Digital Twin for Energy Optimization in an SMT-PCB Assembly Line

Neha V. Karanjkar, Ashish Joglekar, Sampad B. Mohanty, Venkatesh Prabhu, D. Raghunath, R. Sundaresan
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引用次数: 38

Abstract

This paper presents a case study for the use of an IoT-driven digital twin for energy optimization in an automated Surface Mount Technology (SMT) PCB assembly line containing legacy machines. The line was instrumented with multiple sensors for measuring machine-wise activity and energy consumption. A software platform for data aggregation and a discrete-event digital twin of the line were built entirely using open-source tools. Based on the insights gained from data collected over several days, we propose a buffering-based solution for improving the energy efficiency of the line, and evaluate its impact using simulations of the digital twin. The results show that a 2.7x reduction in the energy consumption is possible via buffer insertion without significantly affecting line throughput.
SMT-PCB装配线能量优化的数字孪生
本文介绍了在包含传统机器的自动化表面贴装技术(SMT) PCB装配线中使用物联网驱动的数字孪生体进行能源优化的案例研究。该生产线配备了多个传感器,用于测量机器活动和能耗。数据聚合的软件平台和生产线的离散事件数字孪生完全使用开源工具构建。基于从几天收集的数据中获得的见解,我们提出了一种基于缓冲的解决方案,以提高生产线的能源效率,并使用数字孪生模拟来评估其影响。结果表明,在不显著影响线路吞吐量的情况下,通过缓冲区插入可以减少2.7倍的能耗。
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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