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基于数字孪生技术的钛合金管件智能制造与质量管控的数字线程
Digital Thread of Intelligent Manufacturing and Quality Management of Titanium Pipes within Digital Twins
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- DOI:
- 作者:
- 柴再先1王毅1,2张嘉3孙峰3杨超3张志远4刘希林4李强5王军1寇宏超1,2李金山1,2
CHAI Zaixian 1 , WANG William Yi 1,2 , ZHANG Jia 3 , SUN Feng 4 , YANG Chao 3 , ZHANG Zhiyuan 5 , LIU Xilin 5 , LI Qiang 4 , WANG Jun 1 , KOU Hongchao 1,2 , LI Jinshan 1,2
- 作者单位:
- 1. 西北工业大学凝固技术国家重点实验室2. 西北工业大学重庆科创中心3. 西部超导材料科技股份有限公司4. 中国船舶集团有限公司第七二五研究所5. 重庆两航金属材料有限责任公司
1. State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi'an 710072, China; 2. Innovation Center NPU Chongqing, Chongqing 401135, China; 3. Western Superconducting Technologies Co., Ltd., Xi'an 710018, China; 4. Ti-MAST High Performance Alloy Co., Ltd., Chongqing 401135, China ; 5. Luoyang Ship Material Research Institute, Luoyang 471000, China
- 关键词:
- 数字孪生;钛合金管;模板化模型设计;数据自动采集;组织优化;
digital twin; titanium pipe; template model design; automatic data collection; microstructure optimization
- 摘要:
- 数字时代驱动下的智能制造技术是国家工业水平的重要体现。在国内外材料基因工程、集成计算材料工程、数字孪生等众多国家战略的促进下数字化技术获得了蓬勃发展,有助于满足材料、工艺、产品、装备等关键部件的全寿命周期质量管控的迫切需求,并将加速传统制造业向数字化、网络化和智能化的转型升级。本文基于数字孪生全流程和全寿命周期大数据的数字线程,介绍了钛合金管件智能制造与质量管控的典型铸造和挤压工艺及其材料组织性能控制的关键技术,旨在开发有效提升材料及其产品智能开发设计和智能制造的关键技术。其中,铸造过程样品和样件的智造技术主要包括凝壳炉设备的数据感知和可视化运行监测,以及铸造样品的铸造性能和标准试样高通量制备。通过对钛合金管件进行模板化、标准化、流程化的智能设计,并对工艺模拟仿真技术以及制造过程中工艺数据的自动化采集,提出了样件加工生产中热处理工艺组织调控的算法模型。这些关键技术的应用将有利于原材料性能的快速测试,提高钛合金管件制造过程和质量管控的效能,节省时间和成本,以期为智能制造技术的发展提供重要技术支撑。
In the digital era, integrated intelligent manufacturing plays a significant role in reflecting the level of national
manufacturing. Motivated by numerous national strategies, including Material Genome Engineering, Integrated
Computational Materials Engineering, digital twins and so on, digital technologies have been developed vigorously to fit the
urgent requirements of lifetime quality management of materials, processes, products, equipment together with their
corresponding components/parts. Digital technologies have been accelerated and developed by the manufacturing industry
through a digital-networked-intelligent transformation routine. In line with the digital thread of the whole processing/supply
chain and the lifetime management in digital twins, this work presents several dominant intelligent manufacturing technologies for classical casting and extrusion processes to improve the microstructure and property optimizations, quality
management, smart design, and development of advanced titanium pipes. With respect to intelligent manufacturing
technologies of pipe parts, the data collection, visualization of the utilized shell furnace equipment, castability of the casting
samples and high-throughput standard mechanical specimens are utilized. Moreover, based on our designed templates,
standards, and processing strategies in the smart design/development of titanium pipes, simulation technologies, data
collection in manufacturing, an algorithm together with its model optimizing the microstructures in heat treatments is
proposed. It is understood that the aforementioned intelligent technologies will not only enable the rapid and cost-effective
fabrication and validation of the properties/performances of raw materials but also improve the efficiency of the titanium
pipe manufacturing process and quality control, paving a firm path for the further development of intelligent manufacturing
technologies.