大数据驱动的离散制造车间生产过程智能管控方法研究

在智能制造背景下,离散制造企业对利用大数据技术提高车间生产管控水平提出了迫切的需求.研究大数据驱动的离散制造车间生产过程智能管控方法,在明确离散制造车间特点与管控需求的基础上,分析了传统方法的局限性和大数据方法的优势,进而提出大数据驱动的离散制造车间生产过程管控总体框架,以制造大数据的采集-处理-分析-服务为主线开...

Big Data Driven Intelligent Production Control of Discrete Manufacturing Process

Under intelligent manufacturing era, there is pressing demands from discrete manufacturing enterprise to utilize big data (BD) technologies for enhancing the level of production management and control (PM&C). The BD driven intelligent PM&C in discrete manufacturing process is studied. Based on the determination of characteristics and demands for PM&C, the architecture of BD driven PM&C is firstly constructed, which the main flow is collection-processing-analysis-service of manufacturing BD. Based on the closed-loop mechanism progress prediction-bottleneck discovery-anomaly tracing-decision making for PM&C, the key technologies are respectively proposed, which are:A stacked sparse auto-encoder model for production progress prediction, The parallel gated recurrent units model for shifting bottleneck discovery, The density peak-weighted fuzzy C-means method for anomaly tracing and The multi-agents reinforcement learning for production decision-making. Finally, an aircraft discrete manufacturing workshop is selected as the application scenario to verify the developed prototype system.