一种基于制造大数据的产品工艺自适应设计方法
A Product Process Adaptive Design Method Based on Manufacturing-Related Big Data
随着数字化与智能化生产方式在制造业中的广泛应用，引导企业重视并发挥制造大数据的价值对革新产品工艺设计具有重要意义。本文旨在面向企业数据与业务深度融合的应用需求，提出一种基于制造大数据挖掘的产品工艺自适应设计应用方法，用于解决企业中制造数据利用率不足等问题。以企业制造数据为起点，提出了“数据 + 知识 + 决策”的产品工艺自适应设计模式，总结了该模式的制造数据挖掘与利用流程，涵盖多源异构数据融合、数据清洗与预处理、数据变换与降维、数据挖掘、数据可视化和设计决策6个过程。最后以汽车产品焊接工艺为例，建立焊接工艺参数与焊接缺陷的预测模型，用于改善焊接工艺并提高焊接质量，实现制造大数据驱动的焊接工艺自适应设计。研究表明，制造大数据蕴含丰富的知识与模式，可以指导产品设计决策，支持实现不同制造环境下的产品工艺自适应设计；建议进一步推动大数据与第五代移动通信技术等新兴技术的结合，增加对大数据平台、算法设计平台研发的投入，激发制造大数据与产品工艺设计的更大交融。
As digital and smart production methods being applied widely in manufacturing, enterprises should pay more attention to the values of manufacturing-related big data, which is important to the innovation of product process design. This study aims to propose a product process adaptive design method based on manufacturing-related big data. This method is proposed based on the requirement of enterprises for data–business deep integration and it is used for solving the insufficient utilization of manufacturing-related data among enterprises. To this end, a product process adaptive design model “data + knowledge + decision” is proposed and the data mining and utilization processes are summarized for the model, namely, multi-source heterogeneous data fusion; data cleaning and preprocessing; data conversion and dimensionality reduction; data mining; data visualization; and design decision. Subsequently, the automobile welding process is used as an example. A prediction model of the relationship between welding parameters and welding defects is established, aiming to improve welding quality and realize welding process adaptive design. This research reveals that manufacturing related big data contains rich knowledge and patterns and thus can guide product design decisions and support the product process adaptive design under different manufacturing environments. In the future, to enhance the integration of manufacturing-related big data with product process design, the integration of big data with 5G technology should be promoted and investment should be increased inthe development of big data and algorithm design platforms.
产品工艺 / 自适应设计 / 制造大数据 / 数据挖掘 / 知识发现
产品工艺 / 自适应设计 / 制造大数据 / 数据挖掘 / 知识发现 / product process / adaptive design / manufacturing-related big data / data mining / knowledge discovery
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国家重点研发计划资助项目(2018YFB1701703)；国家自然科学基金资助项目(51675028)；中国工程院咨询项目“‘互联网+’行动计划战略研究（2035）”(2018-ZD-02)()
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