单晶SiC衬底生产线在停机干扰下的管理策略

Xisheng Zhu, Dan Zhang, Wenhao Ai, Weidong Fu, D. Zuo
{"title":"单晶SiC衬底生产线在停机干扰下的管理策略","authors":"Xisheng Zhu, Dan Zhang, Wenhao Ai, Weidong Fu, D. Zuo","doi":"10.1109/ICARCE55724.2022.10046626","DOIUrl":null,"url":null,"abstract":"In order to reduce the system performance loss and restore the normal operation for the downtime disturbance event on the monocrystalline SiC substrate production line, a prediction model of the performance of the SiC wafer substrate production line is established based on the G/G/m/b queuing model. A production line simulation model is built in the Witness simulation software to verify the feasibility of the prediction model. A production line performance optimization model under downtime disturbance with the buffer capacity and processing preparation time as optimization parameters is established combining with the concept of time window. And the management strategy is obtained by the optimization solution of the model using genetic algorithm. The feasibility of the proposed method is verified based on the improved coupled map lattices production network propagation model. The results of the simulation validation in Witness software show that the proposed method improves the production performance of the production line under equipment downtime.","PeriodicalId":416305,"journal":{"name":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Management Strategies for Monocrystalline SiC Substrate Production Lines under Downtime Disturbances\",\"authors\":\"Xisheng Zhu, Dan Zhang, Wenhao Ai, Weidong Fu, D. Zuo\",\"doi\":\"10.1109/ICARCE55724.2022.10046626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to reduce the system performance loss and restore the normal operation for the downtime disturbance event on the monocrystalline SiC substrate production line, a prediction model of the performance of the SiC wafer substrate production line is established based on the G/G/m/b queuing model. A production line simulation model is built in the Witness simulation software to verify the feasibility of the prediction model. A production line performance optimization model under downtime disturbance with the buffer capacity and processing preparation time as optimization parameters is established combining with the concept of time window. And the management strategy is obtained by the optimization solution of the model using genetic algorithm. The feasibility of the proposed method is verified based on the improved coupled map lattices production network propagation model. The results of the simulation validation in Witness software show that the proposed method improves the production performance of the production line under equipment downtime.\",\"PeriodicalId\":416305,\"journal\":{\"name\":\"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARCE55724.2022.10046626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCE55724.2022.10046626","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

为了减少单晶SiC衬底生产线发生停机扰动事件时系统的性能损失,恢复正常运行,建立了基于G/G/m/b排队模型的SiC衬底生产线性能预测模型。在Witness仿真软件中建立了生产线仿真模型,验证了预测模型的可行性。结合时间窗的概念,以缓冲容量和加工准备时间为优化参数,建立了停机扰动下生产线性能优化模型。利用遗传算法对模型进行优化求解,得到管理策略。基于改进的耦合映射格生成网络传播模型,验证了所提方法的可行性。在Witness软件中的仿真验证结果表明,该方法提高了生产线在设备停机情况下的生产性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Management Strategies for Monocrystalline SiC Substrate Production Lines under Downtime Disturbances
In order to reduce the system performance loss and restore the normal operation for the downtime disturbance event on the monocrystalline SiC substrate production line, a prediction model of the performance of the SiC wafer substrate production line is established based on the G/G/m/b queuing model. A production line simulation model is built in the Witness simulation software to verify the feasibility of the prediction model. A production line performance optimization model under downtime disturbance with the buffer capacity and processing preparation time as optimization parameters is established combining with the concept of time window. And the management strategy is obtained by the optimization solution of the model using genetic algorithm. The feasibility of the proposed method is verified based on the improved coupled map lattices production network propagation model. The results of the simulation validation in Witness software show that the proposed method improves the production performance of the production line under equipment downtime.
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