A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss

Scheduling of jobs in a facility in a production line is important particularly if the workstations perform different types of operations requiring machine changeover. Determining an operational scheduling policy would therefore increase line productivity and minimize unnecessary production costs. T...

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Main Authors: Say, Arlene, Tiu, Pamela, Ty, Jeanne
Format: text
Language:English
Published: Animo Repository 1997
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/8311
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-89562021-08-15T03:05:53Z A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss Say, Arlene Tiu, Pamela Ty, Jeanne Scheduling of jobs in a facility in a production line is important particularly if the workstations perform different types of operations requiring machine changeover. Determining an operational scheduling policy would therefore increase line productivity and minimize unnecessary production costs. This study focuses on critical workstations undergoing in-process 100% inspection, wherein the output would either be good items, yield loss or rework items. The good units resulting from such a facility forms transfer batches before they are moved to the next facility. An output of a transfer batch in the final stage of the line is, in the same way, required by the system and these would also affect the transfer batches at the end of the each work facility. The rework items, on the other hand, are placed in a buffer and rerouted to the same workstation for a one-pass rework operation. Items reworked are then classified as either yield rates or yield losses. Holding cost and switchover cost are high, thus, finding the critical value for processing reworks would serve to balance these costs. Too small a critical value would result in frequent switchover which is a considerably high cost. Too big a critical value would then result in increased holding cost for the rework jobs. Hence, there is a need to come up with an operating policy of when to process these rework jobs. The model was formulated on the basis of one cycle (regular operation to rework operation to regular operation) 1997-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/8311 Bachelor's Theses English Animo Repository Mathematical models Stochastic processes Scheduling (Management) Production engineering Random operators Systems engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Mathematical models
Stochastic processes
Scheduling (Management)
Production engineering
Random operators
Systems engineering
spellingShingle Mathematical models
Stochastic processes
Scheduling (Management)
Production engineering
Random operators
Systems engineering
Say, Arlene
Tiu, Pamela
Ty, Jeanne
A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
description Scheduling of jobs in a facility in a production line is important particularly if the workstations perform different types of operations requiring machine changeover. Determining an operational scheduling policy would therefore increase line productivity and minimize unnecessary production costs. This study focuses on critical workstations undergoing in-process 100% inspection, wherein the output would either be good items, yield loss or rework items. The good units resulting from such a facility forms transfer batches before they are moved to the next facility. An output of a transfer batch in the final stage of the line is, in the same way, required by the system and these would also affect the transfer batches at the end of the each work facility. The rework items, on the other hand, are placed in a buffer and rerouted to the same workstation for a one-pass rework operation. Items reworked are then classified as either yield rates or yield losses. Holding cost and switchover cost are high, thus, finding the critical value for processing reworks would serve to balance these costs. Too small a critical value would result in frequent switchover which is a considerably high cost. Too big a critical value would then result in increased holding cost for the rework jobs. Hence, there is a need to come up with an operating policy of when to process these rework jobs. The model was formulated on the basis of one cycle (regular operation to rework operation to regular operation)
format text
author Say, Arlene
Tiu, Pamela
Ty, Jeanne
author_facet Say, Arlene
Tiu, Pamela
Ty, Jeanne
author_sort Say, Arlene
title A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
title_short A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
title_full A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
title_fullStr A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
title_full_unstemmed A mathematical model in determining an optimal policy for an N-stage production line with random rework and yield loss
title_sort mathematical model in determining an optimal policy for an n-stage production line with random rework and yield loss
publisher Animo Repository
publishDate 1997
url https://animorepository.dlsu.edu.ph/etd_bachelors/8311
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