Operational modelling of practical manufacturing systems
Operational modelling of practical manufacturing systems
Increased competition in many industries has resulted in complex manufacturing environments with an emphasis on effective and efficient manufacturing systems. Manufacturing systems involve complexity, uncertainty, variability, and use of resources. These conditions point to the use of the modelling approach of Operational Research for evolving the appropriate manufacturing systems. Analytical models are far too restrictive because of the simplifying assumptions that have to be made for solving the models. Simulation is potentially able to cater for all the complications of advanced manufacturing systems. Contrary to mathematical abstractions behind analytical models, visual animation enhances the understanding and credibility of simulation to a great extent. A customised simulation model can help with many manufacturing decisions at different managerial levels. This thesis presents two such simulation models developed for real-life environments and illustrates their use for resource allocation and production scheduling purposes.
The first simulation model considers a twelve-stage pull-type system with multiple servers at each stage for a small range of expensive high-tech electronic products. It involves many features (manual/automatic operations, rework and scrap operations, purchasing policies, stochastic demand) of practical manufacturing systems. Our objective is to allocate the machines in the best way possible in case a pull-type control mechanism is implemented on the shop floor. We focus on minimisation of total investment cost subject to a minimum level of customer service. An algorithm is proposed to search for an efficient allocation pattern in light of simulation results.
The second simulation model concentrates at a two-stage production facility for mass production of inexpensive products. There is a wide range of product types which require sequence-dependent setups when switching between different types on both stages. The manufacturing operation at the first stage requires multiple resources whereas the second stage is basically an assembly operation. The model is able to evaluate realistic scenarios involving scrap rates, stochastic demand, purchasing activities, etc. The objective is to increase the performance of the system through better production scheduling rules. Simulation output is used to compare a number of priority rules and suggest improvements to current planning practices.
University of Southampton
1998
Ozkan, Ozgur
(1998)
Operational modelling of practical manufacturing systems.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
Increased competition in many industries has resulted in complex manufacturing environments with an emphasis on effective and efficient manufacturing systems. Manufacturing systems involve complexity, uncertainty, variability, and use of resources. These conditions point to the use of the modelling approach of Operational Research for evolving the appropriate manufacturing systems. Analytical models are far too restrictive because of the simplifying assumptions that have to be made for solving the models. Simulation is potentially able to cater for all the complications of advanced manufacturing systems. Contrary to mathematical abstractions behind analytical models, visual animation enhances the understanding and credibility of simulation to a great extent. A customised simulation model can help with many manufacturing decisions at different managerial levels. This thesis presents two such simulation models developed for real-life environments and illustrates their use for resource allocation and production scheduling purposes.
The first simulation model considers a twelve-stage pull-type system with multiple servers at each stage for a small range of expensive high-tech electronic products. It involves many features (manual/automatic operations, rework and scrap operations, purchasing policies, stochastic demand) of practical manufacturing systems. Our objective is to allocate the machines in the best way possible in case a pull-type control mechanism is implemented on the shop floor. We focus on minimisation of total investment cost subject to a minimum level of customer service. An algorithm is proposed to search for an efficient allocation pattern in light of simulation results.
The second simulation model concentrates at a two-stage production facility for mass production of inexpensive products. There is a wide range of product types which require sequence-dependent setups when switching between different types on both stages. The manufacturing operation at the first stage requires multiple resources whereas the second stage is basically an assembly operation. The model is able to evaluate realistic scenarios involving scrap rates, stochastic demand, purchasing activities, etc. The objective is to increase the performance of the system through better production scheduling rules. Simulation output is used to compare a number of priority rules and suggest improvements to current planning practices.
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Published date: 1998
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Local EPrints ID: 464120
URI: http://eprints.soton.ac.uk/id/eprint/464120
PURE UUID: d9817318-7731-4638-8b31-a8c609bd6679
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Date deposited: 04 Jul 2022 21:19
Last modified: 04 Jul 2022 21:19
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Author:
Ozgur Ozkan
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