Tools
Tools
Garg, A., Bhalerao, Y. 
ORCID: https://orcid.org/0000-0002-0743-8633 and Tai, K.
(2013)
Review of empirical modelling techniques for modelling of turning process.
International Journal of Modelling, Identification and Control, 20 (2).
ISSN 1746-6180
Abstract
The most widely and well known machining process used is turning. The turning process possesses higher complexity and uncertainty and therefore several empirical modelling techniques such as artificial neural networks, regression analysis, fuzzy logic and support vector machines have been used for predicting the performance of the process. This paper reviews the applications of empirical modelling techniques in modelling of turning process and unearths the vital issues related to it.
| Item Type: | Article |
|---|---|
| Faculty \ School: | Faculty of Science > School of Engineering (former - to 2024) |
| UEA Research Groups: | Faculty of Science > Research Groups > Materials, Manufacturing & Process Modelling |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 14 Jan 2020 05:00 |
| Last Modified: | 07 Nov 2024 12:41 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/73616 |
| DOI: | 10.1504/IJMIC.2013.056184 |
Actions (login required)
 |
View Item |