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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/26018

Title: Modelling manufacturing processes using Markov Chains
Authors: Leigh, Johanna M.
Jackson, Lisa M.
Dunnett, Sarah J.
Lugo, Heinz
Sharpe, Richard
Neal, Aaron
West, Andrew A.
Issue Date: 2017
Publisher: © CRC Press
Citation: LEIGH, J.M. ... et al., 2017. Modelling Manufacturing Processes using Markov Chains. Presented at the European Safety and Reliability Conference (ESREL 2017), Portoroz, Slovenia, 18th-22nd June.
Abstract: 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.
Description: This paper is closed access until twelve months after its publication.
Sponsor: The authors would also like to thank Engineering and Physical Sciences Research Council for the grant [EP/K014137/1].
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/26018
Publisher Link: http://esrel2017.org/
Appears in Collections:Closed Access (Aeronautical and Automotive Engineering)

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