包含概率故障、报废和超时的混合系统的制造运行时决策

IF 1.6 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL International Journal of Industrial Engineering Computations Pub Date : 2022-01-01 DOI:10.5267/j.ijiec.2022.4.001
Yuanshyi Peter Chiu, Yunsen Wang, Tsu-Ming Yeh, S. Chiu
{"title":"包含概率故障、报废和超时的混合系统的制造运行时决策","authors":"Yuanshyi Peter Chiu, Yunsen Wang, Tsu-Ming Yeh, S. Chiu","doi":"10.5267/j.ijiec.2022.4.001","DOIUrl":null,"url":null,"abstract":"Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem.","PeriodicalId":51356,"journal":{"name":"International Journal of Industrial Engineering Computations","volume":"100 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime\",\"authors\":\"Yuanshyi Peter Chiu, Yunsen Wang, Tsu-Ming Yeh, S. Chiu\",\"doi\":\"10.5267/j.ijiec.2022.4.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem.\",\"PeriodicalId\":51356,\"journal\":{\"name\":\"International Journal of Industrial Engineering Computations\",\"volume\":\"100 1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Industrial Engineering Computations\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.5267/j.ijiec.2022.4.001\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Industrial Engineering Computations","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5267/j.ijiec.2022.4.001","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

摘要

今天的制造商需要通过满足外部客户较短的订单到期日期和管理内部可能不可靠的机器和制造流程来优化其制造运行时决策。外包和加班是加快制造时间的常用策略。此外,对不可避免的产品缺陷(如去除废料)和设备故障(如机器维修)进行详细分析和必要的措施是制造运行时计划的先决条件。为了帮助当今的制造商在上述情况下决定最佳的批量运行计划,本研究将数学模型应用于包含部分加班和外包、不可避免的产品缺陷和泊松分布故障的混合制造问题。我们开发了一个模型来准确地表示问题的特征。公式和详细的模型分析使我们能够首先找到成本函数。微分方程和算法帮助我们确定增益函数的凸性,并找到最佳的运行时决策。最后,通过对研究问题的关键管理信息的深入揭示,用数值例证来说明我们研究的适用性。
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
Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime
Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem.
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
CiteScore
5.70
自引率
9.10%
发文量
35
审稿时长
20 weeks
期刊最新文献
A unifying framework and a mathematical model for the Slab Stack Shuffling Problem Heuristics and metaheuristics to minimize makespan for flowshop with peak power consumption constraints Minimizing operating expenditures for a manufacturing system featuring quality reassurances, probabilistic failures, overtime, and outsourcing Composite heuristics and water wave optimality algorithms for tri-criteria multiple job classes and customer order scheduling on a single machine Investigating the collective impact of postponement, scrap, and external suppliers on multiproduct replenishing decision
×
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