There is logic in logit - Including wear rate in Colding's tool wear model
Laakso, Sampsa V.A. LU
and Johansson, Daniel
LU
(2020)
29th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2019
In Procedia Manufacturing
38.
p.1066-1073
- Abstract
Modelling of tool wear in metal cutting processes has been the foundation of the field since the famous Taylor's tool life model. Tool wear models have been developed for planning machining operations and calculating production costs. Most wear models do not include wear rate in the model but rather just the final wear at end of tool life, i.e. the limiting wear. This is a major disadvantage of Taylor's model, and practically all the other experimental models of tool wear. The wear progression over time is lost with the selection the limiting wear. This paper proposes a new logit-function based model for wear rate that can be included in the existing models. In this work, in addition to Taylor's model, Colding's model is used with the... (More)
Modelling of tool wear in metal cutting processes has been the foundation of the field since the famous Taylor's tool life model. Tool wear models have been developed for planning machining operations and calculating production costs. Most wear models do not include wear rate in the model but rather just the final wear at end of tool life, i.e. the limiting wear. This is a major disadvantage of Taylor's model, and practically all the other experimental models of tool wear. The wear progression over time is lost with the selection the limiting wear. This paper proposes a new logit-function based model for wear rate that can be included in the existing models. In this work, in addition to Taylor's model, Colding's model is used with the proposed wear rate model. The outcome is a model that can predict the tool wear at a given cutting speed, feed and at any given time within the tool life range, without selection the limiting tool wear. The model can be also used inversely so that the output is the tool life at a given cutting parameters and wear. The results show good fit to the experiment data (~10 %) and the model captures the typical wear rate shape well.
(Less)
- author
- Laakso, Sampsa V.A.
LU
and Johansson, Daniel
LU
- organization
- publishing date
- 2020-02-07
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Colding's Model, Metal Cutting, Taylor's Model, Tool Wear, Wear Rate
- in
- Procedia Manufacturing
- volume
- 38
- pages
- 8 pages
- publisher
- Elsevier
- conference name
- 29th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2019
- conference location
- Limerick, Ireland
- conference dates
- 2019-06-24 - 2019-06-28
- external identifiers
-
- scopus:85083533153
- ISSN
- 2351-9789
- DOI
- 10.1016/j.promfg.2020.01.194
- language
- English
- LU publication?
- yes
- id
- e6263965-5f46-4217-b804-cbd59f911a19
- date added to LUP
- 2020-05-12 16:30:17
- date last changed
- 2022-04-18 22:22:36
@article{e6263965-5f46-4217-b804-cbd59f911a19,
abstract = {{<p>Modelling of tool wear in metal cutting processes has been the foundation of the field since the famous Taylor's tool life model. Tool wear models have been developed for planning machining operations and calculating production costs. Most wear models do not include wear rate in the model but rather just the final wear at end of tool life, i.e. the limiting wear. This is a major disadvantage of Taylor's model, and practically all the other experimental models of tool wear. The wear progression over time is lost with the selection the limiting wear. This paper proposes a new logit-function based model for wear rate that can be included in the existing models. In this work, in addition to Taylor's model, Colding's model is used with the proposed wear rate model. The outcome is a model that can predict the tool wear at a given cutting speed, feed and at any given time within the tool life range, without selection the limiting tool wear. The model can be also used inversely so that the output is the tool life at a given cutting parameters and wear. The results show good fit to the experiment data (~10 %) and the model captures the typical wear rate shape well.</p>}},
author = {{Laakso, Sampsa V.A. and Johansson, Daniel}},
issn = {{2351-9789}},
keywords = {{Colding's Model; Metal Cutting; Taylor's Model; Tool Wear; Wear Rate}},
language = {{eng}},
month = {{02}},
pages = {{1066--1073}},
publisher = {{Elsevier}},
series = {{Procedia Manufacturing}},
title = {{There is logic in logit - Including wear rate in Colding's tool wear model}},
url = {{http://dx.doi.org/10.1016/j.promfg.2020.01.194}},
doi = {{10.1016/j.promfg.2020.01.194}},
volume = {{38}},
year = {{2020}},
}