Publication:
Intelligent toolpath selection via multi-criteria optimization in complex sculptured surface milling

dc.contributor.coauthorManav, C.
dc.contributor.departmentDepartment of Mechanical Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorBank, Sinan Hasan
dc.contributor.kuauthorLazoğlu, İsmail
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T23:02:41Z
dc.date.issued2013
dc.description.abstractA new approach is presented the first time in the literature to generate multi-criteria optimized toolpaths for the complex sculptured surface machining. This is achieved by developing a mathematical solution that consists of the physical relationship between the mean resultant forces, cycle times and scallop heights. These three critical process outputs in machining are conflicting with each other. In other words, there are tradeoffs between cutting force magnitudes, cycle time and scallop height. This triple bounded problem in machining is solved in this article by using the objective weighting based algorithm. The multi-criteria toolpath optimization method introduced here for sculptured surface machining increases the controllability of the process with the specified criteria. The method also allows determining all pareto optimal solutions and all possible weights of each criteria. Moreover, the method eases to observe and analyze the trade-off between each criterion, facilitate the limitation and minimization of each criterion and determine corresponding toolpath for each solution. This solution produces optimized toolpaths according to preset constraints for mean cutting force, cycle time and scallop height. The method is a generalized solution for determining optimized toolpaths based on given constrains in free-form surface machining. In order to validate the multi-criteria toolpath optimization method, experiments at various conditions are performed on free-form machining and an example is presented in this article.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue2
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume24
dc.identifier.doi10.1007/s10845-011-0596-3
dc.identifier.eissn1572-8145
dc.identifier.issn0956-5515
dc.identifier.scopus2-s2.0-84880243444
dc.identifier.urihttps://doi.org/10.1007/s10845-011-0596-3
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8340
dc.identifier.wos316689000010
dc.keywordsIntelligent machining
dc.keywordsMilling
dc.keywordsForce
dc.keywordsCycle time
dc.keywordsScallop height
dc.keywordsFree-form surface
dc.keywordsTool path
dc.keywordsMulti-criteria optimization path generation
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofJournal of Intelligent Manufacturing
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectEngineering
dc.subjectManufacturing engineering
dc.titleIntelligent toolpath selection via multi-criteria optimization in complex sculptured surface milling
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorBank, Sinan Hasan
local.contributor.kuauthorLazoğlu, İsmail
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Mechanical Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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relation.isOrgUnitOfPublication3fc31c89-e803-4eb1-af6b-6258bc42c3d8
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