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An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts Architectural Extensions and Potential Applications

机译:工业物联网制造业的基于人工智能的合作方法:关键概念架构扩展和潜在应用

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摘要

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented.
机译:在行业4.0概念下,制造业的数字化导致更加宽松和更有效的生产。如今,从车间资产和信息技术(IT)系统中收集的数据集用于数据驱动的分析努力,以支持更明智的商业智能决策。然而,这些结果目前仅用于生产过程的隔离和分散的部分。与此同时,目前缺乏制造系统的所有部件中的人工智能(AI)的完全集成。在这种情况下,本手稿的目标是通过促进合作来呈现AI的更全面整合。为此,协作被理解为一种多维概念术语,涵盖了制造环境中的AI采用的所有重要推动者,并在商业智能优化,循环和安全联合方面促进了制造场所的安全联合。为了解决这些挑战,拟议的架构方法在三个技术支柱上建立:(1)在工业4.0的参考架构模型中扩展现有层功能的组件; (2)通过LOOP和联邦通过人的循环和联邦进行合作的新层的定义; (3)AI动力机制的安全问题。此外,还讨论了系统实现方面,并提出了工业环境中的潜在应用以及业务影响。

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