefit for industry. The proposed approach is high risk because its viability for non-trivial, industrial strength problems needs to be established, in light of potential barriers such as an industrial bias for rapid convergence to single point solutions and the overall human and computing resource demands relative to more conventional approaches. We plan to conduct preliminary trials with our industrial partner to identify any additional barriers and corresponding research questions aimed at investigating whether those barriers are real or simply perceived. From a theoretical perspective, we need to answer those research questions and investigate the conditions under which the method is superior to other approaches, such as conventional, over-the-wall design processes or highly centralized or MDO-style design processes.