Confidence machine learning for cutting tool life prediction

Nishant Wilson, Steve Barwick, Vince Booker, Tom Mildenhall, Laura Still, Yan Wang, Khuong An Nguyen
Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications, PMLR 152:294-296, 2021.

Abstract

The work aims to develop an automatic cutting tool life prediction model for die-cuts machine at Parafix. Such model will be able to estimate how long a given tool is likely to last, in order to improve performance and productivity. This work is part of the KTP project between Parafix and University of Brighton.

Cite this Paper

BibTeX
@InProceedings{pmlr-v152-wilson21a, title = {Confidence machine learning for cutting tool life prediction}, author = {Wilson, Nishant and Barwick, Steve and Booker, Vince and Mildenhall, Tom and Still, Laura and Wang, Yan and An Nguyen, Khuong}, booktitle = {Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications}, pages = {294--296}, year = {2021}, editor = {Carlsson, Lars and Luo, Zhiyuan and Cherubin, Giovanni and An Nguyen, Khuong}, volume = {152}, series = {Proceedings of Machine Learning Research}, month = {08--10 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v152/wilson21a/wilson21a.pdf}, url = {https://proceedings.mlr.press/v152/wilson21a.html}, abstract = {The work aims to develop an automatic cutting tool life prediction model for die-cuts machine at Parafix. Such model will be able to estimate how long a given tool is likely to last, in order to improve performance and productivity. This work is part of the KTP project between Parafix and University of Brighton.} }
Endnote
%0 Conference Paper %T Confidence machine learning for cutting tool life prediction %A Nishant Wilson %A Steve Barwick %A Vince Booker %A Tom Mildenhall %A Laura Still %A Yan Wang %A Khuong An Nguyen %B Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications %C Proceedings of Machine Learning Research %D 2021 %E Lars Carlsson %E Zhiyuan Luo %E Giovanni Cherubin %E Khuong An Nguyen %F pmlr-v152-wilson21a %I PMLR %P 294--296 %U https://proceedings.mlr.press/v152/wilson21a.html %V 152 %X The work aims to develop an automatic cutting tool life prediction model for die-cuts machine at Parafix. Such model will be able to estimate how long a given tool is likely to last, in order to improve performance and productivity. This work is part of the KTP project between Parafix and University of Brighton.
APA
Wilson, N., Barwick, S., Booker, V., Mildenhall, T., Still, L., Wang, Y. & An Nguyen, K.. (2021). Confidence machine learning for cutting tool life prediction. Proceedings of the Tenth Symposium on Conformal and Probabilistic Prediction and Applications, in Proceedings of Machine Learning Research 152:294-296 Available from https://proceedings.mlr.press/v152/wilson21a.html.

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