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The objective of this research is to maintain the operational state of a flexible manufacturing system (FMS) within the required timeframe by developing and implementing a method for operational control of cutting tools and processed workpieces. A reliable technological system (TS) for the mechanical processing operation is to maintain the production of parts with the required quality and quantity within the specified time, particularly crucial when considering FMSs that eliminate personnel to constantly monitor the technological operation. Through the conducted analytical review, the relevance and immediacy of the work aimed at developing the method for operational control of cutting tools and workpieces are emphasized. This method involves the autonomous operation of the TS through multisensory integration of data on changes in geometric parameters of cutting tools and workpieces, with programming automation and management of information about cutting tools using a database of cutting and auxiliary tool parameters. Within the scope of the research, an experimental validation of the proposed method was conducted, along with solutions addressing issues related to predicting the technical condition of cutting tools for enterprises in the instrument-making and machinery industries under actual production conditions. The prediction of the technical condition of cutting tools was performed using artificial intelligence (AI) methods. The proposed approach for obtaining initial data for developing predictive models is characterized by its reliability, minimizing erroneous results from technical diagnostic and control systems operating independently.
Basova et al. (Mon,) studied this question.
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