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Cyber physical process monitoring systems

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Abstract

Manufacturing process monitoring systems is evolving from centralised bespoke applications to decentralised reconfigurable collectives. The resulting cyber-physical systems are made possible through the integration of high power computation, collaborative communication, and advanced analytics. This digital age of manufacturing is aimed at yielding the next generation of innovative intelligent machines. The focus of this research is to present the design and development of a cyber-physical process monitoring system; the components of which consist of an advanced signal processing chain for the semi-autonomous process characterisation of a CNC turning machine tool. The novelty of this decentralised system is its modularity, reconfigurability, openness, scalability, and unique functionality. The function of the decentralised system is to produce performance criteria via spindle vibration monitoring, which is correlated to the occurrence of sequential process events via motor current monitoring. Performance criteria enables the establishment of normal operating response of machining operations, and more importantly the identification of abnormalities or trends in the sensor data that can provide insight into the quality of the process ongoing. The function of each component in the signal processing chain is reviewed and investigated in an industrial case study.

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Acknowledgments

This research was funded under the Graduate Research Education Programme in Engineering (GREP-Eng) which is a PRTLI Cycle 5 funded programme and is co-funded under the European Regional Development Fund. The author would like to thank his work colleagues at Trinity College Dublin for their assistance in collating this publication.

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  1. Department of Mechanical and Manufacturing Engineering, Trinity College Dublin, Dublin 2, UK

    Jeff Morgan & Garret E. O’Donnell

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  1. Jeff Morgan
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  2. Garret E. O’Donnell
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Correspondence to Jeff Morgan.

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Morgan, J., O’Donnell, G.E. Cyber physical process monitoring systems. J Intell Manuf 29, 1317–1328 (2018). https://doi.org/10.1007/s10845-015-1180-z

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