亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

[Application scenario design and prospect of generative artificial intelligence (AI) in intelligent manufacturing and supply chain of traditional Chinese medicine].

供应链 制造工程 人工智能 工程类 生成语法 计算机科学 业务 营销
作者
Haoshu Xiong,Bei-Xuan Wang,Jian Hou,Cheng Zhao,Yawen Wang,Shun-Nan Zhang,Kaijing Yan
出处
期刊:PubMed 卷期号:49 (14): 3963-3970 被引量:2
标识
DOI:10.19540/j.cnki.cjcmm.20240402.301
摘要

Intelligent manufacturing technologies, including databases, mathematical modeling, and information systems have played a significant role in process control, production management, and supply chain management in traditional Chinese medicine(TCM) industry. However, their ability to process and utilize unstructured data, such as research and development reports, batch production records, quality inspection records, and supplier documents, is relatively weak. For text, images, language, and other unstructured data, generative artificial intelligence(AI) technology has shown strong potential for development in extracting information, extracting knowledge, semantic retrieval, and content generation. Generative AI is expected to provide a feasible set of tools for the utilization of unstructured data resources in the TCM industry. Based on years of research and industrial application experience in TCM intelligent manufacturing technology, this study reviewed the current situation of intelligent manufacturing in TCM and the utilization of unstructured data, analyzed the application value of generative AI in the TCM manufacturing process and supply chain, summarized four typical application scenarios, including intelligent pharmaceutical knowledge base/knowledge graph, intelligent on-the-job trai-ning, intelligent production quality control, and intelligent supply chain. Furthermore, this study also explained the data collection and processing, business process design, application potential, and value of each scenario based on industry demands. Finally, based on the integration of generative AI and TCM industrial models, the study proposed a preliminary concept of a smart industrial brain for TCM, aiming to provide a reference for the application of AI technology in the field of TCM manufacturing.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
自信的高山完成签到,获得积分10
1秒前
4秒前
风凌完成签到 ,获得积分10
5秒前
科研通AI6应助小新XIAO采纳,获得10
6秒前
7秒前
qny完成签到 ,获得积分10
14秒前
tongluobing完成签到,获得积分10
17秒前
负责幻雪完成签到,获得积分20
21秒前
李爱国应助tigerli采纳,获得10
24秒前
15503116087完成签到 ,获得积分10
26秒前
32秒前
李爱国应助刘海清采纳,获得10
35秒前
Owen应助动听的莫茗采纳,获得10
35秒前
喜悦的小土豆完成签到 ,获得积分10
42秒前
ala完成签到,获得积分10
49秒前
59秒前
好运来完成签到 ,获得积分10
1分钟前
ouyoha完成签到,获得积分10
1分钟前
科研通AI6应助科研小巴采纳,获得10
1分钟前
发发扶完成签到,获得积分10
1分钟前
LY完成签到 ,获得积分10
1分钟前
1分钟前
刘海清完成签到,获得积分10
1分钟前
充电宝应助今夜明珠色采纳,获得10
1分钟前
刘海清发布了新的文献求助10
1分钟前
YvonneL发布了新的文献求助10
1分钟前
傻傻的从梦完成签到 ,获得积分10
1分钟前
科目三应助梅倪采纳,获得30
1分钟前
BowieHuang应助科研通管家采纳,获得10
1分钟前
mmyhn应助科研通管家采纳,获得20
1分钟前
mmyhn应助科研通管家采纳,获得20
1分钟前
BowieHuang发布了新的文献求助3000
1分钟前
1分钟前
2分钟前
欣欣完成签到 ,获得积分10
2分钟前
Tanya完成签到 ,获得积分10
2分钟前
55155255完成签到,获得积分10
2分钟前
北七完成签到,获得积分10
2分钟前
xixiazhiwang完成签到 ,获得积分10
2分钟前
黄芪发布了新的文献求助10
2分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Theoretical modelling of unbonded flexible pipe cross-sections 3000
List of 1,091 Public Pension Profiles by Region 1581
Encyclopedia of Agriculture and Food Systems Third Edition 1500
Minimizing the Effects of Phase Quantization Errors in an Electronically Scanned Array 1000
Specialist Periodical Reports - Organometallic Chemistry Organometallic Chemistry: Volume 46 1000
Current Trends in Drug Discovery, Development and Delivery (CTD4-2022) 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5534135
求助须知:如何正确求助?哪些是违规求助? 4622256
关于积分的说明 14582219
捐赠科研通 4562367
什么是DOI,文献DOI怎么找? 2500167
邀请新用户注册赠送积分活动 1479721
关于科研通互助平台的介绍 1450815