制造业生产过程中多源异构数据处理方法综述

陈世超; 崔春雨; 张华; 马戈; 朱凤华; 商秀芹; 熊刚

doi:10.11959/j.issn.2096-0271.2020044

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制造业生产过程中多源异构数据处理方法综述

研究 | 更新时间：2024-06-03

- 制造业生产过程中多源异构数据处理方法综述
- A survey on multi-source heterogeneous data processing methods in manufacturing process
- 大数据 2020年6卷第5期页码：2020044-1
- 作者机构：
  
  1. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
  2. 澳门科技大学，澳门 999078
  3. 北京航天智造科技发展有限公司，北京 100039
  4. 中国工业互联网研究院，北京 100102
- 作者简介：
  
  [ "陈世超（1987- ），男，澳门科技大学计算机技术及应用专业博士生，中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员，主要研究方向为数据处理、工业物联网、边缘计算" ]
  [ "崔春雨（1998- ），女，就职于中国科学院自动化研究所复杂系统管理与控制国家重点实验室，主要研究方向为数据处理、边缘计算" ]
  [ "张华（1986- ），女，博士，北京航天智造科技发展有限公司平台研发部高级工程师，主要研究方向为现代精密测量、工业物联网和边缘计算" ]
  [ "马戈（1990- ），男，博士，中国工业互联网研究院智能化所工程师，主要研究方向为工业互联网、人工智能、边缘计算等" ]
  [ "朱凤华（1976- ），男，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室高级工程师，主要研究方向为人工交通系统、平行交通管理系统" ]
  [ "商秀芹（1983- ），女，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员，主要研究方向为智能制造的数据驱动建模与优化技术" ]
  [ "熊刚（1969- ），男，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室研究员，主要研究方向为复杂系统平行控制与管理、智能制造、智能交通" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2018YFB1702701);国家自然科学基金资助项目;The National Natural Science Foundation of China(61773381);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1909204);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1811463);国家自然科学基金资助项目;The National Natural Science Foundation of China(61773382);国家自然科学基金资助项目;The National Natural Science Foundation of China(61533019);北京高等学校高水平人才交叉培养实培计划“智能边缘计算技术与设备”项目;Practical Training Plan Project “Intelligent Edge Computing Technology and Device” of High-level Talents Cross-cultivation in Beijing Universities and Colleges;东莞创新领军人才项目（熊刚）;Dongguan’s Innovation Talents Project (XIONG Gang)
- DOI：10.11959/j.issn.2096-0271.2020044
  中图分类号： TP391
- 网络首发：2020-09，
  
  纸质出版：2020-09-15
- 稿件说明：
移动端阅览
陈世超, 崔春雨, 张华, 等. 制造业生产过程中多源异构数据处理方法综述[J]. 大数据, 2020,6(5):2020044-1.

Shichao CHEN, Chunyu CUI, Hua ZHANG, et al. A survey on multi-source heterogeneous data processing methods in manufacturing process[J]. Big Data Research, 2020, 6(5): 2020044-1.
陈世超, 崔春雨, 张华, 等. 制造业生产过程中多源异构数据处理方法综述[J]. 大数据, 2020,6(5):2020044-1. DOI： 10.11959/j.issn.2096-0271.2020044.

Shichao CHEN, Chunyu CUI, Hua ZHANG, et al. A survey on multi-source heterogeneous data processing methods in manufacturing process[J]. Big Data Research, 2020, 6(5): 2020044-1. DOI： 10.11959/j.issn.2096-0271.2020044.

摘要

随着现代制造业向着自动化、信息化、智能化方向快速发展，生产过程中会产生大量的多源异构数据。对多源异构数据的有效处理和深度挖掘可为生产制造者提供更有效的生产调度、设备管理等策略，从而提高生产质量和效率。针对制造业生产过程中多源异构数据的处理方法与技术等进行系统性的综述，首先明确了制造业生产过程多源异构数据内容及分类；其次，阐述了多源异构数据处理中数据采集、数据集成及数据分析各个阶段应用的数据处理方法和技术，并分析了各种方法与技术的优缺点以及应用；最后，对生产过程中多源异构数据处理方法和技术进行总结，指出了现阶段多源异构数据处理方法及技术面临的挑战和发展趋势。

Abstract

The effective processing and deep mining analysis of data can provide manufacturers with more effective production scheduling

equipment management and other strategies to affect production yield and efficiency.The processing methods and technologies of multi-source heterogeneous data in the manufacturing process were systematically reviewed.Firstly

the multi-source heterogeneous data content and classification in the manufacturing process was clarified.Secondly

the data processing methods and techniques applied in various stages of data collection

data integration and data analysis in the multi-source heterogeneous data processing were described.And the advantages and disadvantages of various techniques and their applications were analyzed.Finally

the multi-source heterogeneous data processing methods and techniques in the manufacturing process were summarized.And the challenges and development trends were pointed out.

关键词

Keywords

references

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