| 摘要: |
| 航天飞行器制造工艺路线复杂，涉及的设备数量庞大且类型多样，分析设备定检、维修、故障等各类事件对设备生产能力的影响并进行自适应调度，能够有效保障生产效率。本文提出一种基于数字孪生的设备能力评估与动态调度方法，构建“本体建模-数据采集-事件监测-能力评估-动态调度”完整闭环下的航天制造车间智能管控新模式。首先基于本体构建设备孪生模型和能力评估模型；其次，采用大数据技术对实时数据进行处理，驱动孪生模型实现不同动态事件触发下的设备状态分析和能力评估；最后，设计改进的优化算法以实现生产调度实时响应。并通过开发某航天研究所结构件制造车间智能调度系统，对所提方法进行应用示范，为离散制造车间的生产管控提供有效技术途径。 |
| 关键词: 设备能力评估 数字孪生 动态调度 工业大数据 |
| 基金项目: |
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| Digital Twin-based Equipment Capacity Evaluation and Dynamic Scheduling for Spacecraft Manufacturing Shop |
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Hong Haibo1, Chen Jinhua1, Zuo Liling2, Yang Chen1, Lv Youlong2
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1. Shanghai Aerospace Precision Research Institute, Shanghai, 201600;2. Donghua University, Shanghai, 201620
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| Abstract: |
| The manufacturing process route of spacecraft is complex and involves a large number of equipment with various types. The impact analysis of equipment relevant events such as checking, repairs and failures on equipment capacity and related adaptive scheduling is important to keep the production efficiency. This paper proposes a Digital twin-based equipment capability evaluation and dynamic scheduling method, to realize the intelligent control mode for spacecraft manufacturing shop with main steps of ontology modeling, data collection, event monitoring, capability evaluation, and dynamic scheduling. First, the digital twin model and the capability evaluation model are constructed based on the ontology for the equipment. Second, driven by big-data-enabled real-time data processing, the digital twin model realizes status analysis and capability evaluation of the equipment for different events. Finally, an improved optimization algorithm is used to achieve real-time production scheduling based on updated equipment capacities. The proposed method is applied to the production scheduling system of the structural parts manufacturing shop of an aerospace research institute, which provides an effective tool for production control of discrete manufacturing shops. |
| Key words: equipment capability assessment digital twin dynamic scheduling industrial big data |
