工业应用的无人机:从实施的角度确定挑战和机遇

Dimitris Mourtzis , John Angelopoulos , Nikos Panopoulos
{"title":"工业应用的无人机:从实施的角度确定挑战和机遇","authors":"Dimitris Mourtzis ,&nbsp;John Angelopoulos ,&nbsp;Nikos Panopoulos","doi":"10.1016/j.promfg.2021.10.026","DOIUrl":null,"url":null,"abstract":"<div><p>New technologies such as Unmanned Aerial Vehicles (UAV) are constantly being introduced under the Industry 4.0 framework. Although UAVs are mainly used in civil and military applications, the opportunities for Industrial integration must be examined, namely real-time remote monitoring, wireless coverage, and remote sensing. Therefore, UAVs can be considered as proactive solvers, simultaneously contributing to enhanced decision making as they are considered to be Internet of Things (IoT) platforms for efficient cost-effective data collection and monitoring. However, the use of UAVs in confined and crowded Industrial environments, e.g. machine shops, need further research. Therefore, this paper focuses on highlighting the limitations regarding the integration of UAVs in modern manufacturing systems as well as on presenting an intelligent framework based on Industrial Internet of Things (IIoT) for real-time machine shop monitoring. The applicability of the developed framework is tested in-vitro, in a laboratory-based machine shop.</p></div>","PeriodicalId":91947,"journal":{"name":"Procedia manufacturing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2351978921002237/pdf?md5=1ce20000b6cb31853f340fd1a554ace2&pid=1-s2.0-S2351978921002237-main.pdf","citationCount":"16","resultStr":"{\"title\":\"UAVs for Industrial Applications: Identifying Challenges and Opportunities from the Implementation Point of View\",\"authors\":\"Dimitris Mourtzis ,&nbsp;John Angelopoulos ,&nbsp;Nikos Panopoulos\",\"doi\":\"10.1016/j.promfg.2021.10.026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>New technologies such as Unmanned Aerial Vehicles (UAV) are constantly being introduced under the Industry 4.0 framework. Although UAVs are mainly used in civil and military applications, the opportunities for Industrial integration must be examined, namely real-time remote monitoring, wireless coverage, and remote sensing. Therefore, UAVs can be considered as proactive solvers, simultaneously contributing to enhanced decision making as they are considered to be Internet of Things (IoT) platforms for efficient cost-effective data collection and monitoring. However, the use of UAVs in confined and crowded Industrial environments, e.g. machine shops, need further research. Therefore, this paper focuses on highlighting the limitations regarding the integration of UAVs in modern manufacturing systems as well as on presenting an intelligent framework based on Industrial Internet of Things (IIoT) for real-time machine shop monitoring. The applicability of the developed framework is tested in-vitro, in a laboratory-based machine shop.</p></div>\",\"PeriodicalId\":91947,\"journal\":{\"name\":\"Procedia manufacturing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2351978921002237/pdf?md5=1ce20000b6cb31853f340fd1a554ace2&pid=1-s2.0-S2351978921002237-main.pdf\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Procedia manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2351978921002237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2351978921002237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

摘要

在工业4.0框架下,无人机(UAV)等新技术不断被引入。尽管无人机主要用于民用和军事应用,但必须审查工业集成的机会,即实时远程监控,无线覆盖和遥感。因此,无人机可以被视为主动解决方案,同时有助于增强决策,因为它们被认为是物联网(IoT)平台,可实现高效、经济的数据收集和监控。然而,在密闭和拥挤的工业环境中使用无人机,如机械车间,需要进一步研究。因此,本文着重强调了在现代制造系统中集成无人机的局限性,并提出了一个基于工业物联网(IIoT)的智能框架,用于实时监控机器车间。开发的框架的适用性在体外进行了测试,在实验室为基础的机械车间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UAVs for Industrial Applications: Identifying Challenges and Opportunities from the Implementation Point of View

New technologies such as Unmanned Aerial Vehicles (UAV) are constantly being introduced under the Industry 4.0 framework. Although UAVs are mainly used in civil and military applications, the opportunities for Industrial integration must be examined, namely real-time remote monitoring, wireless coverage, and remote sensing. Therefore, UAVs can be considered as proactive solvers, simultaneously contributing to enhanced decision making as they are considered to be Internet of Things (IoT) platforms for efficient cost-effective data collection and monitoring. However, the use of UAVs in confined and crowded Industrial environments, e.g. machine shops, need further research. Therefore, this paper focuses on highlighting the limitations regarding the integration of UAVs in modern manufacturing systems as well as on presenting an intelligent framework based on Industrial Internet of Things (IIoT) for real-time machine shop monitoring. The applicability of the developed framework is tested in-vitro, in a laboratory-based machine shop.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信