Short-Term Joint Maintenance and Production Decision Support Tool of Manufacturing Systems

制造系统短期联合维护和生产决策支持工具

• 批准号: 0825789
• 负责人: Jun Ni
• 金额: $ 27.87万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0825789&HistoricalAwards=false
• 关键词: Short; Term; Joint; Maintenance; Production

The research objective of this award is to develop scientific methods for modeling and analysis of short-term joint maintenance and production decision support tools for complex manufacturing systems. For manufacturing systems with unreliable machines and finite internal buffers, there is a need for effective short-term real time control policies in order to satisfy various system performance requirements, such as throughput, reliability, quality and cost effectiveness. This research will develop a real-time short-term production and maintenance control system based on novel data-driven instantaneous bottleneck detection methods, maintenance opportunity planning and maintenance task prioritization without using simulation models. The proposed system will investigate the mitigation of production uncertainties to reduce unscheduled downtime and the effective utilization of finite factory resources on the throughput-critical sections of a production system by detecting bottlenecks. This goal for such proposed joint maintenance and production decision optimization is to achieve a nearly balanced line status for any given production operation.If successful, the results of this research will establish a scientific knowledge base and provide an opportunity for creating optimal maintenance policies that can be used to effectively improve the performance of complex manufacturing systems as well as many other mission critical engineering systems. The developed ?smart? joint production and maintenance decision-making can have a significant impact for industrial applications such as automotive production systems.The results will be disseminated to allow industrial practitioners to apply these methods to achieve increased production efficiency, reduced cost, and improved competitiveness. Graduate and undergraduate engineering students will benefit through classroom instruction and involvement in the research. Students involved in this research will greatly benefit from the interdisciplinary research environment anticipated in this project, where mechanical, industrial, and electrical engineering science will be intertwined.

该奖项的研究目标是开发用于复杂制造系统的短期联合维护和生产决策支持工具的建模和分析的科学方法。对于具有不可靠机器和有限内部缓冲的制造系统，需要有效的短期实时控制策略，以满足各种系统性能要求，例如吞吐量，可靠性，质量和成本效益。本研究将在不使用仿真模型的情况下，基于新颖的数据驱动的瞬时瓶颈检测方法、维修机会规划和维修任务优先级，开发一种实时的短期生产和维修控制系统。该系统将通过检测瓶颈，研究生产不确定性的缓解，以减少计划外停机时间，并有效利用生产系统吞吐量关键部分的有限工厂资源。这种提出的联合维护和生产决策优化的目标是在任何给定的生产操作中实现近乎平衡的生产线状态。如果成功，这项研究的结果将建立一个科学知识库，并为创建最佳维护策略提供机会，该策略可用于有效提高复杂制造系统以及许多其他关键任务工程系统的性能。发达的？聪明的？联合生产和维护决策可以对汽车生产系统等工业应用产生重大影响。研究结果将得到传播，使工业从业者能够应用这些方法来提高生产效率、降低成本和提高竞争力。研究生和本科生将受益于课堂教学和参与研究。参与本研究的学生将从本计画所预期的跨学科研究环境中获益匪浅，其中机械、工业和电气工程科学将相互交织。