Abstract
Industrial Internet of Things (IIoT) is a digital platform to perform machine-to-machine communication, acquire sensor data, analyse, and deliver comprehensive information and also facilitate the manufacturing system to implement smart decisions faster. This paper presents modelling and analysis of an IoT-enabled autonomous manufacturing system based on the performance metrics. Multi-agent interaction has been defined through a generalised control architecture, considering as an autonomous manufacturing system. The number of jobs entering and leaving the machines computes time-dependent performance metrics such as cycle time and work in process using Little’s law. The mean arrival rate of each machine is calculated by evaluating the amount of work and a utilisation factor. The squared coefficient of inter-arrival rates based on successive substitution of job flow from machine x to machine y has also been obtained. This is preliminary work in the process of designing an IoT-enabled autonomous manufacturing system capable of self-learning and executing accurate decision faster.
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Acknowledgements
Authors sincerely thank the Ministry of Electronics and Information Technology (MeitY), Government of India, for providing financial assistance under Visvesvaraya Ph.D. Scheme to carry out this research work at IIITDM Kancheepuram, Chennai, India.
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Badri Narayanan, K.B., Sreekumar, M. (2019). Modelling and Analysis of Multi-agent Approach for an IoT-Enabled Autonomous Manufacturing System. In: Narayanan, R., Joshi, S., Dixit, U. (eds) Advances in Computational Methods in Manufacturing. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-32-9072-3_54
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DOI: https://doi.org/10.1007/978-981-32-9072-3_54
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