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Modelling manufacturing processes using Markov chains

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conference contribution
posted on 10.08.2017, 14:36 by Johanna M. Leigh, Lisa Jackson, Sarah Dunnett, Heinz Lugo, Richard Sharpe, Aaron Neal, Andrew West
Optimizing manufacturing processes with inaccurate models of the process will lead to unre-liable results. This can be true when there is a strong human influence on the manufacturing process and many variable aspects. This study investigates modelling a manufacturing process influenced by human inter-action with very variable products being processed. To develop a more accurate process model for such pro-cesses radio frequency identification (RFID) tags can be used to track products through the process. The tags record information for each product and this data can be used to produce more accurate models of the manu-facturing process. The data produced has been used to create a Markov chain model. This model is used to predict future product paths for use in discrete event simulation. In this case an IT refurbishment company is used as a case study. RFID tags have been utilized to track the IT products moving through the refurbishment process and this information has been used to produce a Markov chain model.


The authors would also like to thank Engineering and Physical Sciences Research Council for the grant [EP/K014137/1].



  • Mechanical, Electrical and Manufacturing Engineering

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European Safety and Reliability Conference


LEIGH, J.M. ... et al., 2017. Modelling manufacturing processes using Markov chains. IN: Cepin, M. and Bris, R. (eds). Safety and Reliability. Theory and Applications: Proceedings of the 27th European Safety and Reliability Conference (ESREL 2017), Portoroz, Slovenia, 18-22 June 2017. Leiden, The Netherlands: CRC Press, pp.2497-2502.


© CRC Press


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This is an Accepted Manuscript of a paper published by CRC Press in Safety and Reliability. Theory and Applications on 25 May 2017, available online:






Portoroz, Slovenia


Loughborough Publications