Simulation optimisation based DSS application: a diamond tool production line in industry
Simulation optimisation based DSS application: a diamond tool production line in industry
A diamond tool manufacturing system simulation is developed to predict the number of machines and the number of workers necessary to maintain desired levels of production for a company in Ankara, Turkey. The current manufacturing system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized machines. Validated simulation outputs are collected and used to build a multiple regression meta-model as a simulation optimization based decision support system (DSS). The proposed DSS involves analysis and evaluation of the system’s behaviour through the use of a meta-model with an integrated optimization module. It enables the decision maker to perform sensitivity analysis by considering several combinations of decision variables. The aim of this study is two fold. The first is to represent a simulation optimization based DSS application for a real system by considering all the required steps. The second is to analyse the performance of the current production system and determine the optimum working conditions by simulation with greatly reduced cost, time, and effort
multi-stage multi-server production line, multiple regression meta-model, decision support system, simulation optimization, sensitivity analysis
296-312
Dengiz, B.
b10c6b06-5f7d-4b47-aac6-c3fb02b2f950
Bektas, T.
0db10084-e51c-41e5-a3c6-417e0d08dac9
Ultanir, A.E.
63ebbe19-730b-48eb-a07c-db88ccc8497e
April 2006
Dengiz, B.
b10c6b06-5f7d-4b47-aac6-c3fb02b2f950
Bektas, T.
0db10084-e51c-41e5-a3c6-417e0d08dac9
Ultanir, A.E.
63ebbe19-730b-48eb-a07c-db88ccc8497e
Dengiz, B., Bektas, T. and Ultanir, A.E.
(2006)
Simulation optimisation based DSS application: a diamond tool production line in industry.
Simulation Modelling Practice & Theory, 14 (3), .
(doi:10.1016/j.simpat.2005.07.001).
Abstract
A diamond tool manufacturing system simulation is developed to predict the number of machines and the number of workers necessary to maintain desired levels of production for a company in Ankara, Turkey. The current manufacturing system is analysed by a simulation model emphasizing the bottlenecks and the poorly utilized machines. Validated simulation outputs are collected and used to build a multiple regression meta-model as a simulation optimization based decision support system (DSS). The proposed DSS involves analysis and evaluation of the system’s behaviour through the use of a meta-model with an integrated optimization module. It enables the decision maker to perform sensitivity analysis by considering several combinations of decision variables. The aim of this study is two fold. The first is to represent a simulation optimization based DSS application for a real system by considering all the required steps. The second is to analyse the performance of the current production system and determine the optimum working conditions by simulation with greatly reduced cost, time, and effort
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Published date: April 2006
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Keywords:
multi-stage multi-server production line, multiple regression meta-model, decision support system, simulation optimization, sensitivity analysis
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Local EPrints ID: 47174
URI: http://eprints.soton.ac.uk/id/eprint/47174
ISSN: 1569-190X
PURE UUID: 1fd8d1d9-ddfc-40aa-b4c0-32cb6493a155
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Date deposited: 03 Aug 2007
Last modified: 15 Mar 2024 09:32
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Author:
B. Dengiz
Author:
T. Bektas
Author:
A.E. Ultanir
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