Real time production performance evaluation plays a vital role in diagnosing manufacturing system health status and achieving productivity improvements. However, most existing studies on system performance evaluation are based on steady state analysis and focused on the production system with fixed cycle time machines. The real-time performance evaluation for a manufacturing system with variable cycle time machines, although typical for a large number of realistic scenarios, has been mostly ignored. The development of smart manufacturing and increasingly available sensor data have provided unprecedented opportunities to carry out thorough analysis on the real-time performance of such complex systems. In this letter, we developed a data-enabled methodology to efficiently identify and predict the real-time permanent production loss for a serial production line with variable cycle time machines. The concept and evaluation method of opportunity window are introduced to facilitate the permanent production loss estimation. Numerical case studies are presented to demonstrate the effectiveness of the proposed methods for opportunity window evaluation and production loss identification.

中文翻译：

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对具有可变周期时间机器的批量生产系统进行数据支持的永久生产损失分析


实时生产绩效评估在诊断制造系统健康状况和实现生产率提高方面发挥着至关重要的作用。然而，现有的系统性能评估研究大多基于稳态分析，并集中于具有固定循环时间机器的生产系统。具有可变周期时间机器的制造系统的实时性能评估虽然对于大量现实场景来说是典型的，但大多被忽视。智能制造的发展和日益可用的传感器数据为对此类复杂系统的实时性能进行彻底分析提供了前所未有的机会。在这封信中，我们开发了一种基于数据的方法，可以有效地识别和预测具有可变周期时间机器的串行生产线的实时永久生产损失。引入机会窗的概念和评估方法，以方便估算永久性生产损失。数值案例研究证明了所提出的机会窗口评估和生产损失识别方法的有效性。