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Signal-based Context Comparative Analysis for Identification of Similar Manufacturing Modules

机译：基于信号的上下文比较分析，用于识别类似的制造模块

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摘要

Industry 4.0 connects different machines and their modules to each other. Integrating already existing non-modular machines and establishing the required modularization in such a scenario requires a lot of time-consuming analysis. But Industry 4.0 also allows previously unconnected machines to establish a comparative analysis between each other by comparing monitored results of new and old machines. This analysis allows finding behavior that overlaps between machines and allows to identify parts that can be encapsulated in new or substituted by already known modules. In this paper, we propose a method to identify those overlapping parts by exploiting learned behavior models during runtime and combining production paths with sequence search algorithms by using context information of observable event signals.
机译：行业4.0将不同的机器及其模块彼此连接。集成已经存在的非模块化机器并在这种情况下建立所需的模块化需要大量耗时的分析。但行业4.0还允许先前未连接的机器通过比较新和旧机器的监测结果来建立相互之间的比较分析。该分析允许查找在机器之间重叠的行为，并允许识别可以用已知模块中的新的或代替的可以封装的部分。在本文中，我们提出了一种通过利用在运行时期间利用学习行为模型来识别这些重叠部分的方法，并通过使用可观察事件信号的上下文信息来组合具有序列搜索算法的生产路径。

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