工业4.0集成支持预测平台

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2020-12-14 DOI:10.14201/adcaij2020947182
Sergio Márquez Sánchez
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引用次数: 0

摘要

目前,工业领域的公司正致力于整合工业4.0模型中的先进技术,以继续在日益高科技的市场中竞争。除了生产力之外,这些进步对工人的工作环境和为保持健康工作空间而采取的措施产生了显著影响。因此,例如,有项目开发用于维护和工业培训的增强现实技术,用于增材制造的先进建模工具,或用于工业数据的大数据分析平台。然而,设计的解决方案过于针对特定的行业问题,或者提出的平台过于通用,不容易适应行业。这项工作旨在为互联行业提供一个参考软件架构,为流程优化、预测性维护和实时可视化提供新的能力,整合现有系统生成的所有相关信息,整合来自数字社会的新数据源,并确保未来与新信息源的兼容性。解决方案和可能实施的工业物联网(IIoT)设备。
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Integral Support Predictive Platform for Industry 4.0
Currently, companies in the industrial sector are focusing their efforts on incorporating the advances contained in the Industry 4.0 model, to continue competing in an increasingly high-tech market. These advances, in addition to productivity, have a remarkable impact on the working environment of workers and on the measures adopted to maintain a healthy workspace. Thus, for example, there are projects to develop augmented reality technologies for maintenance and industrial training, advanced modelling tools for additive manufacturing, or Big Data analysis platforms for industrial data. However, the solutions designed are too specific to a particular industry problem or the platforms proposed are too generalist and not easily adaptable to the industries. This work seeks to provide a reference software architecture at the service of the connected industry that allows the provision of new capacities for process optimisation, predictive maintenance and real-time visualisation, integrating all the relevant information generated by the existing systems, incorporating new sources of data resulting from the digital society, and ensuring future compatibility with the new sources of information, solutions and Industrial Internet of Things (IIoT) devices that may be implemented.
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
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