Abstract-This paper describes an innovative modular component-based modelling approach for diagnostics and condition-monitoring of manufacturing equipment. The approach is based on the use of object-oriented Bayesian networks, which supports a natural decomposition of a large and complex system into a set of less complex components. The methodology consists of six steps supporting the development process: Begin, Design, Implement, Test, Analyse, and Deploy. The process is iterative and the steps should be repeated until a satisfactory model has been achieved. The paper describes the details of the methodology as well as illustrates the use of the componentbased modelling approach on a linear axis used in manufacturing. This application demonstrates the power and flexibility of the approach for diagnostics and condition-monitoring and shows a significant potential of the approach for modular componentbased modelling in manufacturing and other domains.
To support health monitoring and life-long capability management for self-sustaining manufacturing systems, next generation machine components are expected to embed sensory capabilities combined with advanced ICT. The combination of sensory capabilities and the use of Object-Oriented Bayesian Networks (OOBNs) supports self-diagnosis at the component level enabling them to become self-aware and support self-healing production systems. This paper describes the use of a modular component-based modelling approach enabled by the use of OOBNs for health monitoring and root-cause analysis of manufacturing systems using a welding controller produced by Harms & Wende (HWH) as an example. The model is integrated into the control software of the welding controller and deployed as a SelComp using the SelSus Architecture for diagnosis and predictive maintenance. The SelComp provides diagnosis and condition monitoring capabilities at the component level while the SelSus Architecture provides these capabilities at a wider system level. The results show significant potential of the solution developed.
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