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Modelling cutting instability in rough turning 34CrNiMo6 steel

Author

Listed:
  • Juho Ratava
  • Mika Lohtander
  • Juha Varis

Abstract

To maximise rough turning efficiency, using robust constant parameters or constant measured parameter adaptive control is not enough, but true adaptive control is needed. In order to safely optimise volume removal rate, it is necessary to model the cutting instability appearing at high levels of feed rate. This allows the prediction of the phenomenon and thus use of maximal cutting values while maintaining safe and controlled operation at all times by applying adaptive control. In this paper, various models are studied based on cutting parameters, sensor data and a combination of both. The capabilities of the models to classify cutting samples captured from the machining process are then examined and a model suitable for cutting condition prediction is recommended.

Suggested Citation

  • Juho Ratava & Mika Lohtander & Juha Varis, 2016. "Modelling cutting instability in rough turning 34CrNiMo6 steel," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 25(4), pages 518-531.
    • Handle: RePEc:ids:ijores:v:25:y:2016:i:4:p:518-531
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