Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations
In a production system, achieving a high productivity with lowest cost is one of the overall goals. However, to maintain the quality of the product, usually a time constrain is assigned to the product where the product is considered fail if is it allowed to queue longer than the time constrain. The...
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sg-ntu-dr.10356-510322023-03-04T18:25:47Z Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations Leoga Proklamanus. School of Mechanical and Aerospace Engineering Wu Kan DRNTU::Engineering In a production system, achieving a high productivity with lowest cost is one of the overall goals. However, to maintain the quality of the product, usually a time constrain is assigned to the product where the product is considered fail if is it allowed to queue longer than the time constrain. The "fail" product is either reworked or scrapped. Rework and loss (scrap) will reduce the productivity and increase the production cost. There are many factors that because the product fails to enter the next station within the allocation time constrain. Pre-emptive interruption such as breakdown and repair on the station is one of the major caused to it. When station break down, the station will idle and the product will stagnant in the queue line. High Frequency of breakdown and long the repair time can cause a huge loss in production Other than pre-emptive interruptions, the service time in the station also play an important role. The length of service time will influence the rework and loss rate in the system One of the method to reduce rework and time constrain is by adjusting the queue time constrain. However, sometimes the queue time constrains are rigid. Allowing a loose time constrain may result to drop in standard and quality In this project, a production system consist of 2 single servers with a fixed queue time constrain in between and a deterministic (constant) service times in the 2 server. Both servers suffer a distributed time base preemptive interruption. The objective of this model is to find parameters that have high utilization and low rework / loss rate. Bachelor of Engineering (Mechanical Engineering) 2013-01-03T03:08:31Z 2013-01-03T03:08:31Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/51032 en Nanyang Technological University 94 p. application/pdf |
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DRNTU::Engineering Leoga Proklamanus. Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
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In a production system, achieving a high productivity with lowest cost is one of the overall goals. However, to maintain the quality of the product, usually a time constrain is assigned to the product where the product is considered fail if is it allowed to queue longer than the time constrain. The "fail" product is either reworked or scrapped. Rework and loss (scrap) will reduce the productivity and increase the production cost.
There are many factors that because the product fails to enter the next station within the allocation time constrain. Pre-emptive interruption such as breakdown and repair on the station is one of the major caused to it. When station break down, the station will idle and the product will stagnant in the queue line. High Frequency of breakdown and long the repair time can cause a huge loss in production
Other than pre-emptive interruptions, the service time in the station also play an important role. The length of service time will influence the rework and loss rate in the system
One of the method to reduce rework and time constrain is by adjusting the queue time constrain. However, sometimes the queue time constrains are rigid. Allowing a loose time constrain may result to drop in standard and quality
In this project, a production system consist of 2 single servers with a fixed queue time constrain in between and a deterministic (constant) service times in the 2 server. Both servers suffer a distributed time base preemptive interruption.
The objective of this model is to find parameters that have high utilization and low rework / loss rate. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Leoga Proklamanus. |
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Final Year Project |
author |
Leoga Proklamanus. |
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Leoga Proklamanus. |
title |
Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
title_short |
Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
title_full |
Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
title_fullStr |
Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
title_full_unstemmed |
Production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
title_sort |
production control policy for manufacturing systems with multiple server stations and time constraints between two consecutive operations |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/51032 |
_version_ |
1759856319709315072 |