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    Develoment of an inverse model for honing processes by means of neural networks  Open access

     Sivatte Adroer, Maurici; Llanas Parra, Francesc Xavier; Buj Corral, Irene; Vivancos Calvet, Joan
    International Reseach/Expert Conference "Trends in the Development of Machinery and Associated Technology"
    p. 9-12
    Presentation's date: 2014-09-11
    Presentation of work at congresses

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    In a previous paper, artificial neural networks were employed for modelling average roughness Ra in rough honing processes as a function of process variables, namely grain size, density, linear speed, tangential speed and pressure, by means of the direct problem. In addition, neural network model was compared to statistical models for modelling roughness. In the present paper the inverse problem was studied and analyzed by means of neural networks, in which given a certain average roughness Ra value, the model predicts process variables to be employed. This is not possible with statistical models. Two different approaches were considered: use of a single network or use of five networks.

    In a previous paper, artificial neural networks were employed for modelling average roughness Ra in rough honing processes as a function of process variables, namely grain size, density, linear speed, tangential speed and pressure, by means of the direct problem. In addition, neural network model was compared to statistical models for modelling roughness. In the present paper the inverse problem was studied and analyzed by means of neural networks, in which given a certain average roughness Ra value, the model predicts process variables to be employed. This is not possible with statistical models. Two different approaches were considered: use of a single network or use of five networks.

  • Contribució en la modelització de la rugositat superficial obtinguda en els processos de honing utilitzant xarxes neuronals artificials

     Sivatte Adroer, Maurici
    Universitat Politècnica de Catalunya
    Theses

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    A partir de dades experimentals obtingudes en una màquina d'assaigs construïda a l'efecte,l'objectiu d'aquesta tesi és modelitzar el procés de brunyit dels interiors de cilindres d'acer(procés de honing), utilitzant les xarxes neuronals artificials.Es seleccionen les cinc variables de procés que es consideren més rellevants i es defineix elPerceptró Multicapa amb l'algoritme d'aprenentatge backpropagation i el sistema de validaciócross-validation, com a xarxa neuronal base.En una primera fase es dissenya un model neuronal, de forma què a partir de les dades de procésseleccionades, dóna el paràmetre de rugositat superficial "Ra" que hi correspondria.En una segona fase es modelitza el problema invers. A partir del valor de la rugositat superficial"Ra" que es desitja, el model neuronal explicita els valors de les variables de procés que lafarien possible.Finalment, es dissenya un model iteratiu, utilitzant les xarxes seleccionades en les fasesanteriors, per millorar la modelització inversa.

  • Selection of a neural network for modelling the honing process

     Sivatte Adroer, Maurici; Llanas Parra, Francesc Xavier; Buj Corral, Irene; Vivancos Calvet, Joan
    International Reseach/Expert Conference "Trends in the Development of Machinery and Associated Technology"
    p. 1-4
    Presentation's date: 2013-09-11
    Presentation of work at congresses

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    Roughness obtained in honing process depends on many different process parameters, such as grain size of abrasive stones, pressure of stones on the workpiece¿s surface, density of abrasive, tangential speed of the honing head and linear speed of the honing head. This fact makes it difficult to study the process from an analytical point of view. For this reason, use of empirical methods or use of artificial intelligence is recommended in this case. In the present paper, results about use of neural networks for obtaining average roughness Ra as a function of honing parameters are presented. Best neural network was chosen among different possibilities. For doing this, experimental results were divided into three groups: 70 % of results were used for training, 15 % of results were used for validation and 15 % of results were used as test to compare networks with other models. The best neural network was considered to be the one with lowest errors using the validation experimental results.

    Roughness obtained in honing process depends on many different process parameters, such as grain size of abrasive stones, pressure of stones on the workpiece’s surface, density of abrasive, tangential speed of the honing head and linear speed of the honing head. This fact makes it difficult to study the process from an analytical point of view. For this reason, use of empirical methods or use of artificial intelligence is recommended in this case. In the present paper, results about use of neural networks for obtaining average roughness Ra as a function of honing parameters are presented. Best neural network was chosen among different possibilities. For doing this, experimental results were divided into three groups: 70 % of results were used for training, 15 % of results were used for validation and 15 % of results were used as test to compare networks with other models. The best neural network was considered to be the one with lowest errors using the validation experimental results.

  • Sistema per a l'autoaprenentatge i l'avaluació continuada

     Sivatte Adroer, Maurici
    Congrés Internacional de Docència Universitària i Innovació
    Presentation's date: 2006-07-06
    Presentation of work at congresses

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  • Mètode Docent basat en l'autoaprenentatge i l'autoavaluació

     Sivatte Adroer, Maurici
    1ª Jornadas de Docencia de EPSEVG
    Presentation's date: 2006-07-04
    Presentation of work at congresses

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  • Mètode Docent basat en l'autoaprenentatge i l'autoavaluació

     Magnusson Morer, Ingrid; Sivatte Adroer, Maurici; Joan, Solé; Sole Rovira, Juan
    1ª Jornadas de Docencia de EPSEVG
    Presentation of work at congresses

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  • Estudi, planificació i disseny d'una aplicació interactiva multimèdia per l'autoaprenentatge de cinemàtica de mecanismes plans

     Sivatte Adroer, Maurici
    Congrés Internacional de Docència Universitària i Innovació
    Presentation of work at congresses

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  • Aplicació Informàtica de suport a l'avaluació continuada

     Magnusson Morer, Ingrid; Sivatte Adroer, Maurici; Joan, Solé; Sole Rovira, Juan
    Congrés Internacional de Docència Universitària i Innovació
    Presentation of work at congresses

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  • Estudi, planificació i disseny d'una aplicació interactiva multimèdia per l'autoaprenentatge de cinemàtica de mecanismes plans.

     Sivatte Adroer, Maurici
    Congrés Internacional de Docència Universitària i Innovació
    Presentation's date: 2004-07-01
    Presentation of work at congresses

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  • Sistema per a l'autoaprenentatge i l'avaluació continuada

     Magnusson Morer, Ingrid; Sivatte Adroer, Maurici; Joan, Solé; Sole Rovira, Juan
    Congrés Internacional de Docència Universitària i Innovació
    Presentation of work at congresses

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  • Diseño de una aplicación multimedia orientada al auto aprendizaje de la cinemática de mecanismos

     Sivatte Adroer, Maurici
    Congreso Universitario de Innovación Educativa en las Enseñanzas Técnicas
    Presentation's date: 2004-07-28
    Presentation of work at congresses

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  • Diseño de una aplicación multimedia orientada al auto aprendizaje de la cinemática de mecanismos

     Sivatte Adroer, Maurici
    Congreso Universitario de Innovación Educativa en las Enseñanzas Técnicas
    p. 122
    Presentation of work at congresses

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  • evaluación de propuestas sobre el diseño de unidades móviles

     Sivatte Adroer, Maurici
    Jornada de expertos sobre la evaluación de propuestas sobre el diseño de unidades móviles
    Presentation's date: 1999-11-14
    Presentation of work at congresses

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