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Texture analysis and evaluation would help in predicting a component's functionality. An attempt has been made in the current research work to explore the texture properties of machined surfaces in detail. Pieces made from milling, shaping, grinding, EDM, and sandblasting processes are used for texture analysis. The method uses a charge-coupled device (CCD) camera connected to the vision system to acquire images for texture analysis. The experimental investigation revealed that texture features extracted from the grey level co-occurrence matrix (GLCM) help study texture features. The experimental investigation revealed that when distance =1, the classification accuracy was less. However, the classification accuracy improved when distance =2, but a further increase in the distance would not significantly improve the classification accuracy. Instead, it would add up to the computational time. Thus, it was concluded that d=2 gave maximum classification accuracy of 96%. [ABSTRACT FROM AUTHOR]

Texture analysis and evaluation would help in predicting a component's functionality. An attempt has been made in the current research work to explore the texture properties of machined surfaces in detail. Pieces made from milling, shaping, grinding, EDM, and sandblasting processes are used for texture analysis. The method uses a charge-coupled device (CCD) camera connected to the vision system to acquire images for texture analysis. The experimental investigation revealed that texture features extracted from the grey level co-occurrence matrix (GLCM) help study texture features. The experimental investigation revealed that when distance =1, the classification accuracy was less. However, the classification accuracy improved when distance =2, but a further increase in the distance would not significantly improve the classification accuracy. Instead, it would add up to the computational time. Thus, it was concluded that d=2 gave maximum classification accuracy of 96%. [ABSTRACT FROM AUTHOR]

The Fraunhofer Institutes for Solar Energy Systems ISE and for Mechanics of Materials IWM in cooperation with industrial partners have explored routes for highly cost effective mass manufacturing of dome lens shaped glass secondary optical elements (SOEs) for concentrating photovoltaics (CPV). This included optical design studies, design optimizations and outdoor measurements on prototypes by Fraunhofer ISE. Fraunhofer IWM has explored a short cycle molding process suitable for low-cost high volume production. SOEs of spherical shape can be a possible option for a cost-effective production. [ABSTRACT FROM AUTHOR]