Classification analysis for simulation of machine breakdowns
Classification analysis for simulation of machine breakdowns
Machine failure is often an important factor in throughput of manufacturing systems. To simplify the inputs to the simulation model for complex machining and assembly lines, we have derived the Arrows classification method to group similar machines, where one model can be used to describe the breakdown times for all of the machines in the group and breakdown times of machines can be represented by finite mixture model distributions. The Two-Sample Cram´er-von Mises statistic is used to measure the similarity of two sets of data. We evaluate the classification procedure by comparing the throughput of a simulation model when run with mixture models fitted to individual machine breakdown times; mixture models fitted to group breakdown times; and raw data. Details of the methods and results of the grouping processes will be presented, and will be demonstrated using an example.
simulation, classification analysis
978-1-4244-1306-5
480-487
Lu, L.
172bffdd-bc45-47f5-955f-8d33998eca5f
Currie, C.S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Ladbrook, J.
c88fc9fe-87e1-459a-a1d6-c8bb8cbcd93b
December 2007
Lu, L.
172bffdd-bc45-47f5-955f-8d33998eca5f
Currie, C.S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Cheng, R.C.H.
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Ladbrook, J.
c88fc9fe-87e1-459a-a1d6-c8bb8cbcd93b
Lu, L., Currie, C.S.M., Cheng, R.C.H. and Ladbrook, J.
(2007)
Classification analysis for simulation of machine breakdowns.
Henderson, S.G., Biller, B., Hsieh, M.-H., Shortle, J., Tew, J.D. and Barton, R.R.
(eds.)
In Proceedings of the 2007 Winter Simulation Conference.
IEEE.
.
(doi:10.1109/WSC.2007.4419638).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Machine failure is often an important factor in throughput of manufacturing systems. To simplify the inputs to the simulation model for complex machining and assembly lines, we have derived the Arrows classification method to group similar machines, where one model can be used to describe the breakdown times for all of the machines in the group and breakdown times of machines can be represented by finite mixture model distributions. The Two-Sample Cram´er-von Mises statistic is used to measure the similarity of two sets of data. We evaluate the classification procedure by comparing the throughput of a simulation model when run with mixture models fitted to individual machine breakdown times; mixture models fitted to group breakdown times; and raw data. Details of the methods and results of the grouping processes will be presented, and will be demonstrated using an example.
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More information
Published date: December 2007
Venue - Dates:
Winter Simulation Conference 2007, Washington DC, USA, 2007-12-09 - 2007-12-12
Keywords:
simulation, classification analysis
Organisations:
Operational Research
Identifiers
Local EPrints ID: 54547
URI: http://eprints.soton.ac.uk/id/eprint/54547
ISBN: 978-1-4244-1306-5
PURE UUID: 69874d73-4f3b-4bc5-9216-c850ac6eb2e3
Catalogue record
Date deposited: 28 Jul 2008
Last modified: 16 Mar 2024 03:30
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Contributors
Author:
L. Lu
Author:
J. Ladbrook
Editor:
S.G. Henderson
Editor:
B. Biller
Editor:
M.-H. Hsieh
Editor:
J. Shortle
Editor:
J.D. Tew
Editor:
R.R. Barton
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