Estimation of the surface roughness of K9 optical glass in precision grinding using the brittle material removal fraction based on an improved image processing algorithm

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

Download Full-text

Simulation of the ductile machining mode of silicon

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-021-07167-3 ◽

2021 ◽

Author(s):

Hagen Klippel ◽

Stefan Süssmaier ◽

Matthias Röthlin ◽

Mohamadreza Afrasiabi ◽

Uygar Pala ◽

...

Keyword(s):

Brittle Material ◽

Material Removal ◽

Machining Process ◽

Ductile Material ◽

Diamond Wire ◽

Ductile Machining ◽

Mesh Free ◽

Diamond Wire Sawing ◽

Material Removal Mode ◽

Brittle Material Removal

AbstractDiamond wire sawing has been developed to reduce the cutting loss when cutting silicon wafers from ingots. The surface of silicon solar cells must be flawless in order to achieve the highest possible efficiency. However, the surface is damaged during sawing. The extent of the damage depends primarily on the material removal mode. Under certain conditions, the generally brittle material can be machined in ductile mode, whereby considerably fewer cracks occur in the surface than with brittle material removal. In the presented paper, a numerical model is developed in order to support the optimisation of the machining process regarding the transition between ductile and brittle material removal. The simulations are performed with an GPU-accelerated in-house developed code using mesh-free methods which easily handle large deformations while classic methods like FEM would require intensive remeshing. The Johnson-Cook flow stress model is implemented and used to evaluate the applicability of a model for ductile material behaviour in the transition zone between ductile and brittle removal mode. The simulation results are compared with results obtained from single grain scratch experiments using a real, non-idealised grain geometry as present in the diamond wire sawing process.

Download Full-text