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Resource Allocation and Process Improvement of Genetic Manufacturing Systems

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dc.contributor.authorPurdy, Gregory T.en
dc.contributor.committeechairCamelio, Jaime A.en
dc.contributor.committeememberTaylor, G. Donen
dc.contributor.committeememberEllis, Kimberly P.en
dc.contributor.committeememberKoelling, C. Patricken
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2018-05-16T06:00:17Zen
dc.date.available2018-05-16T06:00:17Zen
dc.date.issued2016-11-21en
dc.description.abstractBreakthroughs in molecular and synthetic biology through de novo gene synthesis are stimulating new vaccines, pharmaceutical applications, and functionalized biomaterials, and advancing the knowledge of the function of cells. This evolution in biological processing motivates the study of a class of manufacturing systems, defined here as genetic manufacturing systems, which produce a final product with a genetic construct. Genetic manufacturing systems rely on rare molecular events for success, resulting in waste and repeated work during the deoxyribonucleic acid (DNA) fabrication process. Inspection and real time monitoring strategies are possible as mitigation tools, but it is unclear if these techniques are cost efficient and value added for the successful creation of custom genetic constructs. This work investigates resource allocation strategies for DNA fabrication environments, with an emphasis on inspection allocation. The primary similarities and differences between traditional manufacturing systems and genetic manufacturing systems are described. A serial, multi-stage inspection allocation mathematical model is formulated for a genetic manufacturing system utilizing gene synthesis. Additionally, discrete event simulation is used to evaluate inspection strategies for a fragment synthesis process and multiple fragment assembly operation. Results from the mathematical model and discrete event simulation provide two approaches to determine the appropriate inspection strategies with respect to total cost or total flow time of the genetic manufacturing system.en
dc.description.abstractgeneralBreakthroughs in molecular and synthetic biology through <i>de novo</i> gene synthesis are stimulating new vaccines, pharmaceutical applications, and functionalized biomaterials, and advancing the knowledge of the function of cells. This evolution in biological processing motivates the study of a class of manufacturing systems, defined here as genetic manufacturing systems, which produce a final product with a genetic construct. Genetic manufacturing systems rely on rare molecular events for success, resulting in waste and repeated work during the deoxyribonucleic acid (DNA) fabrication process. Inspection and real time monitoring strategies are possible as mitigation tools, but it is unclear if these techniques are cost efficient and value added for the successful creation of custom genetic constructs. This work investigates resource allocation strategies for DNA fabrication environments, with an emphasis on inspection allocation. The primary similarities and differences between traditional manufacturing systems and genetic manufacturing systems are described. A serial, multi-stage inspection allocation mathematical model is formulated for a genetic manufacturing system utilizing gene synthesis. Additionally, discrete event simulation is used to evaluate inspection strategies for a fragment synthesis process and multiple fragment assembly operation. Results from the mathematical model and discrete event simulation provide two approaches to determine the appropriate inspection strategies with respect to total cost or total flow time of the genetic manufacturing system.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:9228en
dc.identifier.urihttp://hdl.handle.net/10919/83231en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectDiscrete Event Simulationen
dc.subjectGene Synthesisen
dc.subjectGenetic Manufacturing Systemsen
dc.subjectInspection Allocationen
dc.subjectMathematical Modelingen
dc.subjectMolecular Biologyen
dc.subjectSynthetic Biologyen
dc.titleResource Allocation and Process Improvement of Genetic Manufacturing Systemsen
dc.typeDissertationen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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