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Assembly line rebalancing with non-constant task time attribute
Descriptive
TitleInfo
Title
Assembly line rebalancing with non-constant task time attribute
Name
(type = personal)
NamePart
(type = family)
Li
NamePart
(type = given)
Yuchen
NamePart
(type = date)
1988-
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Yuchen Li
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(authority = RULIB)
author
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(type = personal)
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(type = family)
Boucher
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Thomas
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Thomas Boucher
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Advisory Committee
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(authority = RULIB)
chair
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(type = family)
Albin
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Susan
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Susan Albin
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Advisory Committee
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internal member
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(type = personal)
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(type = family)
Coit
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(type = given)
David
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David Coit
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Wang
NamePart
(type = given)
Honggang
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Honggang Wang
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Nembhard
NamePart
(type = given)
David
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David Nembhard
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Advisory Committee
Role
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(authority = RULIB)
outside member
Name
(type = personal)
NamePart
(type = family)
Das
NamePart
(type = given)
Sanchoy
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Sanchoy Das
Affiliation
Advisory Committee
Role
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(authority = RULIB)
outside member
Name
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Rutgers University
Role
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(authority = RULIB)
degree grantor
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NamePart
Graduate School - New Brunswick
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school
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Text
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theses
OriginInfo
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2016
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2016-10
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2016
Place
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xx
Language
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eng
Abstract
(type = abstract)
Assembly line has been widely used in producing complex items, such as automobiles and other transportation equipment, household appliances and electronic goods. Assembly line balancing is to maximize the efficiency of the assembly line so that the optimal production rate or optimal length of the line is obtained. Since the 1950s there has been a plethora of research studies focusing on the methodologies for assembly line balancing. Methods and algorithms were developed to balance an assembly line, which is operated by human workers, in a fast and efficient fashion. However, more and more assembly lines are incorporating automation in the design of the line, and in that case the line balancing problem structure is altered. For these automated assembly lines, novel algorithms are provided in this dissertation to efficiently solve the automated line balancing problem when the assembly line includes learning automata. Recent studies show that the task time can be improved during production due to machine learning, which gives the opportunities to rebalance the assembly line as the improvements occur and are observed. The concept of assembly line rebalancing or task reassignment are crucial for the assembly which is designed for small volume production because of the demand variation and rapid innovation of new product. In this dissertation, two forms of rebalancing are provided, forward planning and real time adjustment. The first one is to develop a planning schedule before production begins given the task time improvement is deterministic. The second one is to rebalance the line after the improvements are realized given the task time improvement is random. Algorithms address one sided and two sided assembly lines are proposed. Computation experiments are performed in order to test the performance of the novel algorithms and empirically validate the merit of improvement of production statistics.
Subject
(authority = RUETD)
Topic
Industrial and Systems Engineering
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_7563
PhysicalDescription
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electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xiv, 193 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Subject
(authority = ETD-LCSH)
Topic
Line of balance (Management)
Subject
(authority = ETD-LCSH)
Topic
Assembly-line methods
Note
(type = statement of responsibility)
by Yuchen Li
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3XK8HVS
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Li
GivenName
Yuchen
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2016-09-12 22:32:30
AssociatedEntity
Name
Yuchen Li
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ContentModel
ETD
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windows xp
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1.7
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福昕PDF生成器版本 7.2.0.0424
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2016-09-12T22:29:22
DateCreated
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2016-09-12T22:29:22
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