EAGER: Cybermanufacturing: Design of an Agile and Smart Manufacturing Exchange: Enabling Small Businesses through Standardized Protocols and Distributed Optimization

EAGER：网络制造：敏捷和智能制造交换的设计：通过标准化协议和分布式优化支持小型企业

• 批准号: 1543872
• 负责人: Krishnendu Chakrabarty
• 金额: $ 30万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1543872&HistoricalAwards=false
• 关键词: EAGER; Cybermanufacturing; Design; Agile; Smart

This EArly-concept Grant for Exploratory Research (EAGER) award supports fundamental research on the design of an agile manufacturing exchange system (MES) in which suppliers of raw materials, assemblers, transportation companies, etc., will participate through standardized protocols to fulfill complex manufacturing orders. This design will provide the foundation for a smart software mediation layer (i.e., a "broker") that will enable a MES to be self-learning and adaptive to dynamic/diverse service requests and resource availability, as well as support a large network of service providers and users within a complex information ecosystem. The economic competitiveness of the U.S. dependss on new and innovative methods for intelligent mass customization systems for the manufacturing sector, which will enable the processing of small-sized and diverse orders that demand almost instant fulfillment. The MES will enable this transformation by supporting on-demand integration of resources, graceful recovery from failures, and dynamic adaptation without any disruption in operations. In order to meet these goals, research will be focused on adaptation to emerging system behaviors by dynamically evolving optimization strategies in real-time. Users and providers will be connected in a dynamic manufacturing network that will accommodate multiple product flows, uncertainty in links between providers and themselves, and fault tolerance to provide service despite failed network components. This level of adaptation, seamless efficiency, and uninterrupted service will constitute a significant step forward towards a smart MES. The research goals will be accomplished through the design of a distributed real-time optimization and knowledge discovery framework that will address workflow optimization, resource allocation, and data-driven performance prediction in a dynamic manufacturing network of users, brokers, and providers. The specific research tasks include online admission control policies, dynamic production planning, analysis and prediction of service-level performance for forecasting, distributed methods for dynamic resource allocation under uncertainty, and visual analytics techniques to support human decision makers and situational awareness.

这项早期概念探索性研究资助 (EAGER) 奖项支持敏捷制造交换系统 (MES) 设计的基础研究，其中原材料供应商、装配商、运输公司等将通过标准化协议参与其中，以完成复杂的任务。制造订单。该设计将为智能软件中介层（即“经纪人”）提供基础，该中介层将使 MES 能够自学习并适应动态/多样化的服务请求和资源可用性，并支持大型网络复杂信息生态系统中的服务提供商和用户。美国的经济竞争力取决于制造业智能大规模定制系统的创新方法，这将使处理几乎需要即时履行的小规模和多样化订单成为可能。 MES 将通过支持资源的按需集成、从故障中顺利恢复以及在不中断运营的情况下动态适应来实现这一转变。 为了实现这些目标，研究将集中于通过实时动态发展的优化策略来适应新兴系统行为。用户和提供商将在动态制造网络中连接，该网络将适应多种产品流、提供商与其自身之间链接的不确定性以及即使网络组件出现故障也能提供服务的容错能力。这种水平的适应、无缝效率和不间断服务将构成迈向智能 MES 的重要一步。研究目标将通过设计分布式实时优化和知识发现框架来实现，该框架将解决用户、经纪人和提供商的动态制造网络中的工作流程优化、资源分配和数据驱动的性能预测。具体研究任务包括在线准入控制策略、动态生产计划、用于预测的服务水平性能分析和预测、不确定性下动态资源分配的分布式方法以及支持人类决策者和态势感知的可视化分析技术。