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Cloud-based manufacturing process monitoring for smart diagnosis services

机译:智能诊断服务的基于云制造过程监控

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摘要

A cloud-based manufacturing process monitoring framework for online smart diagnosis services has been developed with the aim of performing tool condition monitoring during machining of difficult-to-machine materials. The proposed architecture allows to share process monitoring tasks between different resources, which can be geographically dislocated and managed by actors with different competences and functions. Distributed resources with enhanced computation and data storage capability allow to improve the efficiency of tool condition diagnosis and enable more robust decision-making, exploiting large information and knowledge sharing. Diagnosis on tool conditions is offered as a cloud service, using an architecture where the computing resources in the cloud are connected to the physical manufacturing system realising a complex cyber-physical system using sensor and network communication. Based on sensorial data acquired at the factory level, smart online diagnosis on consumed tool life and tool breakage occurrence is carried out through knowledge-based algorithms and cognitive pattern recognition paradigms. On the basis of the cloud diagnosis, the local server activates the proper corrective action to be taken, such as tool replacement, process halting or parameters change, sending the right command to the machine tool control.
机译:在线智能诊断服务的基于云制造过程监测框架,目的是在加工难以加工的材料时进行工具状态监测。该建议的架构允许在不同资源之间共享流程监视任务,该任务可以由具有不同竞争力和功能的演员地理位置脱臼和管理。具有增强的计算和数据存储功能的分布式资源允许提高工具状况诊断的效率,并实现更强大的决策,利用大型信息和知识共享。使用云端的诊断作为云服务提供,其中云中的计算资源连接到使用传感器和网络通信实现复杂网络物理系统的物理制造系统。基于在工厂级别获取的感觉数据,通过基于知识的算法和认知模式识别范例进行了智能在线诊断消耗的工具寿命和刀具破损发生。在云诊断的基础上,本地服务器激活要拍摄的正确纠正措施,如工具替换,过程停止或参数更改,向机床控制发送右命令。

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