Is MLOps different in Industry 4.0? General and Specific Challenges

Leonhard Faubel, Klaus Schmid, Holger Eichelberger
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引用次数: 3

Abstract

: An important part of the Industry 4.0 vision is the use of machine learning (ML) techniques to create novel capabilities and flexibility in industrial production processes. Currently, there is a strong emphasis on MLOps as an enabling collection of practices, techniques, and tools to integrate ML into industrial practice. However, while MLOps is often discussed in the context of pure software systems, Industry 4.0 systems received much less attention. So far, there is no specialized research for Industry 4.0 in this regard. In this position paper, we discuss whether MLOps in Industry 4.0 leads to significantly different challenges compared to typical Internet systems. We identify both context-independent MLOps challenges (general challenges) as well as challenges particular to Industry 4.0 (specific challenges) and conclude that MLOps works very similarly in Industry 4.0 systems to pure software systems. This indicates that existing tools and approaches are also mostly suited for the Industry 4.0 context.
工业4.0的mlop不同吗?一般挑战和特殊挑战
工业4.0愿景的一个重要组成部分是使用机器学习(ML)技术在工业生产过程中创造新的能力和灵活性。目前,人们非常重视mlop,将其作为实践、技术和工具的支持集合,将ML集成到工业实践中。然而,虽然mlop经常在纯软件系统的背景下讨论,但工业4.0系统却很少受到关注。到目前为止,还没有针对工业4.0在这方面的专门研究。在这篇意见书中,我们讨论了工业4.0中的mlop与典型的互联网系统相比是否会带来明显不同的挑战。我们确定了与上下文无关的MLOps挑战(一般挑战)以及工业4.0特有的挑战(特定挑战),并得出结论,MLOps在工业4.0系统中的工作方式与纯软件系统非常相似。这表明现有的工具和方法也大多适合工业4.0环境。
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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