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April 24, 2026CIRP AnnalsOpen Access

Towards adaptive electrochemical machining via signal-based data-driven modelling

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Authors

ESElio Tchoupe SambouAKA. KlinkTHTim Herrig

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Overview

Demonstrates the potential of adaptive process control in electrochemical machining, suggesting enhanced efficiency and accessibility for manufacturers.

Key Points

  • The aim is to improve electrochemical machining by enabling real-time process monitoring and adaptive control through data-driven modeling.
  • Developed models using historical machining signals for process dynamics monitoring.
  • Analyzed measured data to infer current process conditions.
  • Proposed a framework for closed-loop process control.
  • The model effectively predicts prevailing process conditions from historical data.
  • Adaptive control can lower the barriers of entry for manufacturers new to electrochemical machining.
  • Data-driven monitoring enhances reliability and efficiency of the machining process.

Cite This Study

Sambou et al. (2026) studied this question.

synapsesocial.com/papers/69eb092b553a5433e34b3b99https://doi.org/10.1016/j.cirp.2026.03.020
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