Abstract
Optical glass K9 is a key kind of materials in many industries, and grinding process of it is usually employed as the main rough machining technique. However, most previous observations have been performed either ex-situ after grinding operations or in-situ but by human raw eyes, therefore cannot satisfy the new paradigm of Industry 4.0. In this paper, an in-situ and in-process observation and evaluation methodology of machined surfaces in K9 grinding is attempted to be proposed, which is based on image processing techniques and therefore enables the automation of the observation and evaluation processes. Grinding trials proved that the method could output accurate evaluation results, and the method performance is stable even for the ground K9 surface images with wide ranges of characteristics. Because the method could in-situ and in-process observe a fixed spot on the ground surfaces, more in-depth understandings of K9 grinding mechanism are gained. More importantly, the method could quantify the ductile/brittle region area and area proportions, based on which, the proposed method could be utilized not only to automatically in-situ and in-process monitor the grinding performance but also to optimize or provide suggestions for the future intelligent or smart manufacturing of K9.
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Zhao, Y.J., Li, H.N., Song, K.C. et al. In-situ and in-process monitoring of optical glass grinding process based on image processing technique. Int J Adv Manuf Technol 93, 3017–3031 (2017). https://doi.org/10.1007/s00170-017-0743-x
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DOI: https://doi.org/10.1007/s00170-017-0743-x