关于流程挖掘在工业 4.0 中应用的系统性文献综述

IF 2.5 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Katsiaryna Akhramovich, Estefanía Serral, Carlos Cetina
{"title":"关于流程挖掘在工业 4.0 中应用的系统性文献综述","authors":"Katsiaryna Akhramovich, Estefanía Serral, Carlos Cetina","doi":"10.1007/s10115-023-02042-x","DOIUrl":null,"url":null,"abstract":"<p>The transition to Industry 4.0 means a new era in manufacturing with a new level of production automation, human-to-machine cooperation and product customization. It provides many benefits and opportunities to both enterprises and consumers and allows for principally new level of cooperation. At the same time, the complexity of business processes, large volume and the complex structure of data generated and processed by different Industry 4.0 technologies create serious challenges for Business Process Management. Process mining (PM) can tackle these challenges. PM is a relatively young discipline that is positioned between process-centric and data-centric approaches and focuses on discovering, conformance checking and enhancement of end-to-end business processes. Moreover, new types of PM deal with performance analysis, comparative analysis of several processes, making predictions and triggering improvement actions. This systematic literature review studies the applicability of PM in Industry 4.0 and the benefits that PM can provide to each of the four aspects of Industry 4.0: smart factories, smart products, new business models and new customer services. Approaches of PM proposed in the selected studies are analysed and classified according to two dimensions of the study: PM and Industry 4.0. The research gaps identified while performing the systematic literature review show possible directions for further research in the area.</p>","PeriodicalId":54749,"journal":{"name":"Knowledge and Information Systems","volume":"25 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A systematic literature review on the application of process mining to Industry 4.0\",\"authors\":\"Katsiaryna Akhramovich, Estefanía Serral, Carlos Cetina\",\"doi\":\"10.1007/s10115-023-02042-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The transition to Industry 4.0 means a new era in manufacturing with a new level of production automation, human-to-machine cooperation and product customization. It provides many benefits and opportunities to both enterprises and consumers and allows for principally new level of cooperation. At the same time, the complexity of business processes, large volume and the complex structure of data generated and processed by different Industry 4.0 technologies create serious challenges for Business Process Management. Process mining (PM) can tackle these challenges. PM is a relatively young discipline that is positioned between process-centric and data-centric approaches and focuses on discovering, conformance checking and enhancement of end-to-end business processes. Moreover, new types of PM deal with performance analysis, comparative analysis of several processes, making predictions and triggering improvement actions. This systematic literature review studies the applicability of PM in Industry 4.0 and the benefits that PM can provide to each of the four aspects of Industry 4.0: smart factories, smart products, new business models and new customer services. Approaches of PM proposed in the selected studies are analysed and classified according to two dimensions of the study: PM and Industry 4.0. The research gaps identified while performing the systematic literature review show possible directions for further research in the area.</p>\",\"PeriodicalId\":54749,\"journal\":{\"name\":\"Knowledge and Information Systems\",\"volume\":\"25 1\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Knowledge and Information Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s10115-023-02042-x\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge and Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10115-023-02042-x","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

向工业 4.0 过渡意味着制造业进入一个新时代,生产自动化、人机合作和产品定制将达到一个新水平。工业 4.0 为企业和消费者带来了许多好处和机遇,使合作达到了新的高度。与此同时,不同工业 4.0 技术产生和处理的业务流程复杂、数据量大、结构复杂,给业务流程管理带来了严峻挑战。流程挖掘(PM)可以应对这些挑战。流程挖掘是一门相对年轻的学科,它介于以流程为中心和以数据为中心的方法之间,侧重于端到端业务流程的发现、一致性检查和增强。此外,新型 PM 还涉及性能分析、多个流程的比较分析、预测和触发改进行动。本系统性文献综述研究了 PM 在工业 4.0 中的适用性,以及 PM 可为工业 4.0 的四个方面(智能工厂、智能产品、新商业模式和新客户服务)带来的益处。对所选研究中提出的 PM 方法进行了分析,并根据研究的两个维度进行了分类:PM 和工业 4.0。在进行系统性文献综述时发现的研究空白为该领域的进一步研究指明了可能的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A systematic literature review on the application of process mining to Industry 4.0

A systematic literature review on the application of process mining to Industry 4.0

The transition to Industry 4.0 means a new era in manufacturing with a new level of production automation, human-to-machine cooperation and product customization. It provides many benefits and opportunities to both enterprises and consumers and allows for principally new level of cooperation. At the same time, the complexity of business processes, large volume and the complex structure of data generated and processed by different Industry 4.0 technologies create serious challenges for Business Process Management. Process mining (PM) can tackle these challenges. PM is a relatively young discipline that is positioned between process-centric and data-centric approaches and focuses on discovering, conformance checking and enhancement of end-to-end business processes. Moreover, new types of PM deal with performance analysis, comparative analysis of several processes, making predictions and triggering improvement actions. This systematic literature review studies the applicability of PM in Industry 4.0 and the benefits that PM can provide to each of the four aspects of Industry 4.0: smart factories, smart products, new business models and new customer services. Approaches of PM proposed in the selected studies are analysed and classified according to two dimensions of the study: PM and Industry 4.0. The research gaps identified while performing the systematic literature review show possible directions for further research in the area.

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
Knowledge and Information Systems
Knowledge and Information Systems 工程技术-计算机:人工智能
CiteScore
5.70
自引率
7.40%
发文量
152
审稿时长
7.2 months
期刊介绍: Knowledge and Information Systems (KAIS) provides an international forum for researchers and professionals to share their knowledge and report new advances on all topics related to knowledge systems and advanced information systems. This monthly peer-reviewed archival journal publishes state-of-the-art research reports on emerging topics in KAIS, reviews of important techniques in related areas, and application papers of interest to a general readership.
×
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