Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime

IF 1.6 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Yuanshyi Peter Chiu, Yunsen Wang, Tsu-Ming Yeh, S. Chiu
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引用次数: 0

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.
包含概率故障、报废和超时的混合系统的制造运行时决策
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。
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来源期刊
CiteScore
5.70
自引率
9.10%
发文量
35
审稿时长
20 weeks
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