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

这个探索性研究（SGER）/学术界与工业界联系（GOALI）项目的小额赠款的目的是探索工业界和学术界如何合作，调查将灵活性原则应用于组织和执行协作设计过程的理论和实践可行性。产品开发面临的最大挑战之一是需要跨学科，组织和层次规模分布设计活动，同时管理依赖关系和耦合，以实现令人满意的系统级解决方案。为了促进分布式协作，提出了一种基于灵活性的方法，在该方法中，合作设计师交换近似模型，然后由家庭或帕累托集的强大的解决方案，体现了一系列可实现的耦合参数之间的权衡。灵活性体现在家庭的强大的解决方案，合作设计者可以选择一个适当的解决方案，并调整它在一组强大的界限，以保持系统的可行性和平衡系统级的目标。该方法提供了计算支持协同设计与减少设计师之间的迭代，作为直接结果的设计空间的覆盖率增加，相对于单点解决方案与大多数过墙，MDO（多学科优化），分层优化方法和区间与强大的设计方法。它可以潜在地避免广泛的集中式系统级优化，这些优化需要自动分析并产生系统级瓶颈和计算困难。相反，子系统设计人员始终处于循环中，利用他们的专业知识来制定设计问题和仿真模型，并验证和解释解决方案。此外，多个解决方案的生成增加了未来类似问题的设计重用的可能性，这对工业来说是一个重要的实际好处。所提出的方法是高风险的，因为它的可行性，非平凡的，工业强度的问题需要建立，在潜在的障碍，如工业偏见，快速收敛到单点解决方案和整体人力和计算资源的需求相对于更传统的方法。我们计划与我们的工业合作伙伴进行初步试验，以确定任何额外的障碍和相应的研究问题，旨在调查这些障碍是真实的还是仅仅是感知到的。从理论的角度来看，我们需要回答这些研究问题，并调查的条件下，该方法是上级的其他方法，如传统的，过墙的设计过程或高度集中或多学科设计方法风格的设计过程。

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.