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

这项探索性研究小额资助(SGER)/与工业界学术联络资助机会（GOALI）项目的目的是探索工业界和学术界如何合作，以调查将灵活性原则应用于协作设计过程的组织和执行的理论和实践可行性。产品开发面临的最重要的挑战之一是需要跨规程、组织和层次尺度分布设计活动，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，在这种方法中，协作设计人员交换近似模型，然后是包含耦合参数之间可实现权衡的一系列鲁棒解决方案的家族或帕累托集。灵活性体现在健壮的解决方案家族中，协作的设计师可以从中选择合适的解决方案，并在一组健壮的范围内对其进行调整，以保持系统可行性和平衡系统级目标。该方法为协作设计提供了计算支持，减少了设计人员之间的迭代，这是增加设计空间覆盖的直接结果，相对于与大多数over- wall， MDO（多学科优化）相关的单点解决方案，以及与健壮设计方法相关的分层优化方法和间隔。它可以潜在地避免大量集中的系统级优化，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制定设计问题和仿真模型，并验证和解释解决方案。此外，多种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，这对工业具有重要的实际效益。所提出的方法是高风险的，因为考虑到潜在的障碍，例如工业对快速收敛到单点解决方案的偏好以及相对于更传统的方法的总体人力和计算资源需求，需要建立其对非琐碎的工业强度问题的可行性。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的。从理论的角度来看，我们需要回答这些研究问题，并调查该方法优于其他方法的条件，例如传统的，过度的设计过程或高度集中的或cdo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.