Collaborative Research: Randomized Distributed Data Structures for Product Design

这个合作项目的目标是使产品回收和再利用在经济上和环境上可行。这对工程设计很重要，因为尽管组件重用和再制造可能会降低成本、减少环境影响并提高客户满意度，但计算问题将设计分析限制在单一的静态、行业平均模型输入集上。现实世界的实现需要来自各种广泛分布的数据源的动态输入。要完成的任务包括：开发一个利用来自广泛分布的来源的数据的关于部件回收、再利用、再制造或处置的决策系统；对具有概率行为的共享对象进行严格规范；开发高效和容错的分布式算法来实现共享对象；开发一个设计系统，通过在整个产品生命周期中利用来自多个来源的反馈来提高客户满意度。广泛的影响包括回收目前浪费在报废产品中的经济价值，降低消费者成本和环境影响。此外，我们的计算基础设施的可扩展性也将得到扩大。这个项目将被整合到一个由工业赞助的高级设计课程中，因此对学生和行业的技术转移将是广泛和及时的。将通过为两个不同系(普通工程和计算机科学)的本科生和研究生课程编写新的跨学科课程材料来加强教育基础设施。代表不足的群体将受益于PI对这项研究的陈述，众所周知，这项研究的社会相关性激励女性和少数族裔学生攻读工程学。

The objective of this collaborative project is to make product take-back and reuse economically and environmentally viable. It is important for engineering design because although component reuse and remanufacture can potentially decrease cost, decrease environmental impact, and increase customer satisfaction, computational issues have limited design analysis to a single set of static, industry-average model inputs. Real world implementation requires dynamic input from a variety of widely distributed data sources. Tasks to be completed include: development of a system for making decisions regarding component recycle, reuse, remanufacturing or disposal that utilizes data from widely distributed sources; rigorous specification of shared objects that have probabilistic behavior; development of efficient and fault-tolerant distributed algorithms to implement the shared objects; development of a design system that increases customer satisfaction by utilizing feedback from multiple sources throughout the product lifecycle.Broader impacts include recovering the economic value that is currently wasted in discarded products, decreasing both consumer costs and environmental impacts. Also, the scalability of our computing infrastructure will be expanded. This project will be integrated into an industrially sponsored senior design course, so technology transfer to students and industry will be broad and timely. The educational infrastructure will be enhanced by development of new interdisciplinary course materials for both undergraduate and graduate courses in two different departments (General Engineering and Computer Science). Underrepresented groups will benefit by the PI's presentations of this research, whose social relevance is known to motivate women and minority students to pursue engineering studies.