Recovery-based rescheduling and optimisation of batch production processes

2.50
Hdl Handle:
http://hdl.handle.net/10547/293805
Title:
Recovery-based rescheduling and optimisation of batch production processes
Authors:
Tan, Yaqing
Abstract:
Batch production processes are widely used in the process industries, applied to produce high-value added products with great varieties but in small volumes. The dynamic features of batch production processes contribute to the flexibility of the processes, but also pose big challenges to process scheduling problems. Moreover, disturbances in such a dynamic environment intensify its complexity. In this work, scheduling and rescheduling models on batch production processes are proposed, considering parallel machines allocation, storage capacity and waiting. The rescheduling model addresses process disturbances, such as machine breakdown and rush orders, in a recovery-based approach, which uses the original schedules as a guide to diminish the deviations between new and original schedules. Genetic Algorithms (GA) and Constraint Programming (CP) are applied to solve the models, but the rescheduling model built by CP can be applied to original schedules created by any techniques. According to case studies and experiments on the proposed scheduling and rescheduling approaches, it is found that CP has a better performance for scheduling and rescheduling problems with complex constraints although it cost longer time than GA. It is also found that rush orders exerted bigger influences on the batch production process than machine breakdowns, especially when the breakdowns do not happen on the ‘bottleneck’ machines.
Citation:
Tan, Y. (2012) 'Recovery-based rescheduling and optimisation of batch production processes' MSc Thesis. University of Bedfordshire.
Publisher:
University of Bedfordshire
Issue Date:
Sep-2012
URI:
http://hdl.handle.net/10547/293805
Type:
Thesis or dissertation
Language:
en
Description:
A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Master of Science by research
Appears in Collections:
Masters e-theses

Full metadata record

DC FieldValue Language
dc.contributor.authorTan, Yaqingen_GB
dc.date.accessioned2013-06-11T08:53:57Z-
dc.date.available2013-06-11T08:53:57Z-
dc.date.issued2012-09-
dc.identifier.citationTan, Y. (2012) 'Recovery-based rescheduling and optimisation of batch production processes' MSc Thesis. University of Bedfordshire.en_GB
dc.identifier.urihttp://hdl.handle.net/10547/293805-
dc.descriptionA thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Master of Science by researchen_GB
dc.description.abstractBatch production processes are widely used in the process industries, applied to produce high-value added products with great varieties but in small volumes. The dynamic features of batch production processes contribute to the flexibility of the processes, but also pose big challenges to process scheduling problems. Moreover, disturbances in such a dynamic environment intensify its complexity. In this work, scheduling and rescheduling models on batch production processes are proposed, considering parallel machines allocation, storage capacity and waiting. The rescheduling model addresses process disturbances, such as machine breakdown and rush orders, in a recovery-based approach, which uses the original schedules as a guide to diminish the deviations between new and original schedules. Genetic Algorithms (GA) and Constraint Programming (CP) are applied to solve the models, but the rescheduling model built by CP can be applied to original schedules created by any techniques. According to case studies and experiments on the proposed scheduling and rescheduling approaches, it is found that CP has a better performance for scheduling and rescheduling problems with complex constraints although it cost longer time than GA. It is also found that rush orders exerted bigger influences on the batch production process than machine breakdowns, especially when the breakdowns do not happen on the ‘bottleneck’ machines.en_GB
dc.language.isoenen
dc.publisherUniversity of Bedfordshireen_GB
dc.subjectH131 Automated Engineering Designen_GB
dc.subjectbatch production systemsen_GB
dc.subjectschedulingen_GB
dc.subjectgenetic algorithmsen_GB
dc.subjectconstraint programmingen_GB
dc.titleRecovery-based rescheduling and optimisation of batch production processesen
dc.typeThesis or dissertationen
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