徐颖, 李莉. 制造业大数据的发展与展望[J]. 信息与控制, 2018, 47(4): 421-427. DOI: 10.13976/j.cnki.xk.2018.7593
引用本文: 徐颖, 李莉. 制造业大数据的发展与展望[J]. 信息与控制, 2018, 47(4): 421-427. DOI: 10.13976/j.cnki.xk.2018.7593
XU Ying, LI Li. Development and Prospect of Manufacturing Big Data[J]. INFORMATION AND CONTROL, 2018, 47(4): 421-427. DOI: 10.13976/j.cnki.xk.2018.7593
Citation: XU Ying, LI Li. Development and Prospect of Manufacturing Big Data[J]. INFORMATION AND CONTROL, 2018, 47(4): 421-427. DOI: 10.13976/j.cnki.xk.2018.7593

制造业大数据的发展与展望

Development and Prospect of Manufacturing Big Data

  • 摘要: 随着大数据时代的到来,大数据对制造业的影响越来越明显.把握大数据时代带来的机遇,正确合理地进行传统制造业的转型升级尤为重要.本文首先归纳总结了制造业大数据的含义,突出制造业大数据是贯穿制造业整个价值链的、可通过大数据分析等技术实现智能制造快速发展的海量数据;其次,举例说明了制造业大数据发展和应用的三个阶段;然后从价值链出发,具体分析了大数据对研发与设计、供应、生产、营销和售后服务五方面的影响,体现了价值链由生产驱动向需求驱动的转变趋势;最后从大数据存储、大数据分析技术和数据安全与隐私三个角度分析了制造业大数据面临的挑战,并提出对中国传统制造业转型升级的展望.

     

    Abstract: With the advent of the big data age, the influence of big data on manufacturing has become increasingly obvious. It is very important to use the advantage to reasonably transform and upgrade traditional manufacturing. We summarize the definitions of big data in manufacturing. It emphasizes that manufacturing big data comprising volumes of data through the whole value chain can be used to improve intelligent manufacturing, using big data analysis and other technologies. We illustrate three processes in the development and applications of manufacturing big data with examples. Afterwards, we analyze the effects on value chain from five aspects in detail:research and design, supply, production, marketing, and post-sales service, which reflects the transformation trend from production-driven to demand-driven. Finally, we analyze the challenges faced by manufacturing big data from three perspectives:big data storage, big data analysis technologies, and big data safety and privacy, and propose the prospects for Chinese traditional manufacturing.

     

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