A novel production execution logic model with directed service node pairs and encapsulated service cells for efficient scheduling and simulation in discrete manufacturing shops

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Robotics and Computer-integrated Manufacturing Pub Date : 2025-03-19 DOI:10.1016/j.rcim.2025.103017
Mingyuan Liu, Jiaxiang Xie, Jian Zhang, Shengfeng Qin, Guofu Ding, Haojie Chen
{"title":"A novel production execution logic model with directed service node pairs and encapsulated service cells for efficient scheduling and simulation in discrete manufacturing shops","authors":"Mingyuan Liu, Jiaxiang Xie, Jian Zhang, Shengfeng Qin, Guofu Ding, Haojie Chen","doi":"10.1016/j.rcim.2025.103017","DOIUrl":null,"url":null,"abstract":"In discrete manufacturing shops, dynamic uncertainty disturbances necessitate frequent scheduling and simulation, posing significant challenges to the efficiency of traditional methods. Therefore, effective production execution logic models are required to manage these dynamics and enhance the efficiency of scheduling and simulation. However, existing production execution logic models lack comprehensive integration of flows of information, control, and material (FICM), making it difficult to effectively describe the dynamic production execution logic and limiting their ability to optimize scheduling and simulation processes. To address this challenge, by extending the seven-elements (SE) and material node-oriented seven-elements (MNOSE) models, this paper proposes a production execution logic model with directed service node pairs and encapsulated service cells (PELM-DaE). The model achieves the representation and integration of FICM, enabling an effective description of dynamic production execution logic. Based on PELM-DaE, a method for constructing connectivity maps is proposed, which allows the characterization of job execution relationships and constraints and the pre-computation of FICM. Additionally, by dynamically constructing and continuously applying connectivity maps, a connectivity map-based framework is proposed to support efficient scheduling and simulation. Based on the above research content, a software platform is developed to implement the encapsulation of the proposed model and method. The practicality and advantages of the model and method in describing the production execution logic and improving the efficiency of scheduling simulation are verified based on an actual manufacturing shop floor.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"33 1","pages":""},"PeriodicalIF":9.1000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.rcim.2025.103017","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

In discrete manufacturing shops, dynamic uncertainty disturbances necessitate frequent scheduling and simulation, posing significant challenges to the efficiency of traditional methods. Therefore, effective production execution logic models are required to manage these dynamics and enhance the efficiency of scheduling and simulation. However, existing production execution logic models lack comprehensive integration of flows of information, control, and material (FICM), making it difficult to effectively describe the dynamic production execution logic and limiting their ability to optimize scheduling and simulation processes. To address this challenge, by extending the seven-elements (SE) and material node-oriented seven-elements (MNOSE) models, this paper proposes a production execution logic model with directed service node pairs and encapsulated service cells (PELM-DaE). The model achieves the representation and integration of FICM, enabling an effective description of dynamic production execution logic. Based on PELM-DaE, a method for constructing connectivity maps is proposed, which allows the characterization of job execution relationships and constraints and the pre-computation of FICM. Additionally, by dynamically constructing and continuously applying connectivity maps, a connectivity map-based framework is proposed to support efficient scheduling and simulation. Based on the above research content, a software platform is developed to implement the encapsulation of the proposed model and method. The practicality and advantages of the model and method in describing the production execution logic and improving the efficiency of scheduling simulation are verified based on an actual manufacturing shop floor.
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
求助全文
约1分钟内获得全文 去求助
来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
期刊最新文献
A novel production execution logic model with directed service node pairs and encapsulated service cells for efficient scheduling and simulation in discrete manufacturing shops Study on dynamics modelling and stiffness strengthening method for mobile industrial robot in-situ milling machining Semi-active damping for industrial robots Demand-driven hierarchical integrated planning-scheduling control for a mobile robot-operated flexible smart manufacturing system Real-time defect detection and classification in robotic assembly lines: A machine learning framework
×
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