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Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations

机译:迈向制造业的数据驱动方法:收集操作序列的架构

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The technological advancements of recent years have increased the complexity of manufacturing systems, and the ongoing transformation to Industry 4.0 will further aggravate the situation. This is leading to a point where existing systems on the factory floor get outdated, increasing the gap between existing technologies and state-of-the-art systems, making them incompatible. This paper presents an event-based data pipeline architecture, that can be applied to legacy systems as well as new state-of-the-art systems, to collect data from the factory floor. In the presented architecture, actions executed by the resources are converted to event streams, which are then transformed into an abstraction called operations. These operations correspond to the tasks performed in the manufacturing station. A sequence of these operations recount the task performed by the station. We demonstrate the usability of the collected data by using conformance analysis to detect when the manufacturing system has deviated from its defined model. The described architecture is developed in Sequence Planner - a tool for modelling and analysing production systems - and is currently implemented at an automotive company as a pilot project.
机译:近年来的技术进步提高了制造系统的复杂性,对行业4.0的持续转型将进一步加剧这种情况。这导致工厂地板上现有系统过时的点,提高现有技术与最先进系统之间的差距,使其不兼容。本文提出了一种基于事件的数据流水线架构,可应用于传统系统以及新的最先进系统,从工厂地板中收集数据。在呈现的体系结构中,由资源执行的操作将转换为事件流,然后将其转换为称为操作的抽象。这些操作对应于制造站中执行的任务。这些操作的序列叙述了站执行的任务。我们通过使用一致性分析来展示收集数据的可用性来检测制造系统何时偏离其定义的模型。所描述的架构是在序列规划器中开发的 - 一种用于建模和分析生产系统的工具 - 目前在汽车公司作为试点项目实施。

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