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Smart Society and Artificial Intelligence:Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance

机译:智能社会和人工智能:大数据调度和全球标准方法应用于智能维护

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摘要

The implementation of artificial intelligence(AI)in a smart society,in which the analysis of human habits is mandatory,requires automated data scheduling and analysis using smart applications,a smart infrastructure,smart systems,and a smart network.In this context,which is characterized by a large gap between training and operative processes,a dedicated method is required to manage and extract the massive amount of data and the related information mining.The method presented in this work aims to reduce this gap with near-zero-failure advanced diagnostics(AD)for smart management,which is exploitable in any context of Society 5.0,thus reducing the risk factors at all management levels and ensuring quality and sustainability.We have also developed innovative applications for a humancentered management system to support scheduling in the maintenance of operative processes,for reducing training costs,for improving production yield,and for creating a human–machine cyberspace for smart infrastructure design.The results obtained in 12 international companies demonstrate a possible global standardization of operative processes,leading to the design of a near-zero-failure intelligent system that is able to learn and upgrade itself.Our new method provides guidance for selecting the new generation of intelligent manufacturing and smart systems in order to optimize human–machine interactions,with the related smart maintenance and education.
机译:在一个智能社会中实施人工智能(AI),其中强制性地进行人体习惯的分析,需要使用智能应用,智能基础架构,智能系统和智能网络自动化数据调度和分析。在此上下文中,这其特征在于训练和操作过程之间的巨大差距,需要一种专用的方法来管理和提取大量数据和相关信息挖掘。本工作中呈现的方法旨在减少近零故障的差距智能管理的诊断(广告)在社会中的任何背景下都可以在5.0范围内进行,从而降低了所有管理水平的风险因素,并确保了质量和可持续性。我们还开发了革命性管理系统的创新应用,以支持维护计划用于降低培训成本的操作流程,以提高生产率,以及为智能射井创建人机网络空间结构设计。在12家国际公司中获得的结果展示了可操作流程的全球标准化,导致能够学习和升级自身的近零故障智能系统的设计。我们的新方法提供了选择新的指导一代智能制造和智能系统,以优化人机互动,具有相关的智能维护和教育。

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