Method for predicting tool condition using kriging analysis of normalised frequency shifts of spindle acceleration signature and validation in trimming operations of CFRPs-Reference-Cited by-同舟云学术

Method for predicting tool condition using kriging analysis of normalised frequency shifts of spindle acceleration signature and validation in trimming operations of CFRPs

Published:2022-10-14 Issue: Volume: Page:1-22
ISSN:2374-068X
Container-title:Advances in Materials and Processing Technologies
language:en
Short-container-title:Advances in Materials and Processing Technologies

Author:

El-Sinawi Ameen¹^ORCID,Sheikh-Ahmad Jamal²,Karumuri Srinivasa³,Guha Koushik⁴

Affiliation:

1. Department of Engineering, the American University of Iraq at Sulaimani, Kurdistan Region, Iraq

2. Mechanical Engineering Department, Khalifa University of Science and Technology, Abu Dhabi, UAE, P O Box 127788

3. Department of Electrical Engineering, K L University, Guntur, India

4. Department of Electronics and Communication Engineering, National Institute of Technology, Silchar, India

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Mechanics of Materials,General Materials Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/2374068X.2022.2130876

Reference37 articles.

1. Multi-objective optimization of the trimming operation of CFRPs using sensor-fused neural networks and TOPSIS

2. In-Process Detection of Tool Failure in Milling Using Cutting Force Models

3. In-process detection of tool breakages using time series monitoring of cutting forces

4. Tool condition monitoring in milling based on cutting forces by a neural network

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