Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System
Mandibular fractures are common facial lesions typically treated with titanium plate and screw systems; nevertheless, this material is associated with secondary effects. Absorbable material for implants is an alternative to titanium, but there are also problems such as incomplete screw insertion and...
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MDPI AG
2021-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/3/1350 |
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| author | Alex Bernardo Pimentel-Mendoza Lázaro Rico-Pérez Manuel Javier Rosel-Solis Luis Jesús Villarreal-Gómez Yuridia Vega José Omar Dávalos-Ramírez |
| author_facet | Alex Bernardo Pimentel-Mendoza Lázaro Rico-Pérez Manuel Javier Rosel-Solis Luis Jesús Villarreal-Gómez Yuridia Vega José Omar Dávalos-Ramírez |
| author_sort | Alex Bernardo Pimentel-Mendoza |
| collection | DOAJ |
| description | Mandibular fractures are common facial lesions typically treated with titanium plate and screw systems; nevertheless, this material is associated with secondary effects. Absorbable material for implants is an alternative to titanium, but there are also problems such as incomplete screw insertion and screw breakage due to high pretension in the screw caused by the insertion torque. The purpose of this paper is to find the optimal screw pretension (SP) in absorbable plate and screw systems by means of artificial neural network (ANN) and its inverse (ANNi). This optimal SP must satisfy a desired maximum von Mises strain (MVMS). For training the ANN, a database was generated by means of a design of experiments (DOE). Each DOE configuration was solved by means of finite element method (FEM) calculations. To obtain the optimal value for (SP) in the mini absorbable screw for fracture fixation, a strategy to invert the ANN is developed. Using the ANN coefficients, a sensitive study was performed to identify the influence of the design parameters in the MVMS. The optimal SP obtained was 14.9742 N. The MVMS condition was satisfied with an error less than 1.1% in comparison with FEM and ANN results. The screw shaft length is the most influencing MVMS parameter. |
| first_indexed | 2024-03-09T06:01:23Z |
| format | Article |
| id | doaj.art-7879d5f5558b4ee394b943b45f8db48b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T06:01:23Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7879d5f5558b4ee394b943b45f8db48b2023-12-03T12:08:37ZengMDPI AGApplied Sciences2076-34172021-02-01113135010.3390/app11031350Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw SystemAlex Bernardo Pimentel-Mendoza0Lázaro Rico-Pérez1Manuel Javier Rosel-Solis2Luis Jesús Villarreal-Gómez3Yuridia Vega4José Omar Dávalos-Ramírez5Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana 22260, MexicoDepartamento de Ingeniería Industrial y Manufactura, Instituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Juárez 32584 Cd., MexicoFacultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana 22260, MexicoFacultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana 22260, MexicoFacultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana 22260, MexicoDepartamento de Ingeniería Industrial y Manufactura, Instituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Juárez 32584 Cd., MexicoMandibular fractures are common facial lesions typically treated with titanium plate and screw systems; nevertheless, this material is associated with secondary effects. Absorbable material for implants is an alternative to titanium, but there are also problems such as incomplete screw insertion and screw breakage due to high pretension in the screw caused by the insertion torque. The purpose of this paper is to find the optimal screw pretension (SP) in absorbable plate and screw systems by means of artificial neural network (ANN) and its inverse (ANNi). This optimal SP must satisfy a desired maximum von Mises strain (MVMS). For training the ANN, a database was generated by means of a design of experiments (DOE). Each DOE configuration was solved by means of finite element method (FEM) calculations. To obtain the optimal value for (SP) in the mini absorbable screw for fracture fixation, a strategy to invert the ANN is developed. Using the ANN coefficients, a sensitive study was performed to identify the influence of the design parameters in the MVMS. The optimal SP obtained was 14.9742 N. The MVMS condition was satisfied with an error less than 1.1% in comparison with FEM and ANN results. The screw shaft length is the most influencing MVMS parameter.https://www.mdpi.com/2076-3417/11/3/1350inverse artificial neural networkfinite element methodmini plate and screwabsorbableoptimization |
| spellingShingle | Alex Bernardo Pimentel-Mendoza Lázaro Rico-Pérez Manuel Javier Rosel-Solis Luis Jesús Villarreal-Gómez Yuridia Vega José Omar Dávalos-Ramírez Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System Applied Sciences inverse artificial neural network finite element method mini plate and screw absorbable optimization |
| title | Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System |
| title_full | Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System |
| title_fullStr | Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System |
| title_full_unstemmed | Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System |
| title_short | Application of Inverse Neural Networks for Optimal Pretension of Absorbable Mini Plate and Screw System |
| title_sort | application of inverse neural networks for optimal pretension of absorbable mini plate and screw system |
| topic | inverse artificial neural network finite element method mini plate and screw absorbable optimization |
| url | https://www.mdpi.com/2076-3417/11/3/1350 |
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