Modeling and optimization of multi-scale machining operations

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buir.advisorKarpat, Yiğit
dc.contributor.authorYılmaz, Fevzi
dc.date.accessioned2016-01-08T18:19:59Z
dc.date.available2016-01-08T18:19:59Z
dc.date.issued2012
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionAnkara : The Department of Industrial Engineeringand the Graduate School of Engineering and Science of Bilkent University, 2012.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2012.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractMinimization of production time, cost and energy while improving the part quality is the main goal in manufacturing. In order to be competitive in today’s global markets, it is crucial to develop high precision machine tools and maintain high productive operation of the machine tools through intelligent and effective selection of machining parameters. A recent shift in manufacturing industry is towards the production of high value added micro parts which are mainly used in biomedical and electronics industries. However, the knowledge base for micro machining operations is quite limited compared to macro scale machining processes. Metal cutting, which allows production of parts with complex shapes made from engineering materials, constitutes a large portion in all manufacturing activities and expected to remain so in upcoming years. In this thesis, modeling and optimization of macro scale turning and micro scale milling operations have been considered. A well known multi pass turning problem from the literature is used as a benchmark tool to test the performances of Particle Swarm Optimization (PSO) technique and nonlinear optimization algorithms. It is shown that acceptable results can be obtained through PSO in short time. Micro scale milling operation is thoroughly investigated through experimental techniques where the influences of machining parameters on the process outputs (machining forces, surface quality, and tool life) have been investigated and factors affecting the process outputs are identified. A minimum unit cost optimization problem is formulated based on the pocketing operation and machining strategies are proposed for different machining scenarios using PSO technique.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityYılmaz, Fevzien_US
dc.format.extentxiii, 117 leaves, illustrationsen_US
dc.identifier.urihttp://hdl.handle.net/11693/15532
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectTurningen_US
dc.subjectMicro millingen_US
dc.subjectProcess optimizationen_US
dc.subjectDesign of experimentsen_US
dc.subjectParticle swarm optimizationen_US
dc.subject.lccTS183 .Y55 2012en_US
dc.subject.lcshManufacturing processes--Mathematical models.en_US
dc.subject.lcshMicromachining.en_US
dc.subject.lcshMilling cutters.en_US
dc.subject.lcshTurning--Mathematical models.en_US
dc.titleModeling and optimization of multi-scale machining operationsen_US
dc.typeThesisen_US
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