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Agent-Based Data Analysis Towards the Dynamic Adaptation of Industrial Automation Processes

机译:基于Agent的数据分析可实现工业自动化过程的动态适应

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Industrial complex systems demand the dynamic adaptation and optimization of their operation to cope with operational and business changes. In order to address such requirements and challenges, cyber-physical systems promotes the development of intelligent production units and products. The realization of such concepts requires, amongst others, advanced data analysis approaches, capable to take advantage of increased availability of data, in order to overcome the inherent dynamics of industrial environments, by providing more modular, adaptable and responsiveness systems. In this context, this work introduces an agent-based data analysis approach to support the supervisory and control levels of industrial processes. It proposes to endow agents with data analysis capabilities and cooperation strategies, enabling them to perform distributed data analysis and dynamically improve their analysis capabilities, based on the aggregation of shared knowledge. Some experiments have been performed in the context of an electric micro grid to validate this approach.
机译:工业复杂系统要求动态调整和优化其操作以应对操作和业务变化。为了解决这些要求和挑战,网络物理系统促进了智能生产单元和产品的开发。这些概念的实现尤其需要先进的数据分析方法,这些方法能够利用数据的可用性提高,以通过提供更多的模块化,适应性强和响应性的系统来克服工业环境的固有动态。在这种情况下,这项工作引入了一种基于代理的数据分析方法,以支持工业过程的监控水平。它建议赋予代理以数据分析能力和合作策略,使他们能够基于共享知识的聚集来执行分布式数据分析并动态地提高其分析能力。已经在微电网的背景下进行了一些实验以验证这种方法。

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