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dc.rights.licenseAll rights reserveden_US
dc.contributor.advisorTorres Batista, Nelliud D.
dc.contributor.authorVélez Báez, Héctor
dc.date.accessioned2021-08-16T14:49:57Z
dc.date.available2021-08-16T14:49:57Z
dc.date.issued2021
dc.identifier.citationVélez Báez, H. (2021). Implementation of Data Mining Techniques and Machine Learning Model in Manufacturing Process [Unpublished manuscript]. Graduate School, Polytechnic University of Puerto Rico.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12475/1124
dc.descriptionDesign Project Article for the Graduate Programs at Polytechnic University of Puerto Ricoen_US
dc.description.abstractTime in manufacturing process is critical. A lot of manufacturing companies rely on their operator’s knowledge, experience, or random methods to adjust CNC machines. Sometimes these judgements are ineffective and limited to their own knowledge resulting in an overall decrease in productivity, sales, and profit. Data mining has proven to be an important tool for knowledge acquisition in manufacturing processes. In this paper we will show how data mining techniques and machine learning model could help to effectively adjust CNC machines based on historical data. Key Terms ⎯ data mining, machine learning, manufacturing, neural networken_US
dc.language.isoen_USen_US
dc.publisherPolytechnic University of Puerto Ricoen_US
dc.relation.ispartofComputer Science Program;
dc.relation.ispartofseriesSpring-2021;
dc.relation.haspartSan Juanen_US
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Researchen_US
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Postersen_US
dc.subject.lcshMachine learningen_US
dc.subject.lcshData mining
dc.titleImplementation of Data Mining Techniques and Machine Learning Model in Manufacturing Processen_US
dc.typeArticleen_US
dc.rights.holderPolytechnic University of Puerto Rico, Graduate Schoolen_US


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