Integrated Process-System Modeling and Performance Analysis for Serial Production Lines
Integrated Process-System Modeling and Performance Analysis for Serial Production Lines
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DOI：
10.1109/lra.2022.3181741
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发表时间：
2022
影响因子：
5.2
通讯作者：
Chen Li;Q. Chang;G. Xiao;J. Arinez
中科院分区：
文献类型：
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作者：
Chen Li;Q. Chang;G. Xiao;J. Arinez
智能制造系统的性能不仅受到组成过程的影响，而且还受到系统级交互作用的影响。然而，在目前的大多数研究中，个体过程建模和系统级性能评估是相互独立的。这会极大地影响生产效率。在本文中，利用现有的传感器数据，开发了一个集成的数据使能模型，以无缝融合两个传统上分离的系统级和过程级模型和分析。提出了一种快速递推计算系统成品率的方法。在综合模型的基础上，定义了永久产量损失的概念，并对其进行了评价。此外，由于随机停机和质量问题而导致的PPL归属也已确定。实例研究表明，综合模型具有较高的保真度，PPL分析可以有效地识别产量损失的根本原因。
The performance of a smart manufacturing system is affected by not only the constituent processes but also their system-level interactions. However, in most current studies, individual process modeling and system-level performance evaluation are independent. This can substantially impact production efficiency. In this paper, utilizing available sensor data, an integrated data-enabled model is developed to seamlessly fuse two conventionally separated system-level and process-level models and analysis. A fast recursive method is developed to evaluate the system yield. The permanent production loss (PPL) concept is defined and evaluated based on the proposed integrated model. Furthermore, PPL attributions due to random downtime and quality issues have been identified. Case studies have shown that the integrated model is of high fidelity, and the PPL analysis can effectively identify the root cause of production yield loss.