The economic production quantity model with optimal single sampling inspection

IF 1.9 3区 工程技术 Q3 MANAGEMENT
M. Nakhaeinejad
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引用次数: 0

Abstract

This paper derives an inspection policy for an economic production quantity (EPQ) model under the assumption that a process may produce non-conforming (NC) items. In various stages of a production process, a department receiving an order uses a single sampling inspection policy to detect NC items. Under such a policy, a lot is accepted if the number of NC items in the inspected sample is equal to or less than the acceptance number. The proposed model considers both EPQ- and quality-related costs. Moreover, economic production order quantity, sample size, and acceptance number are considered decision variables. A numerical example is presented, and a set of sensitivity analysis are provided to highlight the effectiveness of the proposed model. The results reveal that when the inspection cost is high, the classical EPQ model achieves a lower expected total cost for the production system compared to the EPQ model with the inspection. In contrast, when the NC cost is high, the EPQ model with the inspection policy outperforms the classical EPQ model, which can significantly decrease the expected total cost.
最优单次抽样检验的经济生产数量模型
本文在假设一个过程可能产生不合格(NC)项目的情况下,推导了经济生产量(EPQ)模型的检验策略。在生产过程的各个阶段,接收订单的部门使用单一的抽样检查策略来检测NC项目。在这种政策下,如果检验样品中的NC项目数量等于或小于验收数量,则接受批次。所提出的模型同时考虑了EPQ和质量相关的成本。此外,经济生产订单数量、样本量和接受数量都被视为决策变量。给出了一个数值例子,并进行了一组灵敏度分析,以突出所提出模型的有效性。结果表明,当检查成本较高时,与带检查的EPQ模型相比,经典EPQ模型实现了较低的生产系统预期总成本。相反,当NC成本高时,具有检查策略的EPQ模型优于经典EPQ模型,这可以显著降低预期的总成本。
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
IMA Journal of Management Mathematics
IMA Journal of Management Mathematics OPERATIONS RESEARCH & MANAGEMENT SCIENCE-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.70
自引率
17.60%
发文量
15
审稿时长
>12 weeks
期刊介绍: The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.
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