Big Data as an enabler to prevent failures in the production area

V. Stich, Kerem Oflazgil, M. Schroter, Felix Jordan, G. Fuhs
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引用次数: 1

Abstract

Failure management in the production area has been intensely analyzed in the research community. Although several efficient methods have been developed and partially successfully implemented, producing companies still face a lot of challenges. The resulting main question is how manufacturers can be assisted by a sustainable approach enabling them to proactively detect and prevent failures before they occur. A high-resolution production system based on analyzed real-time data enables manufacturers to find an answer to the main question. In this context, Big Data technologies have gained importance since the critical success factor is not only to collect real-time data in the production but also to structure the data. Therefore, we present in this paper the implementation of Big Data technologies in the production area using the example of an actual research project. After the literature review, we describe a Big Data based approach to prevent failures in the production area. This approach mainly includes a real-time capable platform including complex event processing algorithms to define appropriate improvement measures.
大数据是防止生产区域故障的推动者
生产领域的故障管理已成为研究领域的热点。尽管已经开发了几种有效的方法,并取得了部分成功,但生产公司仍然面临着许多挑战。由此产生的主要问题是,制造商如何通过可持续的方法来帮助他们主动检测和预防故障发生。基于实时数据分析的高分辨率生产系统使制造商能够找到主要问题的答案。在这种情况下,大数据技术变得越来越重要,因为成功的关键因素不仅是在生产中收集实时数据,还包括数据的结构。因此,本文以实际研究项目为例,介绍大数据技术在生产领域的应用。在文献综述之后,我们描述了一种基于大数据的方法来防止生产区域的故障。该方法主要包括一个具有实时能力的平台,其中包括复杂事件处理算法,以定义适当的改进措施。
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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