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- W2901431366 abstract "Predictive maintenance, in contrast to preventive maintenance, raises the manufacturing quality and reliability, where the integrity is monitored continuously in service. To prevent cost intensive reengineering of outdated production plants, a retrofitting approach is presented to enable older machines towards Industry 4.0. The tool wear of a CNC milling machine is monitored using a programmable prototyping platform equipped with built-in senors. An artificial neural network is trained with acceleration data in order to classify the tool state. This demonstrative example proves the feasibility of retrofitting older machines, supported by the strongly growing field of computational intelligence and big data analysis." @default.
- W2901431366 created "2018-11-29" @default.
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- W2901431366 date "2019-01-01" @default.
- W2901431366 modified "2023-10-05" @default.
- W2901431366 title "Tool wear monitoring of a retrofitted CNC milling machine using artificial neural networks" @default.
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- W2901431366 doi "https://doi.org/10.1016/j.mfglet.2018.11.001" @default.
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