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International Journal of Production Research最新文献

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Optimal designs of the omnibus SPRT control chart for joint monitoring of process mean and dispersion 过程均值与离散度联合监控的综合SPRT控制图优化设计
2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-11 DOI: 10.1080/00207543.2023.2254855
Jing Wei Teoh, Wei Lin Teoh, Michael B.C. Khoo, Giovanni Celano, Zhi Lin Chong
The vast majority of control schemes related to the sequential probability ratio test (SPRT) are designed for the purpose of monitoring only the process mean. Nonetheless, most manufacturing processes are vulnerable to external factors that cause the process mean and variability to change simultaneously. It is, therefore, crucial to consider a joint scheme for monitoring both the location and scale parameters of a production process. In this article, we develop a scheme that combines both mean and variance information in a single SPRT, known as the omnibus SPRT (OSPRT) chart. Expressions for the run-length properties of the OSPRT chart are derived by means of the Markov chain approach. We also propose optimal designs for the OSPRT chart based on two different metrics, i.e. by minimising the average time to signal and the average extra quadratic loss. Through a comprehensive analysis, this article reveals that the optimal OSPRT chart outperforms the classical X¯-S, weighted-loss cumulative sum, absolute-value SPRT, and two maximum weighted-moving-average-type charts. The optimal OSPRT chart also has the advantage of collecting a small number of samples on average before producing a decision. Finally, the implementation of the OSPRT chart is presented with a wire bonding industrial dataset.
绝大多数与序列概率比检验(SPRT)相关的控制方案都是为了监测过程均值而设计的。尽管如此,大多数制造过程容易受到导致过程平均值和可变性同时变化的外部因素的影响。因此,至关重要的是要考虑一项联合计划,以监测生产过程的地点和规模参数。在本文中,我们开发了一种方案,将均值和方差信息结合在单个SPRT中,称为综合SPRT (OSPRT)图。利用马尔可夫链方法导出了OSPRT图的游程性质表达式。我们还提出了基于两个不同指标的OSPRT图的优化设计,即最小化平均信号时间和平均额外二次损失。通过综合分析,本文发现最优的OSPRT图优于经典的X¯-S图、加权损失累计和图、绝对值SPRT图和两个最大加权移动平均图。最优的OSPRT图还具有在产生决策之前平均收集少量样本的优点。最后,利用一个线接工业数据集给出了OSPRT图的实现。
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引用次数: 0
Analysis of factors influencing Circular-Lean-Six Sigma 4.0 implementation considering sustainability implications: an exploratory study 考虑可持续性影响的循环精益-六西格玛4.0实施因素分析:一项探索性研究
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2251159
D. Skalli, A. Charkaoui, A. Cherrafi, Alireza Shokri, J. Garza‐Reyes, Jiju Antony
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,
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引用次数: 0
An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing 一种改进的基于深度强化学习的云制造动态任务调度方法
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2253326
Xiaohan Wang, Lin Zhang, Yongkui Liu, Y. Laili
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引用次数: 0
A data-driven viable supply network for energy security and economic prosperity 一个数据驱动的可行的能源安全和经济繁荣供应网络
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2254414
Kwon Gi Mun, Wenbo Cai, Mark Rodgers, Sungyong Choi
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引用次数: 0
A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling 基于机器学习的生产过程建模的连续跨产品知识积累、提取和转移框架
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2254854
Jiarui Xie, Chonghui Zhang, Manuel Sage, Mutahar Safdar, Y. Zhao
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引用次数: 1
A new integrated strategy for optimising the maintenance cost of complex systems using reliability importance measures 一种利用可靠性重要性测度优化复杂系统维护成本的综合策略
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2254406
M. Rebaiaia, D. Ait-kadi
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引用次数: 0
Distributed appointment assignment and scheduling under uncertainty 不确定条件下的分布式预约分配与调度
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2252937
Li Xue, Yantong Li, Zheng Wang, Sai-Ho Chung, Xin Wen
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引用次数: 0
Investigating make-or-buy decisions and the impact of learning-by-doing in the semiconductor industry 调查生产或购买决策以及在半导体行业中边做边学的影响
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2250009
Dóra Longauer, Tamás Vasvári, Zsuzsanna Hauck
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引用次数: 0
Multiobjective analytical evolutionary algorithm for train stowage planning problem of steel industry 钢铁工业列车配载规划问题的多目标分析进化算法
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2254405
Yun Dong, Xiangling Zhao
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引用次数: 0
A novel collaborative iterative greedy algorithm for hybrid flowshop scheduling problem with batch processing machines and variable sublots 一种新的协同迭代贪婪算法求解具有批处理机和可变子批次的混合流程调度问题
IF 9.2 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Pub Date : 2023-09-07 DOI: 10.1080/00207543.2023.2253925
Chengshuai Li, Yu-yan Han, Biao Zhang, Yuting Wang, Jun-Qiang Li, Kaizhou Gao
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引用次数: 0
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International Journal of Production Research
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