开发数字对应物以辅助主动制造过程能耗决策支持

Liam Morris, M. Ahern, D. O’Sullivan, K. Bruton
{"title":"开发数字对应物以辅助主动制造过程能耗决策支持","authors":"Liam Morris, M. Ahern, D. O’Sullivan, K. Bruton","doi":"10.3390/environsciproc2021011003","DOIUrl":null,"url":null,"abstract":"This research focused on the development of a Digital Model (DM) of a production line at a medical device company, with the objective of providing decision support to stakeholders based on their energy consumption. This model aims to reduce energy consumption by bringing operational data to process engineers, allowing them to make efficient improvement decisions while in production. In order to achieve this objective, the twin transition of digital integration and energy efficiency was enacted by organisations such as the International Energy Agency (IEA). This two-pronged approach involved working with process owners to understand the decision-making process that they undertook to streamline performance and develop the means to digitalise this data while also working with facilities and maintenance engineers to understand which equipment played the most important roles in the production process from an energy consumption perspective. By bringing the process data and energy data together in a digital model of the process, a decision support system could be developed which would unlock the potential to streamline operations not just from an output perspective, but also from an energy efficient perspective. When examining the process step with data catagorised as energy, operational and maintenance, it was found that only operational data was sufficient to support digital modelling in its current state. Therefore, the installation of a wireless energy metering network would be required to support digital modelling and further digital integration.","PeriodicalId":11904,"journal":{"name":"Environmental Sciences Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a Digital Counterpart to Aid Decision Support on Energy Consumption of an Active Manufacturing Process\",\"authors\":\"Liam Morris, M. Ahern, D. O’Sullivan, K. Bruton\",\"doi\":\"10.3390/environsciproc2021011003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research focused on the development of a Digital Model (DM) of a production line at a medical device company, with the objective of providing decision support to stakeholders based on their energy consumption. This model aims to reduce energy consumption by bringing operational data to process engineers, allowing them to make efficient improvement decisions while in production. In order to achieve this objective, the twin transition of digital integration and energy efficiency was enacted by organisations such as the International Energy Agency (IEA). This two-pronged approach involved working with process owners to understand the decision-making process that they undertook to streamline performance and develop the means to digitalise this data while also working with facilities and maintenance engineers to understand which equipment played the most important roles in the production process from an energy consumption perspective. By bringing the process data and energy data together in a digital model of the process, a decision support system could be developed which would unlock the potential to streamline operations not just from an output perspective, but also from an energy efficient perspective. When examining the process step with data catagorised as energy, operational and maintenance, it was found that only operational data was sufficient to support digital modelling in its current state. Therefore, the installation of a wireless energy metering network would be required to support digital modelling and further digital integration.\",\"PeriodicalId\":11904,\"journal\":{\"name\":\"Environmental Sciences Proceedings\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Sciences Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/environsciproc2021011003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Sciences Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/environsciproc2021011003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究的重点是医疗器械公司生产线的数字模型(DM)的开发,目的是根据其能源消耗为利益相关者提供决策支持。该模型旨在通过向流程工程师提供操作数据来降低能耗,从而使他们能够在生产过程中做出有效的改进决策。为了实现这一目标,国际能源署(IEA)等组织制定了数字集成和能源效率的双重转型。这种双管齐下的方法包括与流程所有者合作,了解他们所承担的简化性能的决策过程,并开发数字化数据的手段,同时与设施和维护工程师合作,从能耗的角度了解哪些设备在生产过程中发挥了最重要的作用。通过将过程数据和能源数据整合到过程的数字模型中,可以开发一个决策支持系统,该系统不仅可以从输出角度出发,还可以从节能角度出发,释放简化操作的潜力。当使用分类为能源、操作和维护的数据检查过程步骤时,发现只有操作数据足以支持当前状态下的数字建模。因此,需要安装无线能源计量网络来支持数字建模和进一步的数字集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Development of a Digital Counterpart to Aid Decision Support on Energy Consumption of an Active Manufacturing Process
This research focused on the development of a Digital Model (DM) of a production line at a medical device company, with the objective of providing decision support to stakeholders based on their energy consumption. This model aims to reduce energy consumption by bringing operational data to process engineers, allowing them to make efficient improvement decisions while in production. In order to achieve this objective, the twin transition of digital integration and energy efficiency was enacted by organisations such as the International Energy Agency (IEA). This two-pronged approach involved working with process owners to understand the decision-making process that they undertook to streamline performance and develop the means to digitalise this data while also working with facilities and maintenance engineers to understand which equipment played the most important roles in the production process from an energy consumption perspective. By bringing the process data and energy data together in a digital model of the process, a decision support system could be developed which would unlock the potential to streamline operations not just from an output perspective, but also from an energy efficient perspective. When examining the process step with data catagorised as energy, operational and maintenance, it was found that only operational data was sufficient to support digital modelling in its current state. Therefore, the installation of a wireless energy metering network would be required to support digital modelling and further digital integration.
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
期刊最新文献
Measuring Virtual Reality (VR) Technology Application and Adoption in Chinese Construction Risk Management Spatial Provocateur—Questioning the Status Quo From the Urbanism of Metabolism to Sydney/Tokyo Waterfronts Regeneration (2019–2022) Analysis of Nano Silica Aerogel Based Glazing Effect on the Solar Heat Gain and Cooling Load in a School under Different Climatic Conditions Investigating the Participation Facets of Environmental Citizen Science Initiatives: A Systematic Literature Review of Empirical Research
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1