基于供应链管理和RSM的基于敏捷制造战略的生产系统物联网因素建模与优化

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES
U. K. Vates, B. Sharma, Nand Jee Kanu, E. Gupta, G. Singh
{"title":"基于供应链管理和RSM的基于敏捷制造战略的生产系统物联网因素建模与优化","authors":"U. K. Vates, B. Sharma, Nand Jee Kanu, E. Gupta, G. Singh","doi":"10.1080/23080477.2021.2017543","DOIUrl":null,"url":null,"abstract":"ABSTRACT Agile Manufacturing is a widely accepted strategy by most organizations as a tool to compete in the market. The success of an industrial product or organization depends on their ability to short out the critical and regular factors of agile manufacturing. Identification of suitable implementation of critical enablers could highlight industrial issues to enhance the process performance. The present research aimed to depict the critical enablers of agile manufacturing through the enablers of Internet of things (IoT) to improve the profitability and product quality. The methodologies adopted for the depiction of enablers in the research are similarity coefficient matrix (SCM) and Jaccard’s Similarity Index (JSI). The impact of organizational level, technological level, and employee-level enablers on IoT clusters were investigated analytically through SCM and JSI. JSI is applied to acquire data by survey and then a dendrogram is generated on the basis of the calculations done through this index. Response surface methodology (RSM) was also adopted to optimize the critical IoT enablers and it is validated with an analytical result. GRAPHICAL ABSTRACT","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"10 1","pages":"158 - 173"},"PeriodicalIF":2.4000,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Modeling and Optimization of IoT Factors to Enhance Agile Manufacturing Strategy-based Production System Using SCM and RSM\",\"authors\":\"U. K. Vates, B. Sharma, Nand Jee Kanu, E. Gupta, G. Singh\",\"doi\":\"10.1080/23080477.2021.2017543\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Agile Manufacturing is a widely accepted strategy by most organizations as a tool to compete in the market. The success of an industrial product or organization depends on their ability to short out the critical and regular factors of agile manufacturing. Identification of suitable implementation of critical enablers could highlight industrial issues to enhance the process performance. The present research aimed to depict the critical enablers of agile manufacturing through the enablers of Internet of things (IoT) to improve the profitability and product quality. The methodologies adopted for the depiction of enablers in the research are similarity coefficient matrix (SCM) and Jaccard’s Similarity Index (JSI). The impact of organizational level, technological level, and employee-level enablers on IoT clusters were investigated analytically through SCM and JSI. JSI is applied to acquire data by survey and then a dendrogram is generated on the basis of the calculations done through this index. Response surface methodology (RSM) was also adopted to optimize the critical IoT enablers and it is validated with an analytical result. GRAPHICAL ABSTRACT\",\"PeriodicalId\":53436,\"journal\":{\"name\":\"Smart Science\",\"volume\":\"10 1\",\"pages\":\"158 - 173\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2021-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Smart Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23080477.2021.2017543\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2021.2017543","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 6

摘要

敏捷制造是一种被大多数组织广泛接受的战略,是一种市场竞争的工具。一个工业产品或组织的成功取决于他们缩短敏捷制造的关键和常规因素的能力。识别关键促成因素的适当实现可以突出工业问题,以提高过程性能。本研究旨在通过物联网(IoT)来描述敏捷制造的关键使能因素,以提高盈利能力和产品质量。本研究采用相似系数矩阵(SCM)和Jaccard相似指数(JSI)两种方法来描述促成因素。通过SCM和JSI分析了组织层面、技术层面和员工层面的推动者对物联网集群的影响。采用JSI法对数据进行调查获取,并根据该指标的计算结果生成树形图。还采用响应面法(RSM)来优化关键的物联网使能因素,并通过分析结果对其进行验证。图形抽象
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Optimization of IoT Factors to Enhance Agile Manufacturing Strategy-based Production System Using SCM and RSM
ABSTRACT Agile Manufacturing is a widely accepted strategy by most organizations as a tool to compete in the market. The success of an industrial product or organization depends on their ability to short out the critical and regular factors of agile manufacturing. Identification of suitable implementation of critical enablers could highlight industrial issues to enhance the process performance. The present research aimed to depict the critical enablers of agile manufacturing through the enablers of Internet of things (IoT) to improve the profitability and product quality. The methodologies adopted for the depiction of enablers in the research are similarity coefficient matrix (SCM) and Jaccard’s Similarity Index (JSI). The impact of organizational level, technological level, and employee-level enablers on IoT clusters were investigated analytically through SCM and JSI. JSI is applied to acquire data by survey and then a dendrogram is generated on the basis of the calculations done through this index. Response surface methodology (RSM) was also adopted to optimize the critical IoT enablers and it is validated with an analytical result. GRAPHICAL ABSTRACT
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
Smart Science
Smart Science Engineering-Engineering (all)
CiteScore
4.70
自引率
4.30%
发文量
21
期刊介绍: Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials
×
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