An Information Processing Framework Facilitating the Implementation of Condition Monitoring in Cyber-Physical Systems

Abstract

Implementing condition monitoring functionality in production machinery often proves to be a difficult task. Device-and process-specific algorithms must be created while inhomogeneous industrial communication networks hinder the integration of control signals and process variables. Further challenges arise from the advance of flexible Cyber-Physical Systems (CPS) and the Industrial Internet of Things (IIoT). They demand a service-oriented condition monitoring architecture, which seamlessly adapts to quickly changing production topologies. Existing condition monitoring systems (CMS) and reference architectures for CMS however do not possess the capabilities to meet the requirements originating from CPS and the IIoT. This paper presents a software module serving as a generic framework to ease the implementation of decentralized condition monitoring functionalities. A decentralized component, the monitoring module, constitutes a part of a holistic condition monitoring architecture managed by a central server deployed on an edge or cloud server. Therefore, the monitoring module offers an interface through which its data processing flow and algorithms are entirely remotely configurable during operation. Algorithms are encapsulated in function blocks, which can easily be setup and interconnected. Scalability is ensured by the use of web technology optimized for efficient data handling and parallel data-processing. The examined use cases show the potential of the developed software module for its deployment in the use case of monitoring turn-mill-centers.