Confidence Machine Learning for cutting tool life prediction

Nishant Wilson; Steve Barwick; Vince Booker; Tom Mildenhall; Laura Still; Yan Wang; Khuong An Nguyen

Confidence Machine Learning for cutting tool life prediction

Nishant Wilson, Steve Barwick, Vince Booker, Tom Mildenhall, Laura Still, Yan Wang, Khuong An Nguyen

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

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.

Original language	English
Pages	294-296
Number of pages	3
Publication status	Published - 1 Sept 2021

Keywords

Tool life prediction
predictive maintenance
Conformal Clustering

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Cite this

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title = "Confidence Machine Learning for cutting tool life prediction",

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.",

keywords = "Tool life prediction, predictive maintenance, Conformal Clustering",

author = "Nishant Wilson and Steve Barwick and Vince Booker and Tom Mildenhall and Laura Still and Yan Wang and Nguyen, {Khuong An}",

note = "10th Symposium on Conformal and Probabilistic Prediction with Applications ; Conference date: 08-09-2021 Through 10-09-2021",

year = "2021",

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day = "1",

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pages = "294--296",

}

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T1 - Confidence Machine Learning for cutting tool life prediction

AU - Wilson, Nishant

AU - Barwick, Steve

AU - Booker, Vince

AU - Mildenhall, Tom

AU - Still, Laura

AU - Wang, Yan

AU - Nguyen, Khuong An

N1 - 10th Symposium on Conformal and Probabilistic Prediction with Applications ; Conference date: 08-09-2021 Through 10-09-2021

PY - 2021/9/1

Y1 - 2021/9/1

N2 - 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.

AB - 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.

KW - Tool life prediction

KW - predictive maintenance

KW - Conformal Clustering

M3 - Paper

SP - 294

EP - 296

ER -