首页|Investigation on the greyscale pixel methodology for additive manufactured part: an in-situ quality assessment approach
Investigation on the greyscale pixel methodology for additive manufactured part: an in-situ quality assessment approach
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NSTL
This present work investigates the computer vision and machine vision algorithms in the selective laser melting (SLM) process to additively manufacture the product. The proposed method provides a real-time layer-by-layer sequence monitoring feature during the layer deposition process. This real-time monitoring helps reduce waste by deciding on the termination or continuation of the production process. The method proposed and elucidated is monitoring by capturing the layer image after the laser melting process completes. A total of eight layers are simulated and analysed in the proposed work. The images are analysed using the greyscale pixel value algorithm. The present work results demonstrate the capability of greyscale pixel analysis to identify and quantify defects in the SLM processed layer. The analysis results show the feasibility and potential of exploiting bulk manufacturing quality control and inspection in an industrial environment.
NSTL
