Surface evaluation of orthopedic hip implants marketed in Brazil

Souza, Maíra Massuia de; Trommer, Rafael Mello; Maru, Márcia Marie; Roesler, Carlos Rodrigo de Mello; Barros, Wellington Santos; Dutra, Max Suell

doi:10.1088/1742-6596/733/1/012034

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…The main parameter used to evaluate the surface roughness of a machined surface is the average roughness (Ra) [ 21 , 33 ]. In medical implants, the Ra value is most often situated below 2 μm [ 30 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

et al. 2021

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The aim of this paper is to conduct an experimental study in order to obtain a roughness (Ra) prediction model for dry end-milling (with an AlTiCrSiN PVD-coated tool) of the Co–28Cr–6Mo and Co–20Cr–15W–10Ni biomedical alloys, a model that can contribute to more quickly obtaining the desired surface quality and shortening the manufacturing process time. An experimental plan based on the central composite design method was adopted to determine the influence of the axial depth of cut, feed per tooth and cutting speed process parameters (input variables) on the Ra surface roughness (response variable) which was recorded after machining for both alloys. To develop the prediction models, statistical techniques were used first and three prediction equations were obtained for each alloy, the best results being achieved using response surface methodology. However, for obtaining a higher accuracy of prediction, ANN models were developed with the help of an application made in LabView for roughness (Ra) prediction. The primary results of this research consist of the Co–28Cr–6Mo and Co–20Cr–15W–10Ni prediction models and the developed application. The modeling results show that the ANN model can predict the surface roughness with high accuracy for the considered Co–Cr alloys.

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Section: Introductionmentioning

confidence: 99%

Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

et al. 2021

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Magnetorheological finishing of UHMWPE acetabular cup surface and its performance analysis

Arora

Singh

2020

Materials and Manufacturing Processes

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Investigation of Surface Roughness in Novel Magnetorheological Finishing of the Internal Hemispherical-Shaped Acetabular Cup Workpieces

Arora

Paswan

Singh

2022

Journal of Manufacturing Science and Engineering

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In today's world, the hemispherical-shaped component's fine finishing with high wear resistance and dimensional accuracy is required in different applications such as shells, molds, implants. The magnetorheological finishing (MRF) process with a novel hemispherical tip-based tool is used to finish the hemispherical cups. The study aims to develop a novel mathematical model theoretically for predicting the surface roughness reduction of the hemispherical shaped workpieces using the present MRF process. In the MRF process, the magnetic field controls the external forces, therefore, the magnetic flux density (MFD) effect on the fine finishing of the hemispherical shaped workpieces has been studied theoretically and further validated experimentally. Next, to validate the present mathematical model, experiments are done over the hemispherical shaped acetabular cups. The results of the predicted roughness match well with the experimental values with the error range from 1.17 % to 6.15 %. To analyze the efficacy of the present process, the surface morphology tests is performed on workpiece using scanning electron microscopy. The present mathematical model for the MRF process predicts fine finishing along with the overall enhancement in the surface quality of the hemispherical shaped cup surface.

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Surface evaluation of orthopedic hip implants marketed in Brazil

Cited by 3 publications

References 2 publications

Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

Surface Roughness Analysis and Prediction with an Artificial Neural Network Model for Dry Milling of Co–Cr Biomedical Alloys

Magnetorheological finishing of UHMWPE acetabular cup surface and its performance analysis

Investigation of Surface Roughness in Novel Magnetorheological Finishing of the Internal Hemispherical-Shaped Acetabular Cup Workpieces

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