A FULL METHOD FOR OPTIMIZING THE QUALITY OF MANUFACTURING BY CNC MACHINE-TOOL.

Journal Title: International Journal of Advanced Research (IJAR) - Year 2019, Vol 7, Issue 6

Abstract

In the steering methods of CNC machine tool presented in the literature, none use both the geometry and the cutting parameters to adjust the machine. In the steering methods of machine that we previously presented in our works, we always use an incidence matrix built from linear relationships between a collection of geometric deviations and a collection of correctors available in numerical control (NC). This matrix makes it possible to find the adjustment to be made on the tools which guarantees the geometric quality of the workpiece. Now, more and more machine tools are monitored by sensors (vibration, temperature, load, ...), and it is interesting to watch how we can connect this new collection of parameters to another new collection of possible corrections which would be the feeds, the speeds, the depths of pass, ... In this article, we present new feeds in the field of steering taking into account the relations between new collections of parameters which are, the load, the torque and the feed rate. It is possible to determine from an experimental assembly the linear relationships that exist between these new collections of parameters to apply a more ??global incidence matrix??. If we know the measurement of the parameters obtained thanks to the experimental assembly and the measurement of the geometry of the part, it is then possible to find a more global setting which optimizes the whole of the process on all the parameters and to get the best quality possible regardless of the complexity of the part.

Authors and Affiliations

Abdelhakim Boukar and Diab Ahmat Diab.

Keywords

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International Journal of Advanced Research (IJAR)

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  • EP ID EP611941
  • DOI 10.21474/IJAR01/9236
  • Views 40
  • Downloads 0

How To Cite

Abdelhakim Boukar and Diab Ahmat Diab. (2019). A FULL METHOD FOR OPTIMIZING THE QUALITY OF MANUFACTURING BY CNC MACHINE-TOOL.. International Journal of Advanced Research (IJAR), 7(6), 392-402. https://europub.co.uk/articles/-A-611941