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

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。对于机器不可靠和内部缓冲区有限的制造系统，需要有效的短期实时控制策略来满足各种系统性能要求，如吞吐量、可靠性、质量和成本效益。本研究将开发一个基于新型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的实时短期生产维修控制系统，而不需要使用仿真模型。拟议的系统将调查生产不确定性的缓解，以减少计划外停机时间，并通过检测瓶颈来有效利用生产系统中产能关键部分的有限工厂资源。这种联合维护和生产决策优化的目标是为任何给定的生产操作实现接近平衡的生产线状态。如果成功，本研究的结果将建立一个科学的知识库，并为创建最优维护策略提供机会，这些策略可以用于有效地提高复杂制造系统和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。其结果将被传播，让工业从业者应用这些方法来提高生产效率，降低成本，提高竞争力。工程专业的研究生和本科生将从课堂教学和参与研究中受益。参与这项研究的学生将从这个项目中预期的跨学科研究环境中受益匪浅，在这个环境中，机械、工业和电气工程科学将相互交织。

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.